From 15a7345050b404daa40440a70751d2cd45292fc7 Mon Sep 17 00:00:00 2001
From: franciscoeacosta <facosta@ucsb.edu>
Date: Thu, 12 Sep 2024 20:59:28 -0700
Subject: [PATCH 1/6] create immersion estimator

---
 neurometry/estimators/geometry/__init__.py    |   3 +
 .../geometry/immersion_estimator.py           |   0
 .../estimators/geometry/metric_estimator.py   |   0
 .../estimators/geometry/spherical_vae.py      | 174 +++++++++++++++
 .../estimators/geometry/toroidal_vae.py       | 201 ++++++++++++++++++
 5 files changed, 378 insertions(+)
 create mode 100644 neurometry/estimators/geometry/__init__.py
 create mode 100644 neurometry/estimators/geometry/immersion_estimator.py
 create mode 100644 neurometry/estimators/geometry/metric_estimator.py
 create mode 100644 neurometry/estimators/geometry/spherical_vae.py
 create mode 100644 neurometry/estimators/geometry/toroidal_vae.py

diff --git a/neurometry/estimators/geometry/__init__.py b/neurometry/estimators/geometry/__init__.py
new file mode 100644
index 0000000..8f20503
--- /dev/null
+++ b/neurometry/estimators/geometry/__init__.py
@@ -0,0 +1,3 @@
+"""Initialize folder as submodule."""
+
+__version__ = "0.0.1"
diff --git a/neurometry/estimators/geometry/immersion_estimator.py b/neurometry/estimators/geometry/immersion_estimator.py
new file mode 100644
index 0000000..e69de29
diff --git a/neurometry/estimators/geometry/metric_estimator.py b/neurometry/estimators/geometry/metric_estimator.py
new file mode 100644
index 0000000..e69de29
diff --git a/neurometry/estimators/geometry/spherical_vae.py b/neurometry/estimators/geometry/spherical_vae.py
new file mode 100644
index 0000000..c0414ab
--- /dev/null
+++ b/neurometry/estimators/geometry/spherical_vae.py
@@ -0,0 +1,174 @@
+"""G-manifold deep learning.
+
+This file gathers deep learning models related to G-manifold learning.
+"""
+
+import torch
+from torch.distributions.normal import Normal
+from torch.nn import functional as F
+
+from neurometry.estimators.curvature.hyperspherical.distributions.von_mises_fisher import (
+    VonMisesFisher,
+)
+
+
+class SphericalVAE(torch.nn.Module):
+    """VAE with Linear (fully connected) layers.
+
+    Parameters
+    ----------
+    num_neurons : int
+        Number of neurons in the input data. This is the ambient dimension of the neural state space.
+        Example: 40 for neural recordings of 40 neurons.
+    latent_dim : int
+        Dimension of the latent space.
+        Example: 2.
+    """
+
+    def __init__(
+        self,
+        num_neurons,
+        latent_dim,
+        sftbeta,
+        encoder_width=400,
+        encoder_depth=2,
+        decoder_width=400,
+        decoder_depth=2,
+        drop_out_p=0.0,
+    ):
+        super().__init__()
+        self.num_neurons = num_neurons
+        self.sftbeta = sftbeta
+        self.latent_dim = latent_dim
+        self.drop_out_p = drop_out_p
+
+        decoder_width = encoder_width
+        decoder_depth = encoder_depth
+
+        self.encoder_fc = torch.nn.Linear(self.num_neurons, encoder_width)
+        self.encoder_linears = torch.nn.ModuleList(
+            [
+                torch.nn.Linear(encoder_width, encoder_width)
+                for _ in range(encoder_depth)
+            ]
+        )
+
+        self.fc_z_mu = torch.nn.Linear(encoder_width, self.latent_dim)
+        self.fc_z_logvar = torch.nn.Linear(encoder_width, 1)  # kappa
+
+        self.decoder_fc = torch.nn.Linear(self.latent_dim, decoder_width)
+        self.decoder_linears = torch.nn.ModuleList(
+            [
+                torch.nn.Linear(decoder_width, decoder_width)
+                for _ in range(decoder_depth)
+            ]
+        )
+
+        self.fc_x_mu = torch.nn.Linear(decoder_width, self.num_neurons)
+
+        self.drop_out = torch.nn.Dropout(p=self.drop_out_p)
+
+    def encode(self, x):
+        """Encode input into mean and log-variance.
+
+        The parameters mean (mu) and variance (computed
+        from logvar) defines a multivariate Gaussian
+        that represents the approximate posterior of the
+        latent variable z given the input x.
+
+        Parameters
+        ----------
+        x : array-like, shape=[batch_size, num_neurons]
+            Input data.
+
+        Returns
+        -------
+        mu : array-like, shape=[batch_size, latent_dim]
+            Mean of multivariate Gaussian in latent space.
+        logvar : array-like, shape=[batch_size, latent_dim]
+            Vector representing the diagonal covariance of the
+            multivariate Gaussian in latent space.
+        """
+        h = F.softplus(self.encoder_fc(x.double()), beta=self.sftbeta)
+
+        for _i_layer, layer in enumerate(self.encoder_linears):
+            # h = self.drop_out(h)
+            h = layer(h)
+            h = F.softplus(h, beta=self.sftbeta)
+
+        z_mu = self.fc_z_mu(h)
+        z_kappa = F.softplus(self.fc_z_logvar(h)) + 1
+        posterior_params = z_mu, z_kappa
+
+        return posterior_params
+
+    def reparameterize(self, posterior_params):
+        """
+        Apply reparameterization trick. We 'eternalize' the
+        randomness in z by re-parameterizing the variable as
+        a deterministic and differentiable function of x,
+        the encoder weights, and a new random variable eps.
+
+        Parameters
+        ----------
+        posterior_params : tuple
+            Distributional parameters of approximate posterior. ((e.g.), (z_mu,z_logvar) for Gaussian.
+
+        Returns
+        -------
+
+        z: array-like, shape = [batch_size, latent_dim]
+            Re-parameterized latent variable.
+        """
+
+        z_mu, z_kappa = posterior_params
+        q_z = VonMisesFisher(z_mu, z_kappa)
+
+        return q_z.rsample()
+
+    def decode(self, z):
+        """Decode latent variable z into data.
+
+        Parameters
+        ----------
+        z : array-like, shape=[batch_size, latent_dim]
+            Input to the decoder.
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size, num_neurons]
+            Reconstructed data corresponding to z.
+        """
+
+        h = F.softplus(self.decoder_fc(z), beta=self.sftbeta)
+
+        for _i_layer, layer in enumerate(self.decoder_linears):
+            # h = self.drop_out(h)
+            h = layer(h)
+            h = F.softplus(h, beta=self.sftbeta)
+
+        return self.fc_x_mu(h)
+
+    def forward(self, x):
+        """Run VAE: Encode, sample and decode.
+
+        Parameters
+        ----------
+        x : array-like, shape=[batch_size, num_neurons]
+            Input data.
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size, num_neurons]
+            Reconstructed data corresponding to z.
+        mu : array-like, shape=[batch_size, latent_dim]
+            Mean of multivariate Gaussian in latent space.
+        logvar : array-like, shape=[batch_size, latent_dim]
+            Vector representing the diagonal covariance of the
+            multivariate Gaussian in latent space.
+        """
+
+        posterior_params = self.encode(x)
+        z = self.reparameterize(posterior_params)
+        x_mu = self.decode(z)
+        return z, x_mu, posterior_params
diff --git a/neurometry/estimators/geometry/toroidal_vae.py b/neurometry/estimators/geometry/toroidal_vae.py
new file mode 100644
index 0000000..191f78c
--- /dev/null
+++ b/neurometry/estimators/geometry/toroidal_vae.py
@@ -0,0 +1,201 @@
+"""G-manifold deep learning.
+
+This file gathers deep learning models related to G-manifold learning.
+"""
+
+import geomstats.backend as gs
+import torch
+from torch.nn import functional as F
+
+from neurometry.estimators.curvature.hyperspherical.distributions.von_mises_fisher import (
+    VonMisesFisher,
+)
+
+
+class ToroidalVAE(torch.nn.Module):
+    """VAE with Linear (fully connected) layers.
+
+    Parameters
+    ----------
+    data_dim : int
+        Dimension of input data.
+        Example: 40 for neural recordings of 40 units/clusters.
+    latent_dim : int
+        Dimension of the latent space.
+        Example: 2.
+    """
+
+    def __init__(
+        self,
+        data_dim,
+        latent_dim,
+        sftbeta,
+        encoder_width,
+        encoder_depth,
+        decoder_width,
+        decoder_depth,
+        posterior_type,
+    ):
+        super().__init__()
+        self.data_dim = data_dim
+        self.sftbeta = sftbeta
+        self.latent_dim = latent_dim
+        self.posterior_type = posterior_type
+
+        # decoder_width = encoder_width
+        # decoder_depth = encoder_depth
+
+        self.encoder_fc = torch.nn.Linear(self.data_dim, encoder_width)
+        self.encoder_linears = torch.nn.ModuleList(
+            [
+                torch.nn.Linear(encoder_width, encoder_width)
+                for _ in range(encoder_depth)
+            ]
+        )
+
+        self.fc_z_theta_mu = torch.nn.Linear(encoder_width, self.latent_dim)
+        self.fc_z_theta_kappa = torch.nn.Linear(encoder_width, 1)
+
+        self.fc_z_phi_mu = torch.nn.Linear(encoder_width, self.latent_dim)
+        self.fc_z_phi_kappa = torch.nn.Linear(encoder_width, 1)
+
+        self.decoder_fc = torch.nn.Linear(3, decoder_width)
+        self.decoder_linears = torch.nn.ModuleList(
+            [
+                torch.nn.Linear(decoder_width, decoder_width)
+                for _ in range(decoder_depth)
+            ]
+        )
+
+        self.fc_x_mu = torch.nn.Linear(decoder_width, self.data_dim)
+
+    def encode(self, x):
+        """Encode input into mean and log-variance.
+
+        The parameters mean (mu) and variance (computed
+        from logvar) defines a multivariate Gaussian
+        that represents the approximate posterior of the
+        latent variable z given the input x.
+
+        Parameters
+        ----------
+        x : array-like, shape=[batch_size, data_dim]
+            Input data.
+
+        Returns
+        -------
+        mu : array-like, shape=[batch_size, latent_dim]
+            Mean of multivariate Gaussian in latent space.
+        logvar : array-like, shape=[batch_size, latent_dim]
+            Vector representing the diagonal covariance of the
+            multivariate Gaussian in latent space.
+        """
+        h = F.softplus(self.encoder_fc(x), beta=self.sftbeta)
+
+        for layer in self.encoder_linears:
+            h = F.softplus(layer(h), beta=self.sftbeta)
+
+        z_theta_mu = self.fc_z_theta_mu(h)
+        z_theta_kappa = F.softplus(self.fc_z_theta_kappa(h)) + 1
+
+        z_phi_mu = self.fc_z_phi_mu(h)
+        z_phi_kappa = F.softplus(self.fc_z_phi_kappa(h)) + 1
+
+        return z_theta_mu, z_theta_kappa, z_phi_mu, z_phi_kappa
+
+    def _build_torus(self, z_theta, z_phi):
+        # theta = torch.atan2(z_theta[:, 1] / z_theta[:, 0])
+        # phi = torch.atan2(z_phi[:, 1] / z_phi[:, 0])
+        cos_theta = z_theta[:, 0]
+        sin_theta = z_theta[:, 1]
+
+        cos_phi = z_phi[:, 0]
+        sin_phi = z_phi[:, 1]
+
+        major_radius = 2
+        minor_radius = 1
+
+        x = (major_radius - minor_radius * cos_theta) * cos_phi
+        y = (major_radius - minor_radius * cos_theta) * sin_phi
+        z = minor_radius * sin_theta
+
+        return gs.stack([x, y, z], axis=-1)
+
+    def reparameterize(self, posterior_params):
+        """
+        Apply reparameterization trick. We 'eternalize' the
+        randomness in z by re-parameterizing the variable as
+        a deterministic and differentiable function of x,
+        the encoder weights, and a new random variable eps.
+
+        Parameters
+        ----------
+        posterior_params : tuple
+            Distributional parameters of approximate posterior. ((e.g.), (z_mu,z_logvar) for Gaussian.
+
+        Returns
+        -------
+
+        z: array-like, shape = [batch_size, latent_dim]
+            Re-parameterized latent variable.
+        """
+
+        z_theta_mu, z_theta_kappa, z_phi_mu, z_phi_kappa = posterior_params
+
+        q_z_theta = VonMisesFisher(z_theta_mu, z_theta_kappa)
+
+        q_z_phi = VonMisesFisher(z_phi_mu, z_phi_kappa)
+
+        z_theta = q_z_theta.rsample()
+
+        z_phi = q_z_phi.rsample()
+
+        return self._build_torus(z_theta, z_phi)
+
+    def decode(self, z):
+        """Decode latent variable z into data.
+
+        Parameters
+        ----------
+        z : array-like, shape=[batch_size, latent_dim]
+            Input to the decoder.
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size, data_dim]
+            Reconstructed data corresponding to z.
+        """
+
+        h = F.softplus(self.decoder_fc(z), beta=self.sftbeta)
+
+        for layer in self.decoder_linears:
+            h = F.softplus(layer(h), beta=self.sftbeta)
+
+        return self.fc_x_mu(h)
+
+    def forward(self, x):
+        """Run VAE: Encode, sample and decode.
+
+        Parameters
+        ----------
+        x : array-like, shape=[batch_size, data_dim]
+            Input data.
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size, data_dim]
+            Reconstructed data corresponding to z.
+        mu : array-like, shape=[batch_size, latent_dim]
+            Mean of multivariate Gaussian in latent space.
+        logvar : array-like, shape=[batch_size, latent_dim]
+            Vector representing the diagonal covariance of the
+            multivariate Gaussian in latent space.
+        """
+
+        posterior_params = self.encode(x)
+
+        z = self.reparameterize(posterior_params)
+
+        x_mu = self.decode(z)
+
+        return z, x_mu, posterior_params

From 759652e93fe38051d7ab69d4c810963461adbc22 Mon Sep 17 00:00:00 2001
From: franciscoeacosta <facosta@ucsb.edu>
Date: Fri, 13 Sep 2024 08:25:37 -0700
Subject: [PATCH 2/6] ruff

---
 .../estimators/geometry/immersion_estimator.py  | 17 +++++++++++++++++
 neurometry/estimators/geometry/spherical_vae.py |  4 +---
 2 files changed, 18 insertions(+), 3 deletions(-)

diff --git a/neurometry/estimators/geometry/immersion_estimator.py b/neurometry/estimators/geometry/immersion_estimator.py
index e69de29..e93d8ed 100644
--- a/neurometry/estimators/geometry/immersion_estimator.py
+++ b/neurometry/estimators/geometry/immersion_estimator.py
@@ -0,0 +1,17 @@
+
+from sklearn.base import BaseEstimator
+
+
+class ImmersionEstimator(BaseEstimator):
+    def __init__(self, num_neurons, intrinsic_dimension, topology):
+
+        self.estimate_ = None
+        self.num_neurons = num_neurons
+        self.intrinsic_dimension = intrinsic_dimension
+        self.topology = topology
+
+
+
+
+
+
diff --git a/neurometry/estimators/geometry/spherical_vae.py b/neurometry/estimators/geometry/spherical_vae.py
index c0414ab..fd32f77 100644
--- a/neurometry/estimators/geometry/spherical_vae.py
+++ b/neurometry/estimators/geometry/spherical_vae.py
@@ -4,7 +4,6 @@
 """
 
 import torch
-from torch.distributions.normal import Normal
 from torch.nn import functional as F
 
 from neurometry.estimators.curvature.hyperspherical.distributions.von_mises_fisher import (
@@ -98,9 +97,8 @@ def encode(self, x):
 
         z_mu = self.fc_z_mu(h)
         z_kappa = F.softplus(self.fc_z_logvar(h)) + 1
-        posterior_params = z_mu, z_kappa
 
-        return posterior_params
+        return z_mu, z_kappa
 
     def reparameterize(self, posterior_params):
         """

From b1ef0558e10117951f6f680628380bd36f618088 Mon Sep 17 00:00:00 2001
From: franciscoeacosta <facosta@ucsb.edu>
Date: Fri, 13 Sep 2024 17:37:09 -0700
Subject: [PATCH 3/6] implement ImmersionEstimator for hypersphere

---
 neurometry/datasets/synthetic.py              |   17 +-
 .../geometry/immersion_estimator.py           |   83 +-
 .../estimators/geometry/metric_estimator.py   |   24 +
 .../estimators/geometry/models/__init__.py    |    3 +
 .../models/hyperspherical/__init__.py         |    0
 .../hyperspherical/distributions/__init__.py  |    0
 .../distributions/hyperspherical_uniform.py   |   56 +
 .../distributions/von_mises_fisher.py         |  213 +
 .../models/hyperspherical/ops/__init__.py     |    0
 .../geometry/models/hyperspherical/ops/ive.py |   76 +
 .../estimators/geometry/models/losses.py      |  176 +
 .../geometry/models/spherical_vae.py          |  263 +
 .../geometry/{ => models}/toroidal_vae.py     |   40 +-
 .../estimators/geometry/models/train.py       |  107 +
 .../geometry/models/train_config.py           |   13 +
 .../estimators/geometry/models/utils.py       |  248 +
 .../estimators/geometry/spherical_vae.py      |  172 -
 .../topology/topology_classifier.py           |   11 +-
 .../topology/test_topology_classifier.py      |    1 -
 ..._methods_estimate_manifold_immersion.ipynb | 9026 +++++++++++++++++
 20 files changed, 10320 insertions(+), 209 deletions(-)
 create mode 100644 neurometry/estimators/geometry/models/__init__.py
 create mode 100644 neurometry/estimators/geometry/models/hyperspherical/__init__.py
 create mode 100644 neurometry/estimators/geometry/models/hyperspherical/distributions/__init__.py
 create mode 100644 neurometry/estimators/geometry/models/hyperspherical/distributions/hyperspherical_uniform.py
 create mode 100644 neurometry/estimators/geometry/models/hyperspherical/distributions/von_mises_fisher.py
 create mode 100644 neurometry/estimators/geometry/models/hyperspherical/ops/__init__.py
 create mode 100644 neurometry/estimators/geometry/models/hyperspherical/ops/ive.py
 create mode 100644 neurometry/estimators/geometry/models/losses.py
 create mode 100644 neurometry/estimators/geometry/models/spherical_vae.py
 rename neurometry/estimators/geometry/{ => models}/toroidal_vae.py (85%)
 create mode 100644 neurometry/estimators/geometry/models/train.py
 create mode 100644 neurometry/estimators/geometry/models/train_config.py
 create mode 100644 neurometry/estimators/geometry/models/utils.py
 delete mode 100644 neurometry/estimators/geometry/spherical_vae.py
 create mode 100644 tutorials/04_methods_estimate_manifold_immersion.ipynb

diff --git a/neurometry/datasets/synthetic.py b/neurometry/datasets/synthetic.py
index d9613c1..32c8ed2 100644
--- a/neurometry/datasets/synthetic.py
+++ b/neurometry/datasets/synthetic.py
@@ -75,7 +75,9 @@ def hypersphere(intrinsic_dim, num_points, radius=1):
     """
     unit_hypersphere = Hypersphere(dim=intrinsic_dim)
     unit_hypersphere_points = unit_hypersphere.random_point(n_samples=num_points)
-    intrinsic_coords = unit_hypersphere.extrinsic_to_intrinsic_coords(unit_hypersphere_points)
+    intrinsic_coords = unit_hypersphere.extrinsic_to_intrinsic_coords(
+        unit_hypersphere_points
+    )
     return radius * unit_hypersphere_points, intrinsic_coords
 
 
@@ -110,9 +112,14 @@ def hypertorus(intrinsic_dim, num_points, radii=None, parameterization="flat"):
             hypertorus_points[:, _, :] = radii[_] * unit_hypertorus_points[:, _, :]
     intrinsic_coords = torch.zeros(num_points, intrinsic_dim)
     for i, factor in enumerate(unit_hypertorus.factors):
-        intrinsic_coords[:, i] = factor.extrinsic_to_intrinsic_coords(hypertorus_points[:, i, :]).squeeze()
+        intrinsic_coords[:, i] = factor.extrinsic_to_intrinsic_coords(
+            hypertorus_points[:, i, :]
+        ).squeeze()
 
-    return gs.reshape(hypertorus_points, (num_points, intrinsic_dim * 2)), intrinsic_coords
+    return (
+        gs.reshape(hypertorus_points, (num_points, intrinsic_dim * 2)),
+        intrinsic_coords,
+    )
 
 
 def cylinder(num_points, radius=1):
@@ -132,7 +139,9 @@ def cylinder(num_points, radius=1):
     cylinder = ProductManifold(factors=factors)
     cylinder_points = cylinder.random_point(n_samples=num_points, bound=1)
     intrinsic_coords = torch.zeros(num_points, 2)
-    intrinsic_coords[:, 0] = factors[0].extrinsic_to_intrinsic_coords(cylinder_points[:, :2]).squeeze()
+    intrinsic_coords[:, 0] = (
+        factors[0].extrinsic_to_intrinsic_coords(cylinder_points[:, :2]).squeeze()
+    )
     intrinsic_coords[:, 1] = cylinder_points[:, 2]
     cylinder_points[:, :2] = radius * cylinder_points[:, :2]
     return cylinder_points, intrinsic_coords
diff --git a/neurometry/estimators/geometry/immersion_estimator.py b/neurometry/estimators/geometry/immersion_estimator.py
index e93d8ed..a8efba4 100644
--- a/neurometry/estimators/geometry/immersion_estimator.py
+++ b/neurometry/estimators/geometry/immersion_estimator.py
@@ -1,17 +1,92 @@
+import os
 
+os.environ["GEOMSTATS_BACKEND"] = "pytorch"
+import geomstats.backend as gs
+import torch
 from sklearn.base import BaseEstimator
+from sklearn.model_selection import train_test_split
+from torch.utils.data import DataLoader, TensorDataset
 
+import neurometry.estimators.geometry.models.train_config as train_config
+from neurometry.estimators.geometry.models.spherical_vae import SphericalVAE
+from neurometry.estimators.geometry.models.toroidal_vae import ToroidalVAE
+from neurometry.estimators.geometry.models.train import train_test
 
-class ImmersionEstimator(BaseEstimator):
-    def __init__(self, num_neurons, intrinsic_dimension, topology):
 
+class ImmersionEstimator(BaseEstimator):
+    def __init__(self, extrinsic_dim, topology, device):
         self.estimate_ = None
-        self.num_neurons = num_neurons
-        self.intrinsic_dimension = intrinsic_dimension
+        self.device = device
+        self.extrinsic_dim = extrinsic_dim
         self.topology = topology
+        self.latent_dims = {"circle": 2, "sphere": 3, "torus": 3}
+        self.model = self._get_model()
 
+    def _get_model(self):
+        if self.topology == "circle" or self.topology == "sphere":
+            return SphericalVAE(
+                extrinsic_dim=self.extrinsic_dim,
+                latent_dim=self.latent_dims[self.topology],
+            ).to(self.device)
+        if self.topology == "torus":
+            return ToroidalVAE(
+                extrinsic_dim=self.extrinsic_dim,
+                latent_dim=self.latent_dims[self.topology],
+            ).to(self.device)
+        raise ValueError("Topology not supported")
 
+    def _intrinsic_to_extrinsic(self):
+        if self.topology == "circle":
+            return lambda x: gs.array([gs.cos(x), gs.sin(x)])
+        if self.topology == "sphere":
+            return lambda x: gs.array(
+                [
+                    gs.sin(x[0]) * gs.cos(x[1]),
+                    gs.sin(x[0]) * gs.sin(x[1]),
+                    gs.cos(x[0]),
+                ]
+            )
+        if self.topology == "torus":
+            return lambda x: gs.array(
+                [
+                    (1 - gs.cos(x[0])) * gs.cos(x[1]),
+                    (1 - gs.cos(x[0])) * gs.sin(x[1]),
+                    gs.sin(x[0]),
+                ]
+            )
+        raise ValueError("Topology not supported")
 
+    def fit(self, X, y=None):
+        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
+        X_train = torch.tensor(X_train).to(self.device)
+        X_test = torch.tensor(X_test).to(self.device)
+        y_train = torch.tensor(y_train).to(self.device)
+        y_test = torch.tensor(y_test).to(self.device)
+        train_loader = DataLoader(
+            TensorDataset(X_train, y_train),
+            batch_size=train_config.batch_size,
+            shuffle=True,
+        )
+        test_loader = DataLoader(
+            TensorDataset(X_test, y_test),
+            batch_size=train_config.batch_size,
+            shuffle=True,
+        )
 
+        optimizer = torch.optim.Adam(
+            self.model.parameters(), lr=train_config.lr, amsgrad=True
+        )
+        train_losses, test_losses, best_model = train_test(
+            model=self.model,
+            train_loader=train_loader,
+            test_loader=test_loader,
+            optimizer=optimizer,
+            scheduler=None,
+            config=train_config,
+        )
 
+        self.estimate_ = lambda task_variable: best_model.decode(
+            self._intrinsic_to_extrinsic()(task_variable).T
+        )
 
+        return self
diff --git a/neurometry/estimators/geometry/metric_estimator.py b/neurometry/estimators/geometry/metric_estimator.py
index e69de29..e4cd230 100644
--- a/neurometry/estimators/geometry/metric_estimator.py
+++ b/neurometry/estimators/geometry/metric_estimator.py
@@ -0,0 +1,24 @@
+# import os
+
+# os.environ["GEOMSTATS_BACKEND"] = "pytorch"
+# from geomstats.geometry.base import ImmersedSet
+# from geomstats.geometry.euclidean import Euclidean
+# from geomstats.geometry.pullback_metric import PullbackMetric
+
+
+# class NeuralManifoldIntrinsic(ImmersedSet):
+#     def __init__(self, dim, neural_embedding_dim, neural_immersion, equip=True):
+#         self.neural_embedding_dim = neural_embedding_dim
+#         super().__init__(dim=dim, equip=equip)
+#         self.neural_immersion = neural_immersion
+
+#     def immersion(self, point):
+#         return self.neural_immersion(point)
+
+#     def _define_embedding_space(self):
+#         return Euclidean(dim=self.neural_embedding_dim)
+
+#     neural_manifold = NeuralManifoldIntrinsic(
+#         dim, embedding_dim, immersion, equip=False
+#     )
+#     neural_manifold.equip_with_metric(PullbackMetric)
diff --git a/neurometry/estimators/geometry/models/__init__.py b/neurometry/estimators/geometry/models/__init__.py
new file mode 100644
index 0000000..8f20503
--- /dev/null
+++ b/neurometry/estimators/geometry/models/__init__.py
@@ -0,0 +1,3 @@
+"""Initialize folder as submodule."""
+
+__version__ = "0.0.1"
diff --git a/neurometry/estimators/geometry/models/hyperspherical/__init__.py b/neurometry/estimators/geometry/models/hyperspherical/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/neurometry/estimators/geometry/models/hyperspherical/distributions/__init__.py b/neurometry/estimators/geometry/models/hyperspherical/distributions/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/neurometry/estimators/geometry/models/hyperspherical/distributions/hyperspherical_uniform.py b/neurometry/estimators/geometry/models/hyperspherical/distributions/hyperspherical_uniform.py
new file mode 100644
index 0000000..20f8a41
--- /dev/null
+++ b/neurometry/estimators/geometry/models/hyperspherical/distributions/hyperspherical_uniform.py
@@ -0,0 +1,56 @@
+import math
+
+import torch
+
+
+class HypersphericalUniform(torch.distributions.Distribution):
+    arg_constraints = {}
+    support = torch.distributions.constraints.real
+    has_rsample = False
+    _mean_carrier_measure = 0
+
+    @property
+    def dim(self):
+        return self._dim
+
+    @property
+    def device(self):
+        return self._device
+
+    @device.setter
+    def device(self, val):
+        self._device = val if isinstance(val, torch.device) else torch.device(val)
+
+    def __init__(self, dim, validate_args=None, device=None):
+        super().__init__(torch.Size([dim]), validate_args=validate_args)
+        self._dim = dim
+        self.device = device
+
+    def sample(self, shape=None):
+        if shape is None:
+            shape = torch.Size()
+        output = (
+            torch.distributions.Normal(0, 1)
+            .sample(
+                (shape if isinstance(shape, torch.Size) else torch.Size([shape]))
+                + torch.Size([self._dim + 1])
+            )
+            .to(self.device)
+        )
+
+        return output / output.norm(dim=-1, keepdim=True)
+
+    def entropy(self):
+        return self.__log_surface_area()
+
+    def log_prob(self, x):
+        return -torch.ones(x.shape[:-1], device=self.device) * self.__log_surface_area()
+
+    def __log_surface_area(self):
+        if torch.__version__ >= "1.0.0":
+            lgamma = torch.lgamma(torch.tensor([(self._dim + 1) / 2]).to(self.device))
+        else:
+            lgamma = torch.lgamma(
+                torch.Tensor([(self._dim + 1) / 2], device=self.device)
+            )
+        return math.log(2) + ((self._dim + 1) / 2) * math.log(math.pi) - lgamma
diff --git a/neurometry/estimators/geometry/models/hyperspherical/distributions/von_mises_fisher.py b/neurometry/estimators/geometry/models/hyperspherical/distributions/von_mises_fisher.py
new file mode 100644
index 0000000..1ea089b
--- /dev/null
+++ b/neurometry/estimators/geometry/models/hyperspherical/distributions/von_mises_fisher.py
@@ -0,0 +1,213 @@
+import math
+
+import torch
+from torch.distributions.kl import register_kl
+
+from neurometry.estimators.geometry.models.hyperspherical.ops.ive import ive
+
+from .hyperspherical_uniform import (
+    HypersphericalUniform,
+)
+
+
+class VonMisesFisher(torch.distributions.Distribution):
+    arg_constraints = {
+        "loc": torch.distributions.constraints.real,
+        "scale": torch.distributions.constraints.positive,
+    }
+    support = torch.distributions.constraints.real
+    has_rsample = True
+    _mean_carrier_measure = 0
+
+    @property
+    def mean(self):
+        # option 1:
+        return self.loc * (
+            ive(self.__m / 2, self.scale) / ive(self.__m / 2 - 1, self.scale)
+        )
+        # option 2:
+        # return self.loc * ive_fraction_approx(torch.tensor(self.__m / 2), self.scale)
+        # options 3:
+        # return self.loc * ive_fraction_approx2(torch.tensor(self.__m / 2), self.scale)
+
+    @property
+    def stddev(self):
+        return self.scale
+
+    def __init__(self, loc, scale, validate_args=None, k=1):
+        self.dtype = loc.dtype
+        self.loc = loc
+        self.scale = scale
+        self.device = loc.device
+        self.__m = loc.shape[-1]
+        self.__e1 = (torch.Tensor([1.0] + [0] * (loc.shape[-1] - 1))).to(self.device)
+        self.k = k
+
+        super().__init__(self.loc.size(), validate_args=validate_args)
+
+    def sample(self, shape=None):
+        if shape is None:
+            shape = torch.Size()
+        with torch.no_grad():
+            return self.rsample(shape)
+
+    def rsample(self, shape=None):
+        if shape is None:
+            shape = torch.Size()
+        shape = shape if isinstance(shape, torch.Size) else torch.Size([shape])
+
+        w = (
+            self.__sample_w3(shape=shape)
+            if self.__m == 3
+            else self.__sample_w_rej(shape=shape)
+        )
+
+        v = (
+            torch.distributions.Normal(0, 1)
+            .sample(shape + torch.Size(self.loc.shape))
+            .to(self.device)
+            .transpose(0, -1)[1:]
+        ).transpose(0, -1)
+        v = v / v.norm(dim=-1, keepdim=True)
+
+        w_ = torch.sqrt(torch.clamp(1 - (w**2), 1e-10))
+        x = torch.cat((w, w_ * v), -1)
+        z = self.__householder_rotation(x)
+
+        return z.type(self.dtype)
+
+    def __sample_w3(self, shape):
+        shape = shape + torch.Size(self.scale.shape)
+        u = torch.distributions.Uniform(0, 1).sample(shape).to(self.device)
+        self.__w = (
+            1
+            + torch.stack(
+                [torch.log(u), torch.log(1 - u) - 2 * self.scale], dim=0
+            ).logsumexp(0)
+            / self.scale
+        )
+        return self.__w
+
+    def __sample_w_rej(self, shape):
+        c = torch.sqrt((4 * (self.scale**2)) + (self.__m - 1) ** 2)
+        b_true = (-2 * self.scale + c) / (self.__m - 1)
+
+        # using Taylor approximation with a smooth swift from 10 < scale < 11
+        # to avoid numerical errors for large scale
+        b_app = (self.__m - 1) / (4 * self.scale)
+        s = torch.min(
+            torch.max(
+                torch.tensor([0.0], dtype=self.dtype, device=self.device),
+                self.scale - 10,
+            ),
+            torch.tensor([1.0], dtype=self.dtype, device=self.device),
+        )
+        b = b_app * s + b_true * (1 - s)
+
+        a = (self.__m - 1 + 2 * self.scale + c) / 4
+        d = (4 * a * b) / (1 + b) - (self.__m - 1) * math.log(self.__m - 1)
+
+        self.__b, (self.__e, self.__w) = b, self.__while_loop(b, a, d, shape, k=self.k)
+        return self.__w
+
+    @staticmethod
+    def first_nonzero(x, dim, invalid_val=-1):
+        mask = x > 0
+        return torch.where(
+            mask.any(dim=dim),
+            mask.float().argmax(dim=1).squeeze(),
+            torch.tensor(invalid_val, device=x.device),
+        )
+
+    def __while_loop(self, b, a, d, shape, k=20, eps=1e-20):
+        #  matrix while loop: samples a matrix of [A, k] samples, to avoid looping all together
+        b, a, d = (
+            e.repeat(*shape, *([1] * len(self.scale.shape))).reshape(-1, 1)
+            for e in (b, a, d)
+        )
+        w, e, bool_mask = (
+            torch.zeros_like(b).to(self.device),
+            torch.zeros_like(b).to(self.device),
+            (torch.ones_like(b) == 1).to(self.device),
+        )
+
+        sample_shape = torch.Size([b.shape[0], k])
+        shape = shape + torch.Size(self.scale.shape)
+
+        while bool_mask.sum() != 0:
+            con1 = torch.tensor((self.__m - 1) / 2, dtype=torch.float64)
+            con2 = torch.tensor((self.__m - 1) / 2, dtype=torch.float64)
+            e_ = (
+                torch.distributions.Beta(con1, con2)
+                .sample(sample_shape)
+                .to(self.device)
+                .type(self.dtype)
+            )
+
+            u = (
+                torch.distributions.Uniform(0 + eps, 1 - eps)
+                .sample(sample_shape)
+                .to(self.device)
+                .type(self.dtype)
+            )
+
+            w_ = (1 - (1 + b) * e_) / (1 - (1 - b) * e_)
+            t = (2 * a * b) / (1 - (1 - b) * e_)
+
+            accept = ((self.__m - 1.0) * t.log() - t + d) > torch.log(u)
+            accept_idx = self.first_nonzero(accept, dim=-1, invalid_val=-1).unsqueeze(1)
+            accept_idx_clamped = accept_idx.clamp(0)
+            # we use .abs(), in order to not get -1 index issues, the -1 is still used afterwards
+            w_ = w_.gather(1, accept_idx_clamped.view(-1, 1))
+            e_ = e_.gather(1, accept_idx_clamped.view(-1, 1))
+
+            reject = accept_idx < 0
+            accept = ~reject if torch.__version__ >= "1.2.0" else 1 - reject
+
+            w[bool_mask * accept] = w_[bool_mask * accept]
+            e[bool_mask * accept] = e_[bool_mask * accept]
+
+            bool_mask[bool_mask * accept] = reject[bool_mask * accept]
+
+        return e.reshape(shape), w.reshape(shape)
+
+    def __householder_rotation(self, x):
+        u = self.__e1 - self.loc
+        u = u / (u.norm(dim=-1, keepdim=True) + 1e-5)
+        return x - 2 * (x * u).sum(-1, keepdim=True) * u
+
+    def entropy(self):
+        # option 1:
+        output = (
+            -self.scale
+            * ive(self.__m / 2, self.scale)
+            / ive((self.__m / 2) - 1, self.scale)
+        )
+        # option 2:
+        # output = - self.scale * ive_fraction_approx(torch.tensor(self.__m / 2), self.scale)
+        # option 3:
+        # output = - self.scale * ive_fraction_approx2(torch.tensor(self.__m / 2), self.scale)
+
+        return output.view(*(output.shape[:-1])) + self._log_normalization()
+
+    def log_prob(self, x):
+        return self._log_unnormalized_prob(x) - self._log_normalization()
+
+    def _log_unnormalized_prob(self, x):
+        output = self.scale * (self.loc * x).sum(-1, keepdim=True)
+
+        return output.view(*(output.shape[:-1]))
+
+    def _log_normalization(self):
+        output = -(
+            (self.__m / 2 - 1) * torch.log(self.scale)
+            - (self.__m / 2) * math.log(2 * math.pi)
+            - (self.scale + torch.log(ive(self.__m / 2 - 1, self.scale)))
+        )
+
+        return output.view(*(output.shape[:-1]))
+
+
+@register_kl(VonMisesFisher, HypersphericalUniform)
+def _kl_vmf_uniform(vmf, hyu):
+    return -vmf.entropy() + hyu.entropy()
diff --git a/neurometry/estimators/geometry/models/hyperspherical/ops/__init__.py b/neurometry/estimators/geometry/models/hyperspherical/ops/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/neurometry/estimators/geometry/models/hyperspherical/ops/ive.py b/neurometry/estimators/geometry/models/hyperspherical/ops/ive.py
new file mode 100644
index 0000000..62ce49b
--- /dev/null
+++ b/neurometry/estimators/geometry/models/hyperspherical/ops/ive.py
@@ -0,0 +1,76 @@
+from numbers import Number
+
+import numpy as np
+import scipy.special
+import torch
+
+
+class IveFunction(torch.autograd.Function):
+    @staticmethod
+    def forward(self, v, z):
+        assert isinstance(v, Number), "v must be a scalar"
+
+        self.save_for_backward(z)
+        self.v = v
+        z_cpu = z.data.cpu().numpy()
+
+        if np.isclose(v, 0):
+            output = scipy.special.i0e(z_cpu, dtype=z_cpu.dtype)
+        elif np.isclose(v, 1):
+            output = scipy.special.i1e(z_cpu, dtype=z_cpu.dtype)
+        else:  #  v > 0
+            output = scipy.special.ive(v, z_cpu, dtype=z_cpu.dtype)
+        #         else:
+        #             print(v, type(v), np.isclose(v, 0))
+        #             raise RuntimeError('v must be >= 0, it is {}'.format(v))
+
+        return torch.Tensor(output).to(z.device)
+
+    @staticmethod
+    def backward(self, grad_output):
+        z = self.saved_tensors[-1]
+        return (
+            None,
+            grad_output * (ive(self.v - 1, z) - ive(self.v, z) * (self.v + z) / z),
+        )
+
+
+class Ive(torch.nn.Module):
+    def __init__(self, v):
+        super().__init__()
+        self.v = v
+
+    def forward(self, z):
+        return ive(self.v, z)
+
+
+ive = IveFunction.apply
+
+
+##########
+# The below provided approximations were provided in the
+# respective source papers, to improve the stability of
+# the Bessel fractions.
+# I_(v/2)(k) / I_(v/2 - 1)(k)
+
+
+# source: https://arxiv.org/pdf/1606.02008.pdf
+def ive_fraction_approx(v, z):
+    # I_(v/2)(k) / I_(v/2 - 1)(k) >= z / (v-1 + ((v+1)^2 + z^2)^0.5
+    return z / (v - 1 + torch.pow(torch.pow(v + 1, 2) + torch.pow(z, 2), 0.5))
+
+
+# source: https://arxiv.org/pdf/1902.02603.pdf
+def ive_fraction_approx2(v, z, eps=1e-20):
+    def delta_a(a):
+        lamb = v + (a - 1.0) / 2.0
+        return (v - 0.5) + lamb / (
+            2 * torch.sqrt((torch.pow(lamb, 2) + torch.pow(z, 2)).clamp(eps))
+        )
+
+    delta_0 = delta_a(0.0)
+    delta_2 = delta_a(2.0)
+    B_0 = z / (delta_0 + torch.sqrt(torch.pow(delta_0, 2) + torch.pow(z, 2)).clamp(eps))
+    B_2 = z / (delta_2 + torch.sqrt(torch.pow(delta_2, 2) + torch.pow(z, 2)).clamp(eps))
+
+    return (B_0 + B_2) / 2.0
diff --git a/neurometry/estimators/geometry/models/losses.py b/neurometry/estimators/geometry/models/losses.py
new file mode 100644
index 0000000..21fb2a8
--- /dev/null
+++ b/neurometry/estimators/geometry/models/losses.py
@@ -0,0 +1,176 @@
+"""Losses."""
+
+import torch
+
+from neurometry.estimators.curvature.hyperspherical.distributions import (
+    hyperspherical_uniform,
+    von_mises_fisher,
+)
+
+
+def elbo(x, x_mu, posterior_params, z, labels, config):
+    """Compute the ELBO for the VAE loss.
+
+    The VAE elbo loss is defined as:
+    = reconstruction loss + Kl divergence
+    over all elements and batch
+
+    Notes
+    -----
+    see Appendix B from VAE paper:
+    Kingma and Welling. Auto-Encoding Variational Bayes. ICLR, 2014
+    https://arxiv.org/abs/1312.6114
+    0.5 * sum(1 + log(sigma^2) - mu^2 - sigma^2)
+
+    Parameters
+    ----------
+    x : array-like, shape=[batch_size, data_dim]
+        Input data.
+    gen_likelihood_params : tuple
+        Learned distributional parameters of generative model.
+        (e.g., (x_mu,x_logvar) for Gaussian).
+    posterior_params : tuple
+        Learned distributional parameters of approximate posterior.
+        (e.g., (z_mu,z_logvar) for Gaussian).
+    config : module
+        Module specifying various model hyperparameters
+
+    Returns
+    -------
+    _ : array-like, shape=[batch_size,]
+        VAE elbo loss function on each batch element.
+    """
+
+    if config.posterior_type == "gaussian":
+        z_mu, z_logvar = posterior_params
+        z_var = torch.exp(z_logvar)
+        kld = -0.5 * torch.sum(1 + z_logvar - z_mu.pow(2) - z_var)
+
+    if config.posterior_type == "hyperspherical":
+        z_mu, z_kappa = posterior_params
+        q_z = von_mises_fisher.VonMisesFisher(z_mu, z_kappa)
+        p_z = hyperspherical_uniform.HypersphericalUniform(
+            config.latent_dim - 1, device=config.device
+        )
+        kld = torch.distributions.kl.kl_divergence(q_z, p_z).mean()
+
+    if config.posterior_type == "toroidal":
+        z_theta_mu, z_theta_kappa, z_phi_mu, z_phi_kappa = posterior_params
+        q_z_theta = von_mises_fisher.VonMisesFisher(z_theta_mu, z_theta_kappa)
+        q_z_phi = von_mises_fisher.VonMisesFisher(z_phi_mu, z_phi_kappa)
+        p_z = hyperspherical_uniform.HypersphericalUniform(
+            config.latent_dim - 1, device=config.device
+        )
+        kld_theta = torch.distributions.kl.kl_divergence(q_z_theta, p_z).mean()
+        kld_phi = torch.distributions.kl.kl_divergence(q_z_phi, p_z).mean()
+        kld = kld_theta + kld_phi
+
+    if config.gen_likelihood_type == "gaussian":
+        recon_loss = torch.mean((x - x_mu).pow(2))
+    else:
+        raise NotImplementedError
+
+    if config.dataset_name == "s1_synthetic":
+        recon_loss = recon_loss / (config.radius**2)
+
+    latent_loss = latent_regularization_loss(labels, z, config)
+    moving_loss = moving_forward_loss(z, config)
+
+    elbo_loss = (
+        config.alpha * recon_loss
+        + config.beta * kld
+        + config.gamma * latent_loss
+        + config.gamma_moving * moving_loss
+    )
+    return elbo_loss, recon_loss, kld, latent_loss, moving_loss
+
+
+def latent_regularization_loss(labels, z, config):
+    """Compute squared geodesic distance between outside and inside's variables.
+
+    For example, this computes the squared difference in angles between the lab's
+    angle and the latent angle.
+
+    Parameters
+    ----------
+    labels : array-like, shape=[batch_size, latent_dim]
+        Task variables recorded.
+    z : array-like, shape=[batch_size, latent_dim]
+        Latent variables on the template manifold.
+    config : object-like
+        Configuration of the experiment in wandb format.
+
+    Returns
+    -------
+    _ : array-like, shape=[batch_size, 1]
+        Squared geodesic distance, i.e. the loss.
+    """
+    if config.dataset_name == "s1_synthetic":
+        latent_angles = (torch.atan2(z[:, 1], z[:, 0]) + 2 * torch.pi) % (2 * torch.pi)
+        angle_loss = torch.mean(1 - torch.cos(latent_angles - labels))
+        latent_loss = angle_loss
+    elif config.dataset_name in ("experimental", "three_place_cells_synthetic"):
+        labels = labels * (torch.pi / 180)
+        latent_angles = (torch.atan2(z[:, 1], z[:, 0]) + 2 * torch.pi) % (2 * torch.pi)
+        angle_loss = torch.mean(1 - torch.cos(latent_angles - labels))
+        latent_loss = angle_loss
+    elif config.dataset_name == "s2_synthetic":
+        latent_thetas = torch.arccos(z[:, 2])
+        latent_phis = (torch.atan2(z[:, 1], z[:, 0]) + 2 * torch.pi) % (2 * torch.pi)
+        thetas_loss = torch.mean(1 - torch.cos(latent_thetas - labels[:, 0]))
+        phis_loss = torch.mean(
+            torch.sin(latent_thetas)
+            * torch.sin(labels[:, 0])
+            * (1 - torch.cos(latent_phis - labels[:, 1]))
+        )
+        latent_loss = thetas_loss + phis_loss
+    elif config.dataset_name == "t2_synthetic":
+        latent_thetas = (
+            torch.atan2(z[:, 2], 2 - torch.sqrt(z[:, 0] ** 2 + z[:, 1] ** 2))
+            + 2 * torch.pi
+        ) % (2 * torch.pi)
+        latent_phis = (torch.atan2(z[:, 1], z[:, 0]) + 2 * torch.pi) % (2 * torch.pi)
+        thetas_loss = torch.mean(1 - torch.cos(latent_thetas - labels[:, 0]))
+        phis_loss = torch.mean(1 - torch.cos(latent_phis - labels[:, 1]))
+        latent_loss = thetas_loss + phis_loss
+    elif config.dataset_name == "grid_cells":
+        return 0
+
+    return latent_loss**2
+
+
+def moving_forward_loss(z, config):
+    """Compute difference between two consecutive z's.
+
+    This loss will enforce that the latent variable (the angles) only increase
+    when the rat moves forward.
+
+    In order to enforce increasing values of z's, the loss is not squared.
+    minimizing -(z_t+1 - z_t) will force it to be negative, i.e. z_t+1 > z_t.
+
+    We remove the situation where the rat crosses the angles 360 --> 0.
+    Note that atol=0.089 radians corresponds to 5 degrees, which is the max degree
+    difference observed in the rat's labelled lab angles.
+
+    Parameters
+    ----------
+    """
+    if config.dataset_name != "experimental":
+        # print(
+        #     "WARNING: Moving forward loss only implemented for experimental data
+        #     --> Skipped."
+        # )
+        return torch.zeros(1).to(config.device)
+    if len(z) == 1:
+        return torch.zeros(1).to(config.device)
+    latent_angles = (torch.atan2(z[:, 1], z[:, 0]) + 2 * torch.pi) % (2 * torch.pi)
+    diff = latent_angles[1:] - latent_angles[:-1]
+    # only keep angles where the rat is not crossing 360 --> 0
+    mask = ~torch.isclose(
+        2 * torch.pi - latent_angles[:-1], torch.tensor(0.0), atol=0.089
+    )
+    loss = -diff[mask]
+    if len(loss) == 0:
+        return torch.zeros(1).to(config.device)
+    return torch.mean(loss)
+
diff --git a/neurometry/estimators/geometry/models/spherical_vae.py b/neurometry/estimators/geometry/models/spherical_vae.py
new file mode 100644
index 0000000..cc79c39
--- /dev/null
+++ b/neurometry/estimators/geometry/models/spherical_vae.py
@@ -0,0 +1,263 @@
+"""G-manifold deep learning.
+
+This file gathers deep learning models related to G-manifold learning.
+"""
+
+import torch
+from torch.nn import functional as F
+
+from neurometry.estimators.geometry.models import train_config as train_config
+from neurometry.estimators.geometry.models.hyperspherical.distributions import (
+    hyperspherical_uniform,
+    von_mises_fisher,
+)
+
+
+class SphericalVAE(torch.nn.Module):
+    """VAE with Linear (fully connected) layers.
+
+    Parameters
+    ----------
+    extrinsic_dim : int
+        Extrinsic dimension of neural data.
+        This is the dimension of a hyperplane in which neural activity lies within neural state space.
+    latent_dim : int
+        Dimension of the latent space. This is the dimension of the minimal euclidean embedding of the task-relevant variables.
+    """
+
+    def __init__(
+        self,
+        extrinsic_dim,
+        latent_dim,
+        sftbeta=4.5,
+        encoder_width=400,
+        encoder_depth=2,
+        decoder_width=400,
+        decoder_depth=2,
+        drop_out_p=0.0,
+    ):
+        super().__init__()
+        self.extrinsic_dim = extrinsic_dim
+        self.sftbeta = sftbeta
+        self.latent_dim = latent_dim
+        self.drop_out_p = drop_out_p
+
+        decoder_width = encoder_width
+        decoder_depth = encoder_depth
+
+        self.encoder_fc = torch.nn.Linear(self.extrinsic_dim, encoder_width)
+        self.encoder_linears = torch.nn.ModuleList(
+            [
+                torch.nn.Linear(encoder_width, encoder_width)
+                for _ in range(encoder_depth)
+            ]
+        )
+
+        self.fc_z_mu = torch.nn.Linear(encoder_width, self.latent_dim)
+        self.fc_z_logvar = torch.nn.Linear(encoder_width, 1)  # kappa
+
+        self.decoder_fc = torch.nn.Linear(self.latent_dim, decoder_width)
+        self.decoder_linears = torch.nn.ModuleList(
+            [
+                torch.nn.Linear(decoder_width, decoder_width)
+                for _ in range(decoder_depth)
+            ]
+        )
+
+        self.fc_x_mu = torch.nn.Linear(decoder_width, self.extrinsic_dim)
+
+        self.drop_out = torch.nn.Dropout(p=self.drop_out_p)
+
+    def encode(self, x):
+        """Encode input into mean and log-variance.
+
+        The parameters mean (mu) and variance (computed
+        from logvar) defines a multivariate Gaussian
+        that represents the approximate posterior of the
+        latent variable z given the input x.
+
+        Parameters
+        ----------
+        x : array-like, shape=[batch_size, extrinsic_dim]
+            Input data.
+
+        Returns
+        -------
+        mu : array-like, shape=[batch_size, latent_dim]
+            Mean of multivariate Gaussian in latent space.
+        logvar : array-like, shape=[batch_size, latent_dim]
+            Vector representing the diagonal covariance of the
+            multivariate Gaussian in latent space.
+        """
+        h = F.softplus(self.encoder_fc(x.double()), beta=self.sftbeta)
+
+        for _i_layer, layer in enumerate(self.encoder_linears):
+            # h = self.drop_out(h)
+            h = layer(h)
+            h = F.softplus(h, beta=self.sftbeta)
+
+        z_mu = self.fc_z_mu(h)
+        z_kappa = F.softplus(self.fc_z_logvar(h)) + 1
+
+        return z_mu, z_kappa
+
+    def reparameterize(self, posterior_params):
+        """
+        Apply reparameterization trick. We 'externalize' the
+        randomness in z by re-parameterizing the variable as
+        a deterministic and differentiable function of x,
+        the encoder weights, and a new random variable eps.
+
+        Parameters
+        ----------
+        posterior_params : tuple
+            Distributional parameters of approximate posterior. ((e.g.), (z_mu,z_logvar) for Gaussian.
+
+        Returns
+        -------
+
+        z: array-like, shape = [batch_size, latent_dim]
+            Re-parameterized latent variable.
+        """
+
+        z_mu, z_kappa = posterior_params
+        q_z = von_mises_fisher.VonMisesFisher(z_mu, z_kappa)
+
+        return q_z.rsample()
+
+    def decode(self, z):
+        """Decode latent variable z into data.
+
+        Parameters
+        ----------
+        z : array-like, shape=[batch_size, latent_dim]
+            Input to the decoder.
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size, extrinsic_dim]
+            Reconstructed data corresponding to z.
+        """
+
+        h = F.softplus(self.decoder_fc(z), beta=self.sftbeta)
+
+        for _i_layer, layer in enumerate(self.decoder_linears):
+            # h = self.drop_out(h)
+            h = layer(h)
+            h = F.softplus(h, beta=self.sftbeta)
+
+        return self.fc_x_mu(h)
+
+    def forward(self, x):
+        """Run VAE: Encode, sample and decode.
+
+        Parameters
+        ----------
+        x : array-like, shape=[batch_size, extrinsic_dim]
+            Input data.
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size, extrinsic_dim]
+            Reconstructed data corresponding to z.
+        mu : array-like, shape=[batch_size, latent_dim]
+            Mean of multivariate Gaussian in latent space.
+        logvar : array-like, shape=[batch_size, latent_dim]
+            Vector representing the diagonal covariance of the
+            multivariate Gaussian in latent space.
+        """
+
+        posterior_params = self.encode(x)
+        z = self.reparameterize(posterior_params)
+        x_mu = self.decode(z)
+        return z, x_mu, posterior_params
+
+    def _elbo(self, x, x_mu, posterior_params):
+        """Compute the ELBO for the VAE loss.
+
+        The VAE elbo loss is defined as:
+        = reconstruction loss + Kl divergence
+        over all elements and batch
+
+        Notes
+        -----
+        see Appendix B from VAE paper:
+        Kingma and Welling. Auto-Encoding Variational Bayes. ICLR, 2014
+        https://arxiv.org/abs/1312.6114
+        0.5 * sum(1 + log(sigma^2) - mu^2 - sigma^2)
+
+        Parameters
+        ----------
+        x : array-like, shape=[batch_size, data_dim]
+            Input data.
+        gen_likelihood_params : tuple
+            Learned distributional parameters of generative model.
+            (e.g., (x_mu,x_logvar) for Gaussian).
+        posterior_params : tuple
+            Learned distributional parameters of approximate posterior.
+            (e.g., (z_mu,z_logvar) for Gaussian).
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size,]
+            VAE elbo loss function on each batch element.
+        """
+
+        z_mu, z_kappa = posterior_params
+        q_z = von_mises_fisher.VonMisesFisher(z_mu, z_kappa)
+        p_z = hyperspherical_uniform.HypersphericalUniform(
+            self.latent_dim - 1, device=train_config.device
+        )
+        kld = torch.distributions.kl.kl_divergence(q_z, p_z).mean()
+
+        recon_loss = torch.mean((x - x_mu).pow(2))
+
+
+        return train_config.recon_weight * recon_loss + train_config.kld_weight * kld
+
+    def _latent_regularization_loss(self, labels, z):
+        """Compute squared geodesic distance between outside and inside's variables.
+
+        For example, this computes the squared difference in angles between the lab's
+        angle and the latent angle.
+
+        Parameters
+        ----------
+        labels : array-like, shape=[batch_size, latent_dim]
+            Task variables recorded.
+        z : array-like, shape=[batch_size, latent_dim]
+            Latent variables on the template manifold.
+        config : object-like
+            Configuration of the experiment in wandb format.
+
+        Returns
+        -------
+        _ : array-like, shape=[batch_size, 1]
+            Squared geodesic distance, i.e. the loss.
+        """
+        if self.latent_dim == 2:
+            latent_angles = (torch.atan2(z[:, 1], z[:, 0]) + 2 * torch.pi) % (
+                2 * torch.pi
+            )
+            angle_loss = torch.mean(1 - torch.cos(latent_angles - labels))
+            latent_loss = angle_loss
+        elif self.latent_dim == 3:
+            latent_thetas = torch.arccos(z[:, 2])
+            latent_phis = (torch.atan2(z[:, 1], z[:, 0]) + 2 * torch.pi) % (
+                2 * torch.pi
+            )
+            thetas_loss = torch.mean(1 - torch.cos(latent_thetas - labels[:, 0]))
+            phis_loss = torch.mean(
+                torch.sin(latent_thetas)
+                * torch.sin(labels[:, 0])
+                * (1 - torch.cos(latent_phis - labels[:, 1]))
+            )
+            latent_loss = thetas_loss + phis_loss
+
+        return latent_loss**2
+
+    def criterion(self, x, x_mu, posterior_params, labels, z):
+        elbo_loss = self._elbo(x, x_mu, posterior_params)
+        latent_loss = self._latent_regularization_loss(labels, z)
+
+        return elbo_loss + train_config.latent_weight * latent_loss
diff --git a/neurometry/estimators/geometry/toroidal_vae.py b/neurometry/estimators/geometry/models/toroidal_vae.py
similarity index 85%
rename from neurometry/estimators/geometry/toroidal_vae.py
rename to neurometry/estimators/geometry/models/toroidal_vae.py
index 191f78c..e3eb2b7 100644
--- a/neurometry/estimators/geometry/toroidal_vae.py
+++ b/neurometry/estimators/geometry/models/toroidal_vae.py
@@ -17,35 +17,29 @@ class ToroidalVAE(torch.nn.Module):
 
     Parameters
     ----------
-    data_dim : int
-        Dimension of input data.
-        Example: 40 for neural recordings of 40 units/clusters.
+    extrinsic_dim : int
+        Extrinsic dimension of neural data.
+        This is the dimension of a hyperplane in which neural activity lies within neural state space.
     latent_dim : int
-        Dimension of the latent space.
-        Example: 2.
+        Dimension of the latent space. This is the dimension of the minimal euclidean embedding of the task-relevant variables.
     """
 
     def __init__(
         self,
-        data_dim,
+        extrinsic_dim,
         latent_dim,
-        sftbeta,
-        encoder_width,
-        encoder_depth,
-        decoder_width,
-        decoder_depth,
-        posterior_type,
+        sftbeta=4.5,
+        encoder_width=400,
+        encoder_depth=2,
+        decoder_width=400,
+        decoder_depth=2,
     ):
         super().__init__()
-        self.data_dim = data_dim
+        self.extrinsic_dim = extrinsic_dim
         self.sftbeta = sftbeta
         self.latent_dim = latent_dim
-        self.posterior_type = posterior_type
 
-        # decoder_width = encoder_width
-        # decoder_depth = encoder_depth
-
-        self.encoder_fc = torch.nn.Linear(self.data_dim, encoder_width)
+        self.encoder_fc = torch.nn.Linear(self.extrinsic_dim, encoder_width)
         self.encoder_linears = torch.nn.ModuleList(
             [
                 torch.nn.Linear(encoder_width, encoder_width)
@@ -67,7 +61,7 @@ def __init__(
             ]
         )
 
-        self.fc_x_mu = torch.nn.Linear(decoder_width, self.data_dim)
+        self.fc_x_mu = torch.nn.Linear(decoder_width, self.extrinsic_dim)
 
     def encode(self, x):
         """Encode input into mean and log-variance.
@@ -79,7 +73,7 @@ def encode(self, x):
 
         Parameters
         ----------
-        x : array-like, shape=[batch_size, data_dim]
+        x : array-like, shape=[batch_size, extrinsic_dim]
             Input data.
 
         Returns
@@ -162,7 +156,7 @@ def decode(self, z):
 
         Returns
         -------
-        _ : array-like, shape=[batch_size, data_dim]
+        _ : array-like, shape=[batch_size, extrinsic_dim]
             Reconstructed data corresponding to z.
         """
 
@@ -178,12 +172,12 @@ def forward(self, x):
 
         Parameters
         ----------
-        x : array-like, shape=[batch_size, data_dim]
+        x : array-like, shape=[batch_size, extrinsic_dim]
             Input data.
 
         Returns
         -------
-        _ : array-like, shape=[batch_size, data_dim]
+        _ : array-like, shape=[batch_size, extrinsic_dim]
             Reconstructed data corresponding to z.
         mu : array-like, shape=[batch_size, latent_dim]
             Mean of multivariate Gaussian in latent space.
diff --git a/neurometry/estimators/geometry/models/train.py b/neurometry/estimators/geometry/models/train.py
new file mode 100644
index 0000000..36db748
--- /dev/null
+++ b/neurometry/estimators/geometry/models/train.py
@@ -0,0 +1,107 @@
+"""Training and testing functions for VAE model."""
+
+import copy
+
+# import wandb
+import numpy as np
+
+
+def train_test(model, train_loader, test_loader, optimizer, scheduler, config):
+    train_losses = []
+    test_losses = []
+    lowest_test_loss = np.inf
+    for epoch in range(1, config.num_epochs + 1):
+        train_loss = run_one_epoch(
+            epoch=epoch,
+            model=model,
+            data_loader=train_loader,
+            device=config.device,
+            optimizer=optimizer,
+            train=True,
+        )
+        train_losses.append(train_loss)
+
+        test_loss = run_one_epoch(
+            epoch=epoch,
+            model=model,
+            data_loader=test_loader,
+            device=config.device,
+            optimizer=optimizer,
+            train=False,
+        )
+
+        if scheduler is not None:
+            scheduler.step(test_loss)
+
+        test_losses.append(test_loss)
+
+        if epoch == 1 or test_loss < lowest_test_loss:
+            lowest_test_loss = test_loss
+            best_model = copy.deepcopy(model)
+
+    return train_losses, test_losses, best_model
+
+
+def run_one_epoch(epoch, model, data_loader, device, optimizer, train=True):
+    """Run one epoch on the train or test set.
+
+    Parameters
+    ----------
+    epoch : int
+        Index of current epoch.
+    train : bool, optional
+        Whether this is a training epoch (default is True).
+
+    Returns
+    -------
+    loss : float
+        Loss on epoch.
+    """
+    if train:
+        model.train()
+        mode = "Train"
+    else:
+        model.eval()
+        mode = "Test"
+
+    epoch_loss = 0
+
+    for batch_idx, batch_data in enumerate(data_loader):
+        x_batch, labels = batch_data
+        x_batch = x_batch.to(device)
+        labels = labels.float().to(device)
+
+        if train:
+            optimizer.zero_grad()
+
+        # Forward pass
+        z_batch, x_mu_batch, posterior_params = model(x_batch)
+
+        # Compute loss
+        loss = model.criterion(x_batch, x_mu_batch, posterior_params, labels, z_batch)
+        epoch_loss += loss.item()
+
+        # Backpropagation and optimizer step only during training
+        if train:
+            loss.backward()
+            optimizer.step()
+
+        # Logging during training
+        if train and batch_idx % 20 == 0:
+            print(
+                f"{mode} Epoch: {epoch} [{batch_idx * len(x_batch)}/{len(data_loader.dataset)} "
+                f"({100.0 * batch_idx / len(data_loader):.0f}%)]\tLoss: {loss.item() / len(x_batch):.6f}"
+            )
+
+    epoch_loss /= len(data_loader.dataset)
+
+    # # Logging with wandb
+    # wandb.log(
+    #     {
+    #         f"{mode.lower()}_loss": epoch_loss,
+    #     },
+    #     step=epoch,
+    # )
+
+    print(f"====> {mode} Epoch: {epoch} Average loss: {epoch_loss:.4f}")
+    return epoch_loss
diff --git a/neurometry/estimators/geometry/models/train_config.py b/neurometry/estimators/geometry/models/train_config.py
new file mode 100644
index 0000000..4bb241a
--- /dev/null
+++ b/neurometry/estimators/geometry/models/train_config.py
@@ -0,0 +1,13 @@
+import torch
+
+# hardware
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# training
+num_epochs = 500
+batch_size = 64
+lr = 1e-3
+
+recon_weight = 1.0  # weight for the reconstruction loss
+kld_weight = 0.03  # 0.03  # weight for KL loss
+latent_weight = 10  # weight for latent regularization loss
diff --git a/neurometry/estimators/geometry/models/utils.py b/neurometry/estimators/geometry/models/utils.py
new file mode 100644
index 0000000..ef0f6f3
--- /dev/null
+++ b/neurometry/estimators/geometry/models/utils.py
@@ -0,0 +1,248 @@
+"""Utils to import data from matlab."""
+
+import mat73
+import numpy as np
+import scipy.io
+import torch
+from scipy.signal import savgol_filter
+
+from neurometry.estimators.curvature.datasets.experimental import load_neural_activity
+from neurometry.estimators.curvature.datasets.synthetic import (
+    load_place_cells,
+    load_points,
+    load_s1_synthetic,
+    load_s2_synthetic,
+    load_t2_synthetic,
+)
+
+
+def load(config):
+    """Load dataset according to configuration in config.
+
+    Parameters
+    ----------
+    config
+
+    Returns
+    -------
+    dataset_torch : torch.Tensor
+        Dataset (without labels) as a torch tensor.
+        Each row represents one data point.
+    labels : pd.DataFrame
+        Dataframe of labels corresponding to dataset_torch
+    train_loader : torch.DataLoader
+        Loader that yields minibatches (data and labels) from the
+        train dataset.
+    test_loader : torch.DataLoader
+        Loader that yields minibatches (data and labels) from the
+        test dataset.
+    """
+    if config.dataset_name == "experimental":
+        dataset, labels = load_neural_activity(
+            expt_id=config.expt_id, timestep_microsec=config.timestep_microsec
+        )
+        dataset = dataset[labels["velocities"] > 5]
+        labels = labels[labels["velocities"] > 5]
+        dataset = np.log(dataset.astype(np.float32) + 1)
+
+        if config.smooth is True:
+            dataset_smooth = np.zeros_like(dataset)
+            for _ in range(dataset.shape[1]):
+                dataset_smooth[:, _] = savgol_filter(
+                    dataset[:, _], window_length=40, polyorder=2
+                )
+            dataset = dataset_smooth
+        dataset = (dataset - np.min(dataset)) / (np.max(dataset) - np.min(dataset))
+
+        gain_counts = labels["gains"].value_counts()
+        gain_1 = 1
+        one_gain = labels["gains"].value_counts().is_unique
+        if one_gain:
+            print(f"The dataset contains only one gain value: {gain_counts.index[0]}")
+            gain = gain_1
+        else:
+            print(
+                "The dataset transitions between two gains:"
+                f" {gain_counts.index[0]:4f} and {gain_counts.index[1]:4f}."
+            )
+            if config.select_gain_1:
+                gain = gain_1
+                print(f"We select gain 1: gain = {gain_1}.")
+            else:
+                other_gain = gain_counts.index[0]
+                if other_gain == gain_1:
+                    other_gain = gain_counts.index[1]
+                gain = other_gain
+                print(f"We select the other gain: gain = {other_gain:4f}.")
+        config.update({"gain": gain})
+        dataset = dataset[labels["gains"] == gain]
+        labels = labels[labels["gains"] == gain]
+
+    elif config.dataset_name == "synthetic":
+        dataset, labels = load_place_cells()
+        dataset = np.log(dataset.astype(np.float32) + 1)
+        dataset = (dataset - np.min(dataset)) / (np.max(dataset) - np.min(dataset))
+    elif config.dataset_name == "points":
+        dataset, labels = load_points()
+        dataset = dataset.astype(np.float32)
+    elif config.dataset_name == "s1_synthetic":
+        dataset, labels = load_s1_synthetic(
+            synthetic_rotation=config.synthetic_rotation,
+            n_times=config.n_times,
+            radius=config.radius,
+            n_wiggles=config.n_wiggles,
+            geodesic_distortion_amp=config.geodesic_distortion_amp,
+            embedding_dim=config.embedding_dim,
+            noise_var=config.noise_var,
+            geodesic_distortion_func=config.geodesic_distortion_func,
+        )
+    elif config.dataset_name == "s2_synthetic":
+        dataset, labels = load_s2_synthetic(
+            synthetic_rotation=config.synthetic_rotation,
+            n_times=config.n_times,
+            radius=config.radius,
+            geodesic_distortion_amp=config.geodesic_distortion_amp,
+            embedding_dim=config.embedding_dim,
+            noise_var=config.noise_var,
+        )
+    elif config.dataset_name == "t2_synthetic":
+        dataset, labels = load_t2_synthetic(
+            synthetic_rotation=config.synthetic_rotation,
+            n_times=config.n_times,
+            major_radius=config.major_radius,
+            minor_radius=config.minor_radius,
+            geodesic_distortion_amp=config.geodesic_distortion_amp,
+            embedding_dim=config.embedding_dim,
+            noise_var=config.noise_var,
+        )
+    print(f"Dataset shape: {dataset.shape}.")
+    if isinstance(dataset, np.ndarray):
+        dataset_torch = torch.from_numpy(dataset)
+    else:
+        dataset_torch = dataset
+    # dataset_torch = dataset_torch - torch.mean(dataset_torch, dim=0)
+
+    train_num = int(round(0.7 * len(dataset)))  # 70% training
+    indices = np.arange(len(dataset))
+
+    train_indices = np.arange(train_num)
+    rng = np.random.default_rng(seed=0)
+    if config.batch_shuffle:
+        # Note: this breaks the temporal ordering.
+        train_indices = rng.choice(indices, train_num, replace=False)
+
+    test_indices = np.delete(indices, train_indices)
+    train_dataset = dataset[train_indices]
+    train_labels = labels.iloc[train_indices]
+
+    test_dataset = dataset[test_indices]
+    test_labels = labels.iloc[test_indices]
+
+    train_dataset = dataset[train_indices]
+    train_labels = labels.iloc[train_indices]
+    test_dataset = dataset[test_indices]
+    test_labels = labels.iloc[test_indices]
+
+    # The angles are positional angles in the lab frame
+    if config.dataset_name in (
+        "experimental",
+        "s1_synthetic",
+    ) or config.dataset_name in ("three_place_cells_synthetic"):
+        train = []
+        for data, label in zip(train_dataset, train_labels["angles"], strict=False):
+            train.append([data, float(label)])
+        test = []
+        for data, label in zip(test_dataset, test_labels["angles"], strict=False):
+            test.append([data, float(label)])
+    elif config.dataset_name in ("s2_synthetic", "t2_synthetic"):
+        train = []
+        for data, theta, phi in zip(
+            train_dataset, train_labels["thetas"], train_labels["phis"], strict=False
+        ):
+            train.append([data, torch.tensor([float(theta), float(phi)])])
+        test = []
+        for data, theta, phi in zip(
+            test_dataset, test_labels["thetas"], test_labels["phis"], strict=False
+        ):
+            test.append([data, torch.tensor([float(theta), float(phi)])])
+
+    train_loader = torch.utils.data.DataLoader(train, batch_size=config.batch_size)
+    test_loader = torch.utils.data.DataLoader(test, batch_size=config.batch_size)
+    return dataset_torch, labels, train_loader, test_loader
+
+
+def loadmat(filename):
+    """Improved loadmat (replacement for scipy.io.loadmat).
+
+    Ensures correct loading of python dictionaries from mat files.
+
+    Inspired by: https://stackoverflow.com/a/29126361/572908.
+
+    Parameters
+    ----------
+    filename : str
+        Name of the file containing matlab data.
+        Example: expt34.mat
+    """
+
+    def _has_struct(elem):
+        """Check if elem is an array & if its first item is a struct."""
+        return (
+            isinstance(elem, np.ndarray)
+            and (elem.size > 0)
+            and isinstance(elem[0], scipy.io.matlab.mio5_params.mat_struct)
+        )
+
+    def _check_keys(d):
+        """Check if entries in dictionary are mat-objects.
+
+        If they are mat-objects, then todict is called to change
+        them to nested dictionaries.
+        """
+        for key in d:
+            elem = d[key]
+            if isinstance(elem, scipy.io.matlab.mio5_params.mat_struct):
+                d[key] = _todict(elem)
+            elif _has_struct(elem):
+                d[key] = _tolist(elem)
+        return d
+
+    def _todict(matobj):
+        """Build nested dictionaries from mat-objects.
+
+        This is a recursive function.
+        """
+        d = {}
+        for strg in matobj._fieldnames:
+            elem = matobj.__dict__[strg]
+            if isinstance(elem, scipy.io.matlab.mio5_params.mat_struct):
+                d[strg] = _todict(elem)
+            elif _has_struct(elem):
+                d[strg] = _tolist(elem)
+            else:
+                d[strg] = elem
+        return d
+
+    def _tolist(ndarray):
+        """Build lists from cellarays.
+
+        This is a recursive function that constructs lists from
+        cellarrays (which are loaded as numpy ndarrays).
+
+        It is recursing into the elements if they contain matobjects.
+        """
+        elem_list = []
+        for sub_elem in ndarray:
+            if isinstance(sub_elem, scipy.io.matlab.mio5_params.mat_struct):
+                elem_list.append(_todict(sub_elem))
+            elif _has_struct(sub_elem):
+                elem_list.append(_tolist(sub_elem))
+            else:
+                elem_list.append(sub_elem)
+        return elem_list
+
+    try:
+        data = scipy.io.loadmat(filename, struct_as_record=False, squeeze_me=True)
+    except Exception:
+        data = mat73.loadmat(filename)
+    return _check_keys(data)
diff --git a/neurometry/estimators/geometry/spherical_vae.py b/neurometry/estimators/geometry/spherical_vae.py
deleted file mode 100644
index fd32f77..0000000
--- a/neurometry/estimators/geometry/spherical_vae.py
+++ /dev/null
@@ -1,172 +0,0 @@
-"""G-manifold deep learning.
-
-This file gathers deep learning models related to G-manifold learning.
-"""
-
-import torch
-from torch.nn import functional as F
-
-from neurometry.estimators.curvature.hyperspherical.distributions.von_mises_fisher import (
-    VonMisesFisher,
-)
-
-
-class SphericalVAE(torch.nn.Module):
-    """VAE with Linear (fully connected) layers.
-
-    Parameters
-    ----------
-    num_neurons : int
-        Number of neurons in the input data. This is the ambient dimension of the neural state space.
-        Example: 40 for neural recordings of 40 neurons.
-    latent_dim : int
-        Dimension of the latent space.
-        Example: 2.
-    """
-
-    def __init__(
-        self,
-        num_neurons,
-        latent_dim,
-        sftbeta,
-        encoder_width=400,
-        encoder_depth=2,
-        decoder_width=400,
-        decoder_depth=2,
-        drop_out_p=0.0,
-    ):
-        super().__init__()
-        self.num_neurons = num_neurons
-        self.sftbeta = sftbeta
-        self.latent_dim = latent_dim
-        self.drop_out_p = drop_out_p
-
-        decoder_width = encoder_width
-        decoder_depth = encoder_depth
-
-        self.encoder_fc = torch.nn.Linear(self.num_neurons, encoder_width)
-        self.encoder_linears = torch.nn.ModuleList(
-            [
-                torch.nn.Linear(encoder_width, encoder_width)
-                for _ in range(encoder_depth)
-            ]
-        )
-
-        self.fc_z_mu = torch.nn.Linear(encoder_width, self.latent_dim)
-        self.fc_z_logvar = torch.nn.Linear(encoder_width, 1)  # kappa
-
-        self.decoder_fc = torch.nn.Linear(self.latent_dim, decoder_width)
-        self.decoder_linears = torch.nn.ModuleList(
-            [
-                torch.nn.Linear(decoder_width, decoder_width)
-                for _ in range(decoder_depth)
-            ]
-        )
-
-        self.fc_x_mu = torch.nn.Linear(decoder_width, self.num_neurons)
-
-        self.drop_out = torch.nn.Dropout(p=self.drop_out_p)
-
-    def encode(self, x):
-        """Encode input into mean and log-variance.
-
-        The parameters mean (mu) and variance (computed
-        from logvar) defines a multivariate Gaussian
-        that represents the approximate posterior of the
-        latent variable z given the input x.
-
-        Parameters
-        ----------
-        x : array-like, shape=[batch_size, num_neurons]
-            Input data.
-
-        Returns
-        -------
-        mu : array-like, shape=[batch_size, latent_dim]
-            Mean of multivariate Gaussian in latent space.
-        logvar : array-like, shape=[batch_size, latent_dim]
-            Vector representing the diagonal covariance of the
-            multivariate Gaussian in latent space.
-        """
-        h = F.softplus(self.encoder_fc(x.double()), beta=self.sftbeta)
-
-        for _i_layer, layer in enumerate(self.encoder_linears):
-            # h = self.drop_out(h)
-            h = layer(h)
-            h = F.softplus(h, beta=self.sftbeta)
-
-        z_mu = self.fc_z_mu(h)
-        z_kappa = F.softplus(self.fc_z_logvar(h)) + 1
-
-        return z_mu, z_kappa
-
-    def reparameterize(self, posterior_params):
-        """
-        Apply reparameterization trick. We 'eternalize' the
-        randomness in z by re-parameterizing the variable as
-        a deterministic and differentiable function of x,
-        the encoder weights, and a new random variable eps.
-
-        Parameters
-        ----------
-        posterior_params : tuple
-            Distributional parameters of approximate posterior. ((e.g.), (z_mu,z_logvar) for Gaussian.
-
-        Returns
-        -------
-
-        z: array-like, shape = [batch_size, latent_dim]
-            Re-parameterized latent variable.
-        """
-
-        z_mu, z_kappa = posterior_params
-        q_z = VonMisesFisher(z_mu, z_kappa)
-
-        return q_z.rsample()
-
-    def decode(self, z):
-        """Decode latent variable z into data.
-
-        Parameters
-        ----------
-        z : array-like, shape=[batch_size, latent_dim]
-            Input to the decoder.
-
-        Returns
-        -------
-        _ : array-like, shape=[batch_size, num_neurons]
-            Reconstructed data corresponding to z.
-        """
-
-        h = F.softplus(self.decoder_fc(z), beta=self.sftbeta)
-
-        for _i_layer, layer in enumerate(self.decoder_linears):
-            # h = self.drop_out(h)
-            h = layer(h)
-            h = F.softplus(h, beta=self.sftbeta)
-
-        return self.fc_x_mu(h)
-
-    def forward(self, x):
-        """Run VAE: Encode, sample and decode.
-
-        Parameters
-        ----------
-        x : array-like, shape=[batch_size, num_neurons]
-            Input data.
-
-        Returns
-        -------
-        _ : array-like, shape=[batch_size, num_neurons]
-            Reconstructed data corresponding to z.
-        mu : array-like, shape=[batch_size, latent_dim]
-            Mean of multivariate Gaussian in latent space.
-        logvar : array-like, shape=[batch_size, latent_dim]
-            Vector representing the diagonal covariance of the
-            multivariate Gaussian in latent space.
-        """
-
-        posterior_params = self.encode(x)
-        z = self.reparameterize(posterior_params)
-        x_mu = self.decode(z)
-        return z, x_mu, posterior_params
diff --git a/neurometry/estimators/topology/topology_classifier.py b/neurometry/estimators/topology/topology_classifier.py
index a4657e4..cf01c2a 100644
--- a/neurometry/estimators/topology/topology_classifier.py
+++ b/neurometry/estimators/topology/topology_classifier.py
@@ -60,7 +60,7 @@ def _generate_ref_data(self, input_data):
                 points=circle_task_points,
                 encoding_dim=encoding_dim,
                 nonlinearity="sigmoid",
-                scales=5*gs.random.rand(encoding_dim),
+                scales=5 * gs.random.rand(encoding_dim),
                 fano_factor=self.fano_factor,
             )
             circle_point_clouds.append(circle_noisy_points)
@@ -72,7 +72,7 @@ def _generate_ref_data(self, input_data):
                 points=sphere_task_points,
                 encoding_dim=encoding_dim,
                 nonlinearity="sigmoid",
-                scales=5*gs.random.rand(encoding_dim),
+                scales=5 * gs.random.rand(encoding_dim),
                 fano_factor=self.fano_factor,
             )
             sphere_point_clouds.append(sphere_noisy_points)
@@ -84,7 +84,7 @@ def _generate_ref_data(self, input_data):
                 points=torus_task_points,
                 encoding_dim=encoding_dim,
                 nonlinearity="sigmoid",
-                scales=5*gs.random.rand(encoding_dim),
+                scales=5 * gs.random.rand(encoding_dim),
                 fano_factor=self.fano_factor,
             )
             torus_point_clouds.append(torus_noisy_points)
@@ -143,7 +143,9 @@ def fit(self, X, y=None):
         """
 
         if not isinstance(X, np.ndarray | torch.Tensor):
-            raise ValueError(f"Expected array-like input for X, but got {type(X).__name__}.")
+            raise ValueError(
+                f"Expected array-like input for X, but got {type(X).__name__}."
+            )
 
         ref_point_clouds, ref_labels = self._generate_ref_data(X)
         self.ref_labels = ref_labels
@@ -270,4 +272,3 @@ def compute_diagrams_shuffle(X, num_shuffles, seed=0, homology_dimensions=(0, 1)
     return compute_persistence_diagrams(
         [X, *shuffled_Xs], homology_dimensions=homology_dimensions
     )
-
diff --git a/tests/neurometry/estimators/topology/test_topology_classifier.py b/tests/neurometry/estimators/topology/test_topology_classifier.py
index 203b80a..c20fa11 100644
--- a/tests/neurometry/estimators/topology/test_topology_classifier.py
+++ b/tests/neurometry/estimators/topology/test_topology_classifier.py
@@ -112,4 +112,3 @@ def test_not_fitted_error(self):
         )
         with pytest.raises(NotFittedError):
             classifier.predict(self.circle_data)
-
diff --git a/tutorials/04_methods_estimate_manifold_immersion.ipynb b/tutorials/04_methods_estimate_manifold_immersion.ipynb
new file mode 100644
index 0000000..7f24cec
--- /dev/null
+++ b/tutorials/04_methods_estimate_manifold_immersion.ipynb
@@ -0,0 +1,9026 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Working directory:  /home/facosta/neurometry/neurometry\n",
+      "Directory added to path:  /home/facosta/neurometry\n",
+      "Directory added to path:  /home/facosta/neurometry/neurometry\n",
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n",
+      "The jupyter_black extension is already loaded. To reload it, use:\n",
+      "  %reload_ext jupyter_black\n"
+     ]
+    }
+   ],
+   "source": [
+    "import setup\n",
+    "\n",
+    "setup.main()\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "%load_ext jupyter_black\n",
+    "\n",
+    "import neurometry.datasets.synthetic as synthetic\n",
+    "import numpy as np\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "import os\n",
+    "\n",
+    "os.environ[\"GEOMSTATS_BACKEND\"] = \"pytorch\"\n",
+    "import geomstats.backend as gs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "task_points, intrinsic_coords = synthetic.hypersphere(1, 1000)\n",
+    "noisy_points, manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=task_points,\n",
+    "    encoding_dim=3,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.array([5, 3, 1]),\n",
+    ")\n",
+    "\n",
+    "X = manifold_points\n",
+    "labels = intrinsic_coords"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from neurometry.estimators.geometry.immersion_estimator import ImmersionEstimator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "extrinsic_dim = 3\n",
+    "topology = \"circle\"\n",
+    "device = \"cuda\"\n",
+    "\n",
+    "immersion_estimator = ImmersionEstimator(extrinsic_dim, topology, device=device)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train Epoch: 1 [0/800 (0%)]\tLoss: 202.562974\n",
+      "====> Train Epoch: 1 Average loss: 188.1801\n",
+      "====> Test Epoch: 1 Average loss: 165.0614\n",
+      "Train Epoch: 2 [0/800 (0%)]\tLoss: 134.526717\n",
+      "====> Train Epoch: 2 Average loss: 74.1690\n",
+      "====> Test Epoch: 2 Average loss: 70.4762\n",
+      "Train Epoch: 3 [0/800 (0%)]\tLoss: 56.325479\n",
+      "====> Train Epoch: 3 Average loss: 47.7297\n",
+      "====> Test Epoch: 3 Average loss: 57.2686\n",
+      "Train Epoch: 4 [0/800 (0%)]\tLoss: 42.957465\n",
+      "====> Train Epoch: 4 Average loss: 44.2286\n",
+      "====> Test Epoch: 4 Average loss: 54.5528\n",
+      "Train Epoch: 5 [0/800 (0%)]\tLoss: 42.971686\n",
+      "====> Train Epoch: 5 Average loss: 44.1926\n",
+      "====> Test Epoch: 5 Average loss: 53.0346\n",
+      "Train Epoch: 6 [0/800 (0%)]\tLoss: 45.222545\n",
+      "====> Train Epoch: 6 Average loss: 43.8985\n",
+      "====> Test Epoch: 6 Average loss: 53.7503\n",
+      "Train Epoch: 7 [0/800 (0%)]\tLoss: 42.859619\n",
+      "====> Train Epoch: 7 Average loss: 43.8415\n",
+      "====> Test Epoch: 7 Average loss: 55.3904\n",
+      "Train Epoch: 8 [0/800 (0%)]\tLoss: 43.091515\n",
+      "====> Train Epoch: 8 Average loss: 43.9621\n",
+      "====> Test Epoch: 8 Average loss: 57.2641\n",
+      "Train Epoch: 9 [0/800 (0%)]\tLoss: 44.604582\n",
+      "====> Train Epoch: 9 Average loss: 43.0592\n",
+      "====> Test Epoch: 9 Average loss: 56.2048\n",
+      "Train Epoch: 10 [0/800 (0%)]\tLoss: 43.722002\n",
+      "====> Train Epoch: 10 Average loss: 41.9819\n",
+      "====> Test Epoch: 10 Average loss: 47.0864\n",
+      "Train Epoch: 11 [0/800 (0%)]\tLoss: 40.527655\n",
+      "====> Train Epoch: 11 Average loss: 32.4589\n",
+      "====> Test Epoch: 11 Average loss: 24.6105\n",
+      "Train Epoch: 12 [0/800 (0%)]\tLoss: 20.672960\n",
+      "====> Train Epoch: 12 Average loss: 11.0092\n",
+      "====> Test Epoch: 12 Average loss: 3.7723\n",
+      "Train Epoch: 13 [0/800 (0%)]\tLoss: 2.635911\n",
+      "====> Train Epoch: 13 Average loss: 1.5510\n",
+      "====> Test Epoch: 13 Average loss: 1.2765\n",
+      "Train Epoch: 14 [0/800 (0%)]\tLoss: 0.891321\n",
+      "====> Train Epoch: 14 Average loss: 0.8177\n",
+      "====> Test Epoch: 14 Average loss: 0.6365\n",
+      "Train Epoch: 15 [0/800 (0%)]\tLoss: 0.475057\n",
+      "====> Train Epoch: 15 Average loss: 0.5230\n",
+      "====> Test Epoch: 15 Average loss: 0.6178\n",
+      "Train Epoch: 16 [0/800 (0%)]\tLoss: 0.478396\n",
+      "====> Train Epoch: 16 Average loss: 0.4701\n",
+      "====> Test Epoch: 16 Average loss: 0.5698\n",
+      "Train Epoch: 17 [0/800 (0%)]\tLoss: 0.432256\n",
+      "====> Train Epoch: 17 Average loss: 0.4701\n",
+      "====> Test Epoch: 17 Average loss: 0.5922\n",
+      "Train Epoch: 18 [0/800 (0%)]\tLoss: 0.370971\n",
+      "====> Train Epoch: 18 Average loss: 0.4501\n",
+      "====> Test Epoch: 18 Average loss: 0.5178\n",
+      "Train Epoch: 19 [0/800 (0%)]\tLoss: 0.414358\n",
+      "====> Train Epoch: 19 Average loss: 0.4366\n",
+      "====> Test Epoch: 19 Average loss: 0.4987\n",
+      "Train Epoch: 20 [0/800 (0%)]\tLoss: 0.409152\n",
+      "====> Train Epoch: 20 Average loss: 0.4115\n",
+      "====> Test Epoch: 20 Average loss: 0.5795\n",
+      "Train Epoch: 21 [0/800 (0%)]\tLoss: 0.358589\n",
+      "====> Train Epoch: 21 Average loss: 0.4051\n",
+      "====> Test Epoch: 21 Average loss: 0.5097\n",
+      "Train Epoch: 22 [0/800 (0%)]\tLoss: 0.340934\n",
+      "====> Train Epoch: 22 Average loss: 0.4006\n",
+      "====> Test Epoch: 22 Average loss: 0.5227\n",
+      "Train Epoch: 23 [0/800 (0%)]\tLoss: 0.364239\n",
+      "====> Train Epoch: 23 Average loss: 0.3981\n",
+      "====> Test Epoch: 23 Average loss: 0.5110\n",
+      "Train Epoch: 24 [0/800 (0%)]\tLoss: 0.467021\n",
+      "====> Train Epoch: 24 Average loss: 0.4026\n",
+      "====> Test Epoch: 24 Average loss: 0.4992\n",
+      "Train Epoch: 25 [0/800 (0%)]\tLoss: 0.367135\n",
+      "====> Train Epoch: 25 Average loss: 0.3962\n",
+      "====> Test Epoch: 25 Average loss: 0.4834\n",
+      "Train Epoch: 26 [0/800 (0%)]\tLoss: 0.354192\n",
+      "====> Train Epoch: 26 Average loss: 0.3957\n",
+      "====> Test Epoch: 26 Average loss: 0.5604\n",
+      "Train Epoch: 27 [0/800 (0%)]\tLoss: 0.363110\n",
+      "====> Train Epoch: 27 Average loss: 0.3873\n",
+      "====> Test Epoch: 27 Average loss: 0.5432\n",
+      "Train Epoch: 28 [0/800 (0%)]\tLoss: 0.410737\n",
+      "====> Train Epoch: 28 Average loss: 0.3854\n",
+      "====> Test Epoch: 28 Average loss: 0.5653\n",
+      "Train Epoch: 29 [0/800 (0%)]\tLoss: 0.438414\n",
+      "====> Train Epoch: 29 Average loss: 0.3896\n",
+      "====> Test Epoch: 29 Average loss: 0.5405\n",
+      "Train Epoch: 30 [0/800 (0%)]\tLoss: 0.364736\n",
+      "====> Train Epoch: 30 Average loss: 0.3919\n",
+      "====> Test Epoch: 30 Average loss: 0.4729\n",
+      "Train Epoch: 31 [0/800 (0%)]\tLoss: 0.359523\n",
+      "====> Train Epoch: 31 Average loss: 0.3832\n",
+      "====> Test Epoch: 31 Average loss: 0.4906\n",
+      "Train Epoch: 32 [0/800 (0%)]\tLoss: 0.363511\n",
+      "====> Train Epoch: 32 Average loss: 0.3898\n",
+      "====> Test Epoch: 32 Average loss: 0.5490\n",
+      "Train Epoch: 33 [0/800 (0%)]\tLoss: 0.366312\n",
+      "====> Train Epoch: 33 Average loss: 0.3775\n",
+      "====> Test Epoch: 33 Average loss: 0.5361\n",
+      "Train Epoch: 34 [0/800 (0%)]\tLoss: 0.294660\n",
+      "====> Train Epoch: 34 Average loss: 0.3831\n",
+      "====> Test Epoch: 34 Average loss: 0.5104\n",
+      "Train Epoch: 35 [0/800 (0%)]\tLoss: 0.320748\n",
+      "====> Train Epoch: 35 Average loss: 0.3798\n",
+      "====> Test Epoch: 35 Average loss: 0.5171\n",
+      "Train Epoch: 36 [0/800 (0%)]\tLoss: 0.326945\n",
+      "====> Train Epoch: 36 Average loss: 0.3779\n",
+      "====> Test Epoch: 36 Average loss: 0.5659\n",
+      "Train Epoch: 37 [0/800 (0%)]\tLoss: 0.422952\n",
+      "====> Train Epoch: 37 Average loss: 0.3930\n",
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+      "Train Epoch: 38 [0/800 (0%)]\tLoss: 0.366206\n",
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+      "Train Epoch: 39 [0/800 (0%)]\tLoss: 0.375366\n",
+      "====> Train Epoch: 39 Average loss: 0.3757\n",
+      "====> Test Epoch: 39 Average loss: 0.4838\n",
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+      "====> Test Epoch: 40 Average loss: 0.4783\n",
+      "Train Epoch: 41 [0/800 (0%)]\tLoss: 0.316981\n",
+      "====> Train Epoch: 41 Average loss: 0.3726\n",
+      "====> Test Epoch: 41 Average loss: 0.5378\n",
+      "Train Epoch: 42 [0/800 (0%)]\tLoss: 0.310224\n",
+      "====> Train Epoch: 42 Average loss: 0.3689\n",
+      "====> Test Epoch: 42 Average loss: 0.4702\n",
+      "Train Epoch: 43 [0/800 (0%)]\tLoss: 0.400191\n",
+      "====> Train Epoch: 43 Average loss: 0.3683\n",
+      "====> Test Epoch: 43 Average loss: 0.5155\n",
+      "Train Epoch: 44 [0/800 (0%)]\tLoss: 0.286684\n",
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+      "====> Test Epoch: 44 Average loss: 0.4841\n",
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+      "====> Train Epoch: 45 Average loss: 0.3655\n",
+      "====> Test Epoch: 45 Average loss: 0.4869\n",
+      "Train Epoch: 46 [0/800 (0%)]\tLoss: 0.288526\n",
+      "====> Train Epoch: 46 Average loss: 0.3654\n",
+      "====> Test Epoch: 46 Average loss: 0.4803\n",
+      "Train Epoch: 47 [0/800 (0%)]\tLoss: 0.344736\n",
+      "====> Train Epoch: 47 Average loss: 0.3665\n",
+      "====> Test Epoch: 47 Average loss: 0.4423\n",
+      "Train Epoch: 48 [0/800 (0%)]\tLoss: 0.345866\n",
+      "====> Train Epoch: 48 Average loss: 0.3599\n",
+      "====> Test Epoch: 48 Average loss: 0.4727\n",
+      "Train Epoch: 49 [0/800 (0%)]\tLoss: 0.364070\n",
+      "====> Train Epoch: 49 Average loss: 0.3608\n",
+      "====> Test Epoch: 49 Average loss: 0.4626\n",
+      "Train Epoch: 50 [0/800 (0%)]\tLoss: 0.302894\n",
+      "====> Train Epoch: 50 Average loss: 0.3599\n",
+      "====> Test Epoch: 50 Average loss: 0.5517\n",
+      "Train Epoch: 51 [0/800 (0%)]\tLoss: 0.299003\n",
+      "====> Train Epoch: 51 Average loss: 0.3544\n",
+      "====> Test Epoch: 51 Average loss: 0.5282\n",
+      "Train Epoch: 52 [0/800 (0%)]\tLoss: 0.326340\n",
+      "====> Train Epoch: 52 Average loss: 0.3555\n",
+      "====> Test Epoch: 52 Average loss: 0.4251\n",
+      "Train Epoch: 53 [0/800 (0%)]\tLoss: 0.340130\n",
+      "====> Train Epoch: 53 Average loss: 0.3625\n",
+      "====> Test Epoch: 53 Average loss: 0.4999\n",
+      "Train Epoch: 54 [0/800 (0%)]\tLoss: 0.327880\n",
+      "====> Train Epoch: 54 Average loss: 0.3628\n",
+      "====> Test Epoch: 54 Average loss: 0.4982\n",
+      "Train Epoch: 55 [0/800 (0%)]\tLoss: 0.385465\n",
+      "====> Train Epoch: 55 Average loss: 0.3578\n",
+      "====> Test Epoch: 55 Average loss: 0.4963\n",
+      "Train Epoch: 56 [0/800 (0%)]\tLoss: 0.329657\n",
+      "====> Train Epoch: 56 Average loss: 0.3554\n",
+      "====> Test Epoch: 56 Average loss: 0.4604\n",
+      "Train Epoch: 57 [0/800 (0%)]\tLoss: 0.333544\n",
+      "====> Train Epoch: 57 Average loss: 0.3558\n",
+      "====> Test Epoch: 57 Average loss: 0.4721\n",
+      "Train Epoch: 58 [0/800 (0%)]\tLoss: 0.318377\n",
+      "====> Train Epoch: 58 Average loss: 0.3526\n",
+      "====> Test Epoch: 58 Average loss: 0.4810\n",
+      "Train Epoch: 59 [0/800 (0%)]\tLoss: 0.343557\n",
+      "====> Train Epoch: 59 Average loss: 0.3632\n",
+      "====> Test Epoch: 59 Average loss: 0.4197\n",
+      "Train Epoch: 60 [0/800 (0%)]\tLoss: 0.341523\n",
+      "====> Train Epoch: 60 Average loss: 0.3496\n",
+      "====> Test Epoch: 60 Average loss: 0.4536\n",
+      "Train Epoch: 61 [0/800 (0%)]\tLoss: 0.315160\n",
+      "====> Train Epoch: 61 Average loss: 0.3472\n",
+      "====> Test Epoch: 61 Average loss: 0.4358\n",
+      "Train Epoch: 62 [0/800 (0%)]\tLoss: 0.361033\n",
+      "====> Train Epoch: 62 Average loss: 0.3500\n",
+      "====> Test Epoch: 62 Average loss: 0.4606\n",
+      "Train Epoch: 63 [0/800 (0%)]\tLoss: 0.327960\n",
+      "====> Train Epoch: 63 Average loss: 0.3464\n",
+      "====> Test Epoch: 63 Average loss: 0.4085\n",
+      "Train Epoch: 64 [0/800 (0%)]\tLoss: 0.315360\n",
+      "====> Train Epoch: 64 Average loss: 0.3492\n",
+      "====> Test Epoch: 64 Average loss: 0.4562\n",
+      "Train Epoch: 65 [0/800 (0%)]\tLoss: 0.328683\n",
+      "====> Train Epoch: 65 Average loss: 0.3552\n",
+      "====> Test Epoch: 65 Average loss: 0.4653\n",
+      "Train Epoch: 66 [0/800 (0%)]\tLoss: 0.361559\n",
+      "====> Train Epoch: 66 Average loss: 0.3458\n",
+      "====> Test Epoch: 66 Average loss: 0.4178\n",
+      "Train Epoch: 67 [0/800 (0%)]\tLoss: 0.350607\n",
+      "====> Train Epoch: 67 Average loss: 0.3456\n",
+      "====> Test Epoch: 67 Average loss: 0.4518\n",
+      "Train Epoch: 68 [0/800 (0%)]\tLoss: 0.332659\n",
+      "====> Train Epoch: 68 Average loss: 0.3447\n",
+      "====> Test Epoch: 68 Average loss: 0.4410\n",
+      "Train Epoch: 69 [0/800 (0%)]\tLoss: 0.359798\n",
+      "====> Train Epoch: 69 Average loss: 0.3466\n",
+      "====> Test Epoch: 69 Average loss: 0.3887\n",
+      "Train Epoch: 70 [0/800 (0%)]\tLoss: 0.331415\n",
+      "====> Train Epoch: 70 Average loss: 0.3468\n",
+      "====> Test Epoch: 70 Average loss: 0.4415\n",
+      "Train Epoch: 71 [0/800 (0%)]\tLoss: 0.290515\n",
+      "====> Train Epoch: 71 Average loss: 0.3502\n",
+      "====> Test Epoch: 71 Average loss: 0.4555\n",
+      "Train Epoch: 72 [0/800 (0%)]\tLoss: 0.326178\n",
+      "====> Train Epoch: 72 Average loss: 0.3432\n",
+      "====> Test Epoch: 72 Average loss: 0.4230\n",
+      "Train Epoch: 73 [0/800 (0%)]\tLoss: 0.352951\n",
+      "====> Train Epoch: 73 Average loss: 0.3410\n",
+      "====> Test Epoch: 73 Average loss: 0.4152\n",
+      "Train Epoch: 74 [0/800 (0%)]\tLoss: 0.345941\n",
+      "====> Train Epoch: 74 Average loss: 0.3441\n",
+      "====> Test Epoch: 74 Average loss: 0.4496\n",
+      "Train Epoch: 75 [0/800 (0%)]\tLoss: 0.323312\n",
+      "====> Train Epoch: 75 Average loss: 0.3525\n",
+      "====> Test Epoch: 75 Average loss: 0.4256\n",
+      "Train Epoch: 76 [0/800 (0%)]\tLoss: 0.359461\n",
+      "====> Train Epoch: 76 Average loss: 0.3456\n",
+      "====> Test Epoch: 76 Average loss: 0.4563\n",
+      "Train Epoch: 77 [0/800 (0%)]\tLoss: 0.309019\n",
+      "====> Train Epoch: 77 Average loss: 0.3410\n",
+      "====> Test Epoch: 77 Average loss: 0.4576\n",
+      "Train Epoch: 78 [0/800 (0%)]\tLoss: 0.277495\n",
+      "====> Train Epoch: 78 Average loss: 0.3422\n",
+      "====> Test Epoch: 78 Average loss: 0.4286\n",
+      "Train Epoch: 79 [0/800 (0%)]\tLoss: 0.331909\n",
+      "====> Train Epoch: 79 Average loss: 0.3421\n",
+      "====> Test Epoch: 79 Average loss: 0.4514\n",
+      "Train Epoch: 80 [0/800 (0%)]\tLoss: 0.328482\n",
+      "====> Train Epoch: 80 Average loss: 0.3392\n",
+      "====> Test Epoch: 80 Average loss: 0.4032\n",
+      "Train Epoch: 81 [0/800 (0%)]\tLoss: 0.360393\n",
+      "====> Train Epoch: 81 Average loss: 0.3402\n",
+      "====> Test Epoch: 81 Average loss: 0.4651\n",
+      "Train Epoch: 82 [0/800 (0%)]\tLoss: 0.346302\n",
+      "====> Train Epoch: 82 Average loss: 0.3435\n",
+      "====> Test Epoch: 82 Average loss: 0.4182\n",
+      "Train Epoch: 83 [0/800 (0%)]\tLoss: 0.341857\n",
+      "====> Train Epoch: 83 Average loss: 0.3382\n",
+      "====> Test Epoch: 83 Average loss: 0.4326\n",
+      "Train Epoch: 84 [0/800 (0%)]\tLoss: 0.345726\n",
+      "====> Train Epoch: 84 Average loss: 0.3398\n",
+      "====> Test Epoch: 84 Average loss: 0.4685\n",
+      "Train Epoch: 85 [0/800 (0%)]\tLoss: 0.322022\n",
+      "====> Train Epoch: 85 Average loss: 0.3398\n",
+      "====> Test Epoch: 85 Average loss: 0.4503\n",
+      "Train Epoch: 86 [0/800 (0%)]\tLoss: 0.324270\n",
+      "====> Train Epoch: 86 Average loss: 0.3390\n",
+      "====> Test Epoch: 86 Average loss: 0.4066\n",
+      "Train Epoch: 87 [0/800 (0%)]\tLoss: 0.361386\n",
+      "====> Train Epoch: 87 Average loss: 0.3412\n",
+      "====> Test Epoch: 87 Average loss: 0.4599\n",
+      "Train Epoch: 88 [0/800 (0%)]\tLoss: 0.352073\n",
+      "====> Train Epoch: 88 Average loss: 0.3393\n",
+      "====> Test Epoch: 88 Average loss: 0.4317\n",
+      "Train Epoch: 89 [0/800 (0%)]\tLoss: 0.301782\n",
+      "====> Train Epoch: 89 Average loss: 0.3385\n",
+      "====> Test Epoch: 89 Average loss: 0.4638\n",
+      "Train Epoch: 90 [0/800 (0%)]\tLoss: 0.322445\n",
+      "====> Train Epoch: 90 Average loss: 0.3458\n",
+      "====> Test Epoch: 90 Average loss: 0.4424\n",
+      "Train Epoch: 91 [0/800 (0%)]\tLoss: 0.368829\n",
+      "====> Train Epoch: 91 Average loss: 0.3470\n",
+      "====> Test Epoch: 91 Average loss: 0.4701\n",
+      "Train Epoch: 92 [0/800 (0%)]\tLoss: 0.328310\n",
+      "====> Train Epoch: 92 Average loss: 0.3521\n",
+      "====> Test Epoch: 92 Average loss: 0.4117\n",
+      "Train Epoch: 93 [0/800 (0%)]\tLoss: 0.332204\n",
+      "====> Train Epoch: 93 Average loss: 0.3395\n",
+      "====> Test Epoch: 93 Average loss: 0.4116\n",
+      "Train Epoch: 94 [0/800 (0%)]\tLoss: 0.380097\n",
+      "====> Train Epoch: 94 Average loss: 0.3380\n",
+      "====> Test Epoch: 94 Average loss: 0.4127\n",
+      "Train Epoch: 95 [0/800 (0%)]\tLoss: 0.334023\n",
+      "====> Train Epoch: 95 Average loss: 0.3435\n",
+      "====> Test Epoch: 95 Average loss: 0.4472\n",
+      "Train Epoch: 96 [0/800 (0%)]\tLoss: 0.294089\n",
+      "====> Train Epoch: 96 Average loss: 0.3399\n",
+      "====> Test Epoch: 96 Average loss: 0.4381\n",
+      "Train Epoch: 97 [0/800 (0%)]\tLoss: 0.338171\n",
+      "====> Train Epoch: 97 Average loss: 0.3358\n",
+      "====> Test Epoch: 97 Average loss: 0.4390\n",
+      "Train Epoch: 98 [0/800 (0%)]\tLoss: 0.303698\n",
+      "====> Train Epoch: 98 Average loss: 0.3366\n",
+      "====> Test Epoch: 98 Average loss: 0.4057\n",
+      "Train Epoch: 99 [0/800 (0%)]\tLoss: 0.288910\n",
+      "====> Train Epoch: 99 Average loss: 0.3383\n",
+      "====> Test Epoch: 99 Average loss: 0.4024\n",
+      "Train Epoch: 100 [0/800 (0%)]\tLoss: 0.320597\n",
+      "====> Train Epoch: 100 Average loss: 0.3359\n",
+      "====> Test Epoch: 100 Average loss: 0.4495\n",
+      "Train Epoch: 101 [0/800 (0%)]\tLoss: 0.338919\n",
+      "====> Train Epoch: 101 Average loss: 0.3379\n",
+      "====> Test Epoch: 101 Average loss: 0.4233\n",
+      "Train Epoch: 102 [0/800 (0%)]\tLoss: 0.327563\n",
+      "====> Train Epoch: 102 Average loss: 0.3382\n",
+      "====> Test Epoch: 102 Average loss: 0.4080\n",
+      "Train Epoch: 103 [0/800 (0%)]\tLoss: 0.335580\n",
+      "====> Train Epoch: 103 Average loss: 0.3393\n",
+      "====> Test Epoch: 103 Average loss: 0.4379\n",
+      "Train Epoch: 104 [0/800 (0%)]\tLoss: 0.352786\n",
+      "====> Train Epoch: 104 Average loss: 0.3351\n",
+      "====> Test Epoch: 104 Average loss: 0.4479\n",
+      "Train Epoch: 105 [0/800 (0%)]\tLoss: 0.288589\n",
+      "====> Train Epoch: 105 Average loss: 0.3399\n",
+      "====> Test Epoch: 105 Average loss: 0.4108\n",
+      "Train Epoch: 106 [0/800 (0%)]\tLoss: 0.323290\n",
+      "====> Train Epoch: 106 Average loss: 0.3445\n",
+      "====> Test Epoch: 106 Average loss: 0.4266\n",
+      "Train Epoch: 107 [0/800 (0%)]\tLoss: 0.316327\n",
+      "====> Train Epoch: 107 Average loss: 0.3427\n",
+      "====> Test Epoch: 107 Average loss: 0.4257\n",
+      "Train Epoch: 108 [0/800 (0%)]\tLoss: 0.296629\n",
+      "====> Train Epoch: 108 Average loss: 0.3392\n",
+      "====> Test Epoch: 108 Average loss: 0.4568\n",
+      "Train Epoch: 109 [0/800 (0%)]\tLoss: 0.351611\n",
+      "====> Train Epoch: 109 Average loss: 0.3364\n",
+      "====> Test Epoch: 109 Average loss: 0.4367\n",
+      "Train Epoch: 110 [0/800 (0%)]\tLoss: 0.332466\n",
+      "====> Train Epoch: 110 Average loss: 0.3372\n",
+      "====> Test Epoch: 110 Average loss: 0.4047\n",
+      "Train Epoch: 111 [0/800 (0%)]\tLoss: 0.334755\n",
+      "====> Train Epoch: 111 Average loss: 0.3350\n",
+      "====> Test Epoch: 111 Average loss: 0.4502\n",
+      "Train Epoch: 112 [0/800 (0%)]\tLoss: 0.298860\n",
+      "====> Train Epoch: 112 Average loss: 0.3380\n",
+      "====> Test Epoch: 112 Average loss: 0.4283\n",
+      "Train Epoch: 113 [0/800 (0%)]\tLoss: 0.312920\n",
+      "====> Train Epoch: 113 Average loss: 0.3426\n",
+      "====> Test Epoch: 113 Average loss: 0.4092\n",
+      "Train Epoch: 114 [0/800 (0%)]\tLoss: 0.322195\n",
+      "====> Train Epoch: 114 Average loss: 0.3417\n",
+      "====> Test Epoch: 114 Average loss: 0.4534\n",
+      "Train Epoch: 115 [0/800 (0%)]\tLoss: 0.340131\n",
+      "====> Train Epoch: 115 Average loss: 0.3401\n",
+      "====> Test Epoch: 115 Average loss: 0.4145\n",
+      "Train Epoch: 116 [0/800 (0%)]\tLoss: 0.296664\n",
+      "====> Train Epoch: 116 Average loss: 0.3430\n",
+      "====> Test Epoch: 116 Average loss: 0.4375\n",
+      "Train Epoch: 117 [0/800 (0%)]\tLoss: 0.274110\n",
+      "====> Train Epoch: 117 Average loss: 0.3448\n",
+      "====> Test Epoch: 117 Average loss: 0.4196\n",
+      "Train Epoch: 118 [0/800 (0%)]\tLoss: 0.354060\n",
+      "====> Train Epoch: 118 Average loss: 0.3382\n",
+      "====> Test Epoch: 118 Average loss: 0.4489\n",
+      "Train Epoch: 119 [0/800 (0%)]\tLoss: 0.299252\n",
+      "====> Train Epoch: 119 Average loss: 0.3354\n",
+      "====> Test Epoch: 119 Average loss: 0.4402\n",
+      "Train Epoch: 120 [0/800 (0%)]\tLoss: 0.257673\n",
+      "====> Train Epoch: 120 Average loss: 0.3341\n",
+      "====> Test Epoch: 120 Average loss: 0.4348\n",
+      "Train Epoch: 121 [0/800 (0%)]\tLoss: 0.296842\n",
+      "====> Train Epoch: 121 Average loss: 0.3395\n",
+      "====> Test Epoch: 121 Average loss: 0.4338\n",
+      "Train Epoch: 122 [0/800 (0%)]\tLoss: 0.325235\n",
+      "====> Train Epoch: 122 Average loss: 0.3411\n",
+      "====> Test Epoch: 122 Average loss: 0.3938\n",
+      "Train Epoch: 123 [0/800 (0%)]\tLoss: 0.349853\n",
+      "====> Train Epoch: 123 Average loss: 0.3357\n",
+      "====> Test Epoch: 123 Average loss: 0.3855\n",
+      "Train Epoch: 124 [0/800 (0%)]\tLoss: 0.285074\n",
+      "====> Train Epoch: 124 Average loss: 0.3410\n",
+      "====> Test Epoch: 124 Average loss: 0.4396\n",
+      "Train Epoch: 125 [0/800 (0%)]\tLoss: 0.294363\n",
+      "====> Train Epoch: 125 Average loss: 0.3369\n",
+      "====> Test Epoch: 125 Average loss: 0.4277\n",
+      "Train Epoch: 126 [0/800 (0%)]\tLoss: 0.322116\n",
+      "====> Train Epoch: 126 Average loss: 0.3373\n",
+      "====> Test Epoch: 126 Average loss: 0.4547\n",
+      "Train Epoch: 127 [0/800 (0%)]\tLoss: 0.392205\n",
+      "====> Train Epoch: 127 Average loss: 0.3366\n",
+      "====> Test Epoch: 127 Average loss: 0.4243\n",
+      "Train Epoch: 128 [0/800 (0%)]\tLoss: 0.329151\n",
+      "====> Train Epoch: 128 Average loss: 0.3389\n",
+      "====> Test Epoch: 128 Average loss: 0.4175\n",
+      "Train Epoch: 129 [0/800 (0%)]\tLoss: 0.294626\n",
+      "====> Train Epoch: 129 Average loss: 0.3362\n",
+      "====> Test Epoch: 129 Average loss: 0.4226\n",
+      "Train Epoch: 130 [0/800 (0%)]\tLoss: 0.334011\n",
+      "====> Train Epoch: 130 Average loss: 0.3429\n",
+      "====> Test Epoch: 130 Average loss: 0.4392\n",
+      "Train Epoch: 131 [0/800 (0%)]\tLoss: 0.332046\n",
+      "====> Train Epoch: 131 Average loss: 0.3342\n",
+      "====> Test Epoch: 131 Average loss: 0.4211\n",
+      "Train Epoch: 132 [0/800 (0%)]\tLoss: 0.312376\n",
+      "====> Train Epoch: 132 Average loss: 0.3348\n",
+      "====> Test Epoch: 132 Average loss: 0.4260\n",
+      "Train Epoch: 133 [0/800 (0%)]\tLoss: 0.383944\n",
+      "====> Train Epoch: 133 Average loss: 0.3392\n",
+      "====> Test Epoch: 133 Average loss: 0.3897\n",
+      "Train Epoch: 134 [0/800 (0%)]\tLoss: 0.370083\n",
+      "====> Train Epoch: 134 Average loss: 0.3385\n",
+      "====> Test Epoch: 134 Average loss: 0.4127\n",
+      "Train Epoch: 135 [0/800 (0%)]\tLoss: 0.335396\n",
+      "====> Train Epoch: 135 Average loss: 0.3336\n",
+      "====> Test Epoch: 135 Average loss: 0.4509\n",
+      "Train Epoch: 136 [0/800 (0%)]\tLoss: 0.349327\n",
+      "====> Train Epoch: 136 Average loss: 0.3361\n",
+      "====> Test Epoch: 136 Average loss: 0.4866\n",
+      "Train Epoch: 137 [0/800 (0%)]\tLoss: 0.321025\n",
+      "====> Train Epoch: 137 Average loss: 0.3374\n",
+      "====> Test Epoch: 137 Average loss: 0.3901\n",
+      "Train Epoch: 138 [0/800 (0%)]\tLoss: 0.283220\n",
+      "====> Train Epoch: 138 Average loss: 0.3398\n",
+      "====> Test Epoch: 138 Average loss: 0.4523\n",
+      "Train Epoch: 139 [0/800 (0%)]\tLoss: 0.309011\n",
+      "====> Train Epoch: 139 Average loss: 0.3367\n",
+      "====> Test Epoch: 139 Average loss: 0.4153\n",
+      "Train Epoch: 140 [0/800 (0%)]\tLoss: 0.325448\n",
+      "====> Train Epoch: 140 Average loss: 0.3360\n",
+      "====> Test Epoch: 140 Average loss: 0.4733\n",
+      "Train Epoch: 141 [0/800 (0%)]\tLoss: 0.307979\n",
+      "====> Train Epoch: 141 Average loss: 0.3422\n",
+      "====> Test Epoch: 141 Average loss: 0.4147\n",
+      "Train Epoch: 142 [0/800 (0%)]\tLoss: 0.311005\n",
+      "====> Train Epoch: 142 Average loss: 0.3407\n",
+      "====> Test Epoch: 142 Average loss: 0.4124\n",
+      "Train Epoch: 143 [0/800 (0%)]\tLoss: 0.276591\n",
+      "====> Train Epoch: 143 Average loss: 0.3451\n",
+      "====> Test Epoch: 143 Average loss: 0.4504\n",
+      "Train Epoch: 144 [0/800 (0%)]\tLoss: 0.389320\n",
+      "====> Train Epoch: 144 Average loss: 0.3387\n",
+      "====> Test Epoch: 144 Average loss: 0.4692\n",
+      "Train Epoch: 145 [0/800 (0%)]\tLoss: 0.331704\n",
+      "====> Train Epoch: 145 Average loss: 0.3308\n",
+      "====> Test Epoch: 145 Average loss: 0.3872\n",
+      "Train Epoch: 146 [0/800 (0%)]\tLoss: 0.304555\n",
+      "====> Train Epoch: 146 Average loss: 0.3344\n",
+      "====> Test Epoch: 146 Average loss: 0.3970\n",
+      "Train Epoch: 147 [0/800 (0%)]\tLoss: 0.370381\n",
+      "====> Train Epoch: 147 Average loss: 0.3411\n",
+      "====> Test Epoch: 147 Average loss: 0.4464\n",
+      "Train Epoch: 148 [0/800 (0%)]\tLoss: 0.305472\n",
+      "====> Train Epoch: 148 Average loss: 0.3353\n",
+      "====> Test Epoch: 148 Average loss: 0.4478\n",
+      "Train Epoch: 149 [0/800 (0%)]\tLoss: 0.294694\n",
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+      "Train Epoch: 169 [0/800 (0%)]\tLoss: 0.341918\n",
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+      "Train Epoch: 170 [0/800 (0%)]\tLoss: 0.407857\n",
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+      "Train Epoch: 171 [0/800 (0%)]\tLoss: 0.302195\n",
+      "====> Train Epoch: 171 Average loss: 0.3478\n",
+      "====> Test Epoch: 171 Average loss: 0.4174\n",
+      "Train Epoch: 172 [0/800 (0%)]\tLoss: 0.336693\n",
+      "====> Train Epoch: 172 Average loss: 0.3368\n",
+      "====> Test Epoch: 172 Average loss: 0.4394\n",
+      "Train Epoch: 173 [0/800 (0%)]\tLoss: 0.326823\n",
+      "====> Train Epoch: 173 Average loss: 0.3365\n",
+      "====> Test Epoch: 173 Average loss: 0.4476\n",
+      "Train Epoch: 174 [0/800 (0%)]\tLoss: 0.306480\n",
+      "====> Train Epoch: 174 Average loss: 0.3463\n",
+      "====> Test Epoch: 174 Average loss: 0.4069\n",
+      "Train Epoch: 175 [0/800 (0%)]\tLoss: 0.399629\n",
+      "====> Train Epoch: 175 Average loss: 0.3379\n",
+      "====> Test Epoch: 175 Average loss: 0.4116\n",
+      "Train Epoch: 176 [0/800 (0%)]\tLoss: 0.327628\n",
+      "====> Train Epoch: 176 Average loss: 0.3373\n",
+      "====> Test Epoch: 176 Average loss: 0.4248\n",
+      "Train Epoch: 177 [0/800 (0%)]\tLoss: 0.295664\n",
+      "====> Train Epoch: 177 Average loss: 0.3338\n",
+      "====> Test Epoch: 177 Average loss: 0.4371\n",
+      "Train Epoch: 178 [0/800 (0%)]\tLoss: 0.332204\n",
+      "====> Train Epoch: 178 Average loss: 0.3321\n",
+      "====> Test Epoch: 178 Average loss: 0.4152\n",
+      "Train Epoch: 179 [0/800 (0%)]\tLoss: 0.355991\n",
+      "====> Train Epoch: 179 Average loss: 0.3339\n",
+      "====> Test Epoch: 179 Average loss: 0.4077\n",
+      "Train Epoch: 180 [0/800 (0%)]\tLoss: 0.295245\n",
+      "====> Train Epoch: 180 Average loss: 0.3343\n",
+      "====> Test Epoch: 180 Average loss: 0.4377\n",
+      "Train Epoch: 181 [0/800 (0%)]\tLoss: 0.322589\n",
+      "====> Train Epoch: 181 Average loss: 0.3292\n",
+      "====> Test Epoch: 181 Average loss: 0.4340\n",
+      "Train Epoch: 182 [0/800 (0%)]\tLoss: 0.327280\n",
+      "====> Train Epoch: 182 Average loss: 0.3311\n",
+      "====> Test Epoch: 182 Average loss: 0.4126\n",
+      "Train Epoch: 183 [0/800 (0%)]\tLoss: 0.306734\n",
+      "====> Train Epoch: 183 Average loss: 0.3320\n",
+      "====> Test Epoch: 183 Average loss: 0.4296\n",
+      "Train Epoch: 184 [0/800 (0%)]\tLoss: 0.302349\n",
+      "====> Train Epoch: 184 Average loss: 0.3352\n",
+      "====> Test Epoch: 184 Average loss: 0.4168\n",
+      "Train Epoch: 185 [0/800 (0%)]\tLoss: 0.326094\n",
+      "====> Train Epoch: 185 Average loss: 0.3309\n",
+      "====> Test Epoch: 185 Average loss: 0.4090\n",
+      "Train Epoch: 186 [0/800 (0%)]\tLoss: 0.345535\n",
+      "====> Train Epoch: 186 Average loss: 0.3323\n",
+      "====> Test Epoch: 186 Average loss: 0.4064\n",
+      "Train Epoch: 187 [0/800 (0%)]\tLoss: 0.302290\n",
+      "====> Train Epoch: 187 Average loss: 0.3339\n",
+      "====> Test Epoch: 187 Average loss: 0.4490\n",
+      "Train Epoch: 188 [0/800 (0%)]\tLoss: 0.298911\n",
+      "====> Train Epoch: 188 Average loss: 0.3444\n",
+      "====> Test Epoch: 188 Average loss: 0.4362\n",
+      "Train Epoch: 189 [0/800 (0%)]\tLoss: 0.316099\n",
+      "====> Train Epoch: 189 Average loss: 0.3363\n",
+      "====> Test Epoch: 189 Average loss: 0.4029\n",
+      "Train Epoch: 190 [0/800 (0%)]\tLoss: 0.263224\n",
+      "====> Train Epoch: 190 Average loss: 0.3285\n",
+      "====> Test Epoch: 190 Average loss: 0.4221\n",
+      "Train Epoch: 191 [0/800 (0%)]\tLoss: 0.331940\n",
+      "====> Train Epoch: 191 Average loss: 0.3342\n",
+      "====> Test Epoch: 191 Average loss: 0.4407\n",
+      "Train Epoch: 192 [0/800 (0%)]\tLoss: 0.324911\n",
+      "====> Train Epoch: 192 Average loss: 0.3311\n",
+      "====> Test Epoch: 192 Average loss: 0.4131\n",
+      "Train Epoch: 193 [0/800 (0%)]\tLoss: 0.335330\n",
+      "====> Train Epoch: 193 Average loss: 0.3319\n",
+      "====> Test Epoch: 193 Average loss: 0.4062\n",
+      "Train Epoch: 194 [0/800 (0%)]\tLoss: 0.318260\n",
+      "====> Train Epoch: 194 Average loss: 0.3326\n",
+      "====> Test Epoch: 194 Average loss: 0.4211\n",
+      "Train Epoch: 195 [0/800 (0%)]\tLoss: 0.337618\n",
+      "====> Train Epoch: 195 Average loss: 0.3303\n",
+      "====> Test Epoch: 195 Average loss: 0.4069\n",
+      "Train Epoch: 196 [0/800 (0%)]\tLoss: 0.354162\n",
+      "====> Train Epoch: 196 Average loss: 0.3377\n",
+      "====> Test Epoch: 196 Average loss: 0.4092\n",
+      "Train Epoch: 197 [0/800 (0%)]\tLoss: 0.333098\n",
+      "====> Train Epoch: 197 Average loss: 0.3351\n",
+      "====> Test Epoch: 197 Average loss: 0.4753\n",
+      "Train Epoch: 198 [0/800 (0%)]\tLoss: 0.354940\n",
+      "====> Train Epoch: 198 Average loss: 0.3351\n",
+      "====> Test Epoch: 198 Average loss: 0.4184\n",
+      "Train Epoch: 199 [0/800 (0%)]\tLoss: 0.332484\n",
+      "====> Train Epoch: 199 Average loss: 0.3318\n",
+      "====> Test Epoch: 199 Average loss: 0.4286\n",
+      "Train Epoch: 200 [0/800 (0%)]\tLoss: 0.339608\n",
+      "====> Train Epoch: 200 Average loss: 0.3320\n",
+      "====> Test Epoch: 200 Average loss: 0.5072\n",
+      "Train Epoch: 201 [0/800 (0%)]\tLoss: 0.250427\n",
+      "====> Train Epoch: 201 Average loss: 0.3390\n",
+      "====> Test Epoch: 201 Average loss: 0.4254\n",
+      "Train Epoch: 202 [0/800 (0%)]\tLoss: 0.337059\n",
+      "====> Train Epoch: 202 Average loss: 0.3370\n",
+      "====> Test Epoch: 202 Average loss: 0.4127\n",
+      "Train Epoch: 203 [0/800 (0%)]\tLoss: 0.301415\n",
+      "====> Train Epoch: 203 Average loss: 0.3353\n",
+      "====> Test Epoch: 203 Average loss: 0.4146\n",
+      "Train Epoch: 204 [0/800 (0%)]\tLoss: 0.313147\n",
+      "====> Train Epoch: 204 Average loss: 0.3357\n",
+      "====> Test Epoch: 204 Average loss: 0.4527\n",
+      "Train Epoch: 205 [0/800 (0%)]\tLoss: 0.341395\n",
+      "====> Train Epoch: 205 Average loss: 0.3344\n",
+      "====> Test Epoch: 205 Average loss: 0.4752\n",
+      "Train Epoch: 206 [0/800 (0%)]\tLoss: 0.312960\n",
+      "====> Train Epoch: 206 Average loss: 0.3404\n",
+      "====> Test Epoch: 206 Average loss: 0.4416\n",
+      "Train Epoch: 207 [0/800 (0%)]\tLoss: 0.299602\n",
+      "====> Train Epoch: 207 Average loss: 0.3409\n",
+      "====> Test Epoch: 207 Average loss: 0.4033\n",
+      "Train Epoch: 208 [0/800 (0%)]\tLoss: 0.307093\n",
+      "====> Train Epoch: 208 Average loss: 0.3342\n",
+      "====> Test Epoch: 208 Average loss: 0.4251\n",
+      "Train Epoch: 209 [0/800 (0%)]\tLoss: 0.354619\n",
+      "====> Train Epoch: 209 Average loss: 0.3342\n",
+      "====> Test Epoch: 209 Average loss: 0.4300\n",
+      "Train Epoch: 210 [0/800 (0%)]\tLoss: 0.325339\n",
+      "====> Train Epoch: 210 Average loss: 0.3405\n",
+      "====> Test Epoch: 210 Average loss: 0.4138\n",
+      "Train Epoch: 211 [0/800 (0%)]\tLoss: 0.314749\n",
+      "====> Train Epoch: 211 Average loss: 0.3402\n",
+      "====> Test Epoch: 211 Average loss: 0.4275\n",
+      "Train Epoch: 212 [0/800 (0%)]\tLoss: 0.368186\n",
+      "====> Train Epoch: 212 Average loss: 0.3267\n",
+      "====> Test Epoch: 212 Average loss: 0.3873\n",
+      "Train Epoch: 213 [0/800 (0%)]\tLoss: 0.296698\n",
+      "====> Train Epoch: 213 Average loss: 0.3298\n",
+      "====> Test Epoch: 213 Average loss: 0.3760\n",
+      "Train Epoch: 214 [0/800 (0%)]\tLoss: 0.315352\n",
+      "====> Train Epoch: 214 Average loss: 0.3326\n",
+      "====> Test Epoch: 214 Average loss: 0.4321\n",
+      "Train Epoch: 215 [0/800 (0%)]\tLoss: 0.356242\n",
+      "====> Train Epoch: 215 Average loss: 0.3405\n",
+      "====> Test Epoch: 215 Average loss: 0.4701\n",
+      "Train Epoch: 216 [0/800 (0%)]\tLoss: 0.366479\n",
+      "====> Train Epoch: 216 Average loss: 0.3357\n",
+      "====> Test Epoch: 216 Average loss: 0.4360\n",
+      "Train Epoch: 217 [0/800 (0%)]\tLoss: 0.304180\n",
+      "====> Train Epoch: 217 Average loss: 0.3369\n",
+      "====> Test Epoch: 217 Average loss: 0.4488\n",
+      "Train Epoch: 218 [0/800 (0%)]\tLoss: 0.344373\n",
+      "====> Train Epoch: 218 Average loss: 0.3353\n",
+      "====> Test Epoch: 218 Average loss: 0.4325\n",
+      "Train Epoch: 219 [0/800 (0%)]\tLoss: 0.345227\n",
+      "====> Train Epoch: 219 Average loss: 0.3342\n",
+      "====> Test Epoch: 219 Average loss: 0.4102\n",
+      "Train Epoch: 220 [0/800 (0%)]\tLoss: 0.341289\n",
+      "====> Train Epoch: 220 Average loss: 0.3332\n",
+      "====> Test Epoch: 220 Average loss: 0.4598\n",
+      "Train Epoch: 221 [0/800 (0%)]\tLoss: 0.337682\n",
+      "====> Train Epoch: 221 Average loss: 0.3326\n",
+      "====> Test Epoch: 221 Average loss: 0.4428\n",
+      "Train Epoch: 222 [0/800 (0%)]\tLoss: 0.318066\n",
+      "====> Train Epoch: 222 Average loss: 0.3460\n",
+      "====> Test Epoch: 222 Average loss: 0.4319\n",
+      "Train Epoch: 223 [0/800 (0%)]\tLoss: 0.277225\n",
+      "====> Train Epoch: 223 Average loss: 0.3351\n",
+      "====> Test Epoch: 223 Average loss: 0.4356\n",
+      "Train Epoch: 224 [0/800 (0%)]\tLoss: 0.348051\n",
+      "====> Train Epoch: 224 Average loss: 0.3275\n",
+      "====> Test Epoch: 224 Average loss: 0.4059\n",
+      "Train Epoch: 225 [0/800 (0%)]\tLoss: 0.327616\n",
+      "====> Train Epoch: 225 Average loss: 0.3316\n",
+      "====> Test Epoch: 225 Average loss: 0.4457\n",
+      "Train Epoch: 226 [0/800 (0%)]\tLoss: 0.281431\n",
+      "====> Train Epoch: 226 Average loss: 0.3331\n",
+      "====> Test Epoch: 226 Average loss: 0.4034\n",
+      "Train Epoch: 227 [0/800 (0%)]\tLoss: 0.279887\n",
+      "====> Train Epoch: 227 Average loss: 0.3340\n",
+      "====> Test Epoch: 227 Average loss: 0.4107\n",
+      "Train Epoch: 228 [0/800 (0%)]\tLoss: 0.346101\n",
+      "====> Train Epoch: 228 Average loss: 0.3319\n",
+      "====> Test Epoch: 228 Average loss: 0.4297\n",
+      "Train Epoch: 229 [0/800 (0%)]\tLoss: 0.302602\n",
+      "====> Train Epoch: 229 Average loss: 0.3368\n",
+      "====> Test Epoch: 229 Average loss: 0.4149\n",
+      "Train Epoch: 230 [0/800 (0%)]\tLoss: 0.281826\n",
+      "====> Train Epoch: 230 Average loss: 0.3353\n",
+      "====> Test Epoch: 230 Average loss: 0.4439\n",
+      "Train Epoch: 231 [0/800 (0%)]\tLoss: 0.316216\n",
+      "====> Train Epoch: 231 Average loss: 0.3303\n",
+      "====> Test Epoch: 231 Average loss: 0.4114\n",
+      "Train Epoch: 232 [0/800 (0%)]\tLoss: 0.294380\n",
+      "====> Train Epoch: 232 Average loss: 0.3289\n",
+      "====> Test Epoch: 232 Average loss: 0.3973\n",
+      "Train Epoch: 233 [0/800 (0%)]\tLoss: 0.348873\n",
+      "====> Train Epoch: 233 Average loss: 0.3393\n",
+      "====> Test Epoch: 233 Average loss: 0.4550\n",
+      "Train Epoch: 234 [0/800 (0%)]\tLoss: 0.415974\n",
+      "====> Train Epoch: 234 Average loss: 0.3332\n",
+      "====> Test Epoch: 234 Average loss: 0.4052\n",
+      "Train Epoch: 235 [0/800 (0%)]\tLoss: 0.292791\n",
+      "====> Train Epoch: 235 Average loss: 0.3293\n",
+      "====> Test Epoch: 235 Average loss: 0.4533\n",
+      "Train Epoch: 236 [0/800 (0%)]\tLoss: 0.315637\n",
+      "====> Train Epoch: 236 Average loss: 0.3361\n",
+      "====> Test Epoch: 236 Average loss: 0.4642\n",
+      "Train Epoch: 237 [0/800 (0%)]\tLoss: 0.305269\n",
+      "====> Train Epoch: 237 Average loss: 0.3378\n",
+      "====> Test Epoch: 237 Average loss: 0.4429\n",
+      "Train Epoch: 238 [0/800 (0%)]\tLoss: 0.321044\n",
+      "====> Train Epoch: 238 Average loss: 0.3389\n",
+      "====> Test Epoch: 238 Average loss: 0.4321\n",
+      "Train Epoch: 239 [0/800 (0%)]\tLoss: 0.308239\n",
+      "====> Train Epoch: 239 Average loss: 0.3353\n",
+      "====> Test Epoch: 239 Average loss: 0.4150\n",
+      "Train Epoch: 240 [0/800 (0%)]\tLoss: 0.351744\n",
+      "====> Train Epoch: 240 Average loss: 0.3337\n",
+      "====> Test Epoch: 240 Average loss: 0.4470\n",
+      "Train Epoch: 241 [0/800 (0%)]\tLoss: 0.358029\n",
+      "====> Train Epoch: 241 Average loss: 0.3305\n",
+      "====> Test Epoch: 241 Average loss: 0.4277\n",
+      "Train Epoch: 242 [0/800 (0%)]\tLoss: 0.321355\n",
+      "====> Train Epoch: 242 Average loss: 0.3301\n",
+      "====> Test Epoch: 242 Average loss: 0.4120\n",
+      "Train Epoch: 243 [0/800 (0%)]\tLoss: 0.362843\n",
+      "====> Train Epoch: 243 Average loss: 0.3339\n",
+      "====> Test Epoch: 243 Average loss: 0.4054\n",
+      "Train Epoch: 244 [0/800 (0%)]\tLoss: 0.328035\n",
+      "====> Train Epoch: 244 Average loss: 0.3386\n",
+      "====> Test Epoch: 244 Average loss: 0.4287\n",
+      "Train Epoch: 245 [0/800 (0%)]\tLoss: 0.344948\n",
+      "====> Train Epoch: 245 Average loss: 0.3304\n",
+      "====> Test Epoch: 245 Average loss: 0.4349\n",
+      "Train Epoch: 246 [0/800 (0%)]\tLoss: 0.308394\n",
+      "====> Train Epoch: 246 Average loss: 0.3278\n",
+      "====> Test Epoch: 246 Average loss: 0.4140\n",
+      "Train Epoch: 247 [0/800 (0%)]\tLoss: 0.311953\n",
+      "====> Train Epoch: 247 Average loss: 0.3288\n",
+      "====> Test Epoch: 247 Average loss: 0.4327\n",
+      "Train Epoch: 248 [0/800 (0%)]\tLoss: 0.305728\n",
+      "====> Train Epoch: 248 Average loss: 0.3333\n",
+      "====> Test Epoch: 248 Average loss: 0.4147\n",
+      "Train Epoch: 249 [0/800 (0%)]\tLoss: 0.329084\n",
+      "====> Train Epoch: 249 Average loss: 0.3317\n",
+      "====> Test Epoch: 249 Average loss: 0.4429\n",
+      "Train Epoch: 250 [0/800 (0%)]\tLoss: 0.301968\n",
+      "====> Train Epoch: 250 Average loss: 0.3339\n",
+      "====> Test Epoch: 250 Average loss: 0.4333\n",
+      "Train Epoch: 251 [0/800 (0%)]\tLoss: 0.301946\n",
+      "====> Train Epoch: 251 Average loss: 0.3286\n",
+      "====> Test Epoch: 251 Average loss: 0.4179\n",
+      "Train Epoch: 252 [0/800 (0%)]\tLoss: 0.320120\n",
+      "====> Train Epoch: 252 Average loss: 0.3349\n",
+      "====> Test Epoch: 252 Average loss: 0.4101\n",
+      "Train Epoch: 253 [0/800 (0%)]\tLoss: 0.323264\n",
+      "====> Train Epoch: 253 Average loss: 0.3344\n",
+      "====> Test Epoch: 253 Average loss: 0.4581\n",
+      "Train Epoch: 254 [0/800 (0%)]\tLoss: 0.349070\n",
+      "====> Train Epoch: 254 Average loss: 0.3314\n",
+      "====> Test Epoch: 254 Average loss: 0.4400\n",
+      "Train Epoch: 255 [0/800 (0%)]\tLoss: 0.324259\n",
+      "====> Train Epoch: 255 Average loss: 0.3335\n",
+      "====> Test Epoch: 255 Average loss: 0.4046\n",
+      "Train Epoch: 256 [0/800 (0%)]\tLoss: 0.315389\n",
+      "====> Train Epoch: 256 Average loss: 0.3340\n",
+      "====> Test Epoch: 256 Average loss: 0.4503\n",
+      "Train Epoch: 257 [0/800 (0%)]\tLoss: 0.311935\n",
+      "====> Train Epoch: 257 Average loss: 0.3342\n",
+      "====> Test Epoch: 257 Average loss: 0.3791\n",
+      "Train Epoch: 258 [0/800 (0%)]\tLoss: 0.283838\n",
+      "====> Train Epoch: 258 Average loss: 0.3348\n",
+      "====> Test Epoch: 258 Average loss: 0.4551\n",
+      "Train Epoch: 259 [0/800 (0%)]\tLoss: 0.320332\n",
+      "====> Train Epoch: 259 Average loss: 0.3320\n",
+      "====> Test Epoch: 259 Average loss: 0.3790\n",
+      "Train Epoch: 260 [0/800 (0%)]\tLoss: 0.277346\n",
+      "====> Train Epoch: 260 Average loss: 0.3339\n",
+      "====> Test Epoch: 260 Average loss: 0.4220\n",
+      "Train Epoch: 261 [0/800 (0%)]\tLoss: 0.340593\n",
+      "====> Train Epoch: 261 Average loss: 0.3327\n",
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+      "Train Epoch: 269 [0/800 (0%)]\tLoss: 0.316169\n",
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+      "====> Test Epoch: 273 Average loss: 0.4404\n",
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+      "Train Epoch: 276 [0/800 (0%)]\tLoss: 0.272207\n",
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+      "Train Epoch: 278 [0/800 (0%)]\tLoss: 0.312439\n",
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+      "====> Test Epoch: 278 Average loss: 0.4290\n",
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+      "====> Train Epoch: 279 Average loss: 0.3331\n",
+      "====> Test Epoch: 279 Average loss: 0.4686\n",
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+      "====> Train Epoch: 280 Average loss: 0.3351\n",
+      "====> Test Epoch: 280 Average loss: 0.4208\n",
+      "Train Epoch: 281 [0/800 (0%)]\tLoss: 0.330766\n",
+      "====> Train Epoch: 281 Average loss: 0.3324\n",
+      "====> Test Epoch: 281 Average loss: 0.4230\n",
+      "Train Epoch: 282 [0/800 (0%)]\tLoss: 0.311964\n",
+      "====> Train Epoch: 282 Average loss: 0.3306\n",
+      "====> Test Epoch: 282 Average loss: 0.3752\n",
+      "Train Epoch: 283 [0/800 (0%)]\tLoss: 0.309912\n",
+      "====> Train Epoch: 283 Average loss: 0.3379\n",
+      "====> Test Epoch: 283 Average loss: 0.3797\n",
+      "Train Epoch: 284 [0/800 (0%)]\tLoss: 0.295896\n",
+      "====> Train Epoch: 284 Average loss: 0.3427\n",
+      "====> Test Epoch: 284 Average loss: 0.4440\n",
+      "Train Epoch: 285 [0/800 (0%)]\tLoss: 0.303134\n",
+      "====> Train Epoch: 285 Average loss: 0.3308\n",
+      "====> Test Epoch: 285 Average loss: 0.4133\n",
+      "Train Epoch: 286 [0/800 (0%)]\tLoss: 0.280549\n",
+      "====> Train Epoch: 286 Average loss: 0.3373\n",
+      "====> Test Epoch: 286 Average loss: 0.4062\n",
+      "Train Epoch: 287 [0/800 (0%)]\tLoss: 0.300696\n",
+      "====> Train Epoch: 287 Average loss: 0.3316\n",
+      "====> Test Epoch: 287 Average loss: 0.3883\n",
+      "Train Epoch: 288 [0/800 (0%)]\tLoss: 0.335261\n",
+      "====> Train Epoch: 288 Average loss: 0.3310\n",
+      "====> Test Epoch: 288 Average loss: 0.4110\n",
+      "Train Epoch: 289 [0/800 (0%)]\tLoss: 0.316794\n",
+      "====> Train Epoch: 289 Average loss: 0.3311\n",
+      "====> Test Epoch: 289 Average loss: 0.4128\n",
+      "Train Epoch: 290 [0/800 (0%)]\tLoss: 0.340596\n",
+      "====> Train Epoch: 290 Average loss: 0.3352\n",
+      "====> Test Epoch: 290 Average loss: 0.3839\n",
+      "Train Epoch: 291 [0/800 (0%)]\tLoss: 0.295371\n",
+      "====> Train Epoch: 291 Average loss: 0.3391\n",
+      "====> Test Epoch: 291 Average loss: 0.4207\n",
+      "Train Epoch: 292 [0/800 (0%)]\tLoss: 0.305484\n",
+      "====> Train Epoch: 292 Average loss: 0.3378\n",
+      "====> Test Epoch: 292 Average loss: 0.4174\n",
+      "Train Epoch: 293 [0/800 (0%)]\tLoss: 0.269608\n",
+      "====> Train Epoch: 293 Average loss: 0.3328\n",
+      "====> Test Epoch: 293 Average loss: 0.4369\n",
+      "Train Epoch: 294 [0/800 (0%)]\tLoss: 0.314887\n",
+      "====> Train Epoch: 294 Average loss: 0.3314\n",
+      "====> Test Epoch: 294 Average loss: 0.4276\n",
+      "Train Epoch: 295 [0/800 (0%)]\tLoss: 0.332695\n",
+      "====> Train Epoch: 295 Average loss: 0.3299\n",
+      "====> Test Epoch: 295 Average loss: 0.4133\n",
+      "Train Epoch: 296 [0/800 (0%)]\tLoss: 0.279944\n",
+      "====> Train Epoch: 296 Average loss: 0.3328\n",
+      "====> Test Epoch: 296 Average loss: 0.4374\n",
+      "Train Epoch: 297 [0/800 (0%)]\tLoss: 0.331745\n",
+      "====> Train Epoch: 297 Average loss: 0.3348\n",
+      "====> Test Epoch: 297 Average loss: 0.4132\n",
+      "Train Epoch: 298 [0/800 (0%)]\tLoss: 0.355335\n",
+      "====> Train Epoch: 298 Average loss: 0.3306\n",
+      "====> Test Epoch: 298 Average loss: 0.4462\n",
+      "Train Epoch: 299 [0/800 (0%)]\tLoss: 0.362715\n",
+      "====> Train Epoch: 299 Average loss: 0.3345\n",
+      "====> Test Epoch: 299 Average loss: 0.3914\n",
+      "Train Epoch: 300 [0/800 (0%)]\tLoss: 0.304918\n",
+      "====> Train Epoch: 300 Average loss: 0.3323\n",
+      "====> Test Epoch: 300 Average loss: 0.4407\n",
+      "Train Epoch: 301 [0/800 (0%)]\tLoss: 0.314781\n",
+      "====> Train Epoch: 301 Average loss: 0.3340\n",
+      "====> Test Epoch: 301 Average loss: 0.4152\n",
+      "Train Epoch: 302 [0/800 (0%)]\tLoss: 0.314543\n",
+      "====> Train Epoch: 302 Average loss: 0.3343\n",
+      "====> Test Epoch: 302 Average loss: 0.4493\n",
+      "Train Epoch: 303 [0/800 (0%)]\tLoss: 0.334269\n",
+      "====> Train Epoch: 303 Average loss: 0.3367\n",
+      "====> Test Epoch: 303 Average loss: 0.4379\n",
+      "Train Epoch: 304 [0/800 (0%)]\tLoss: 0.311459\n",
+      "====> Train Epoch: 304 Average loss: 0.3345\n",
+      "====> Test Epoch: 304 Average loss: 0.4131\n",
+      "Train Epoch: 305 [0/800 (0%)]\tLoss: 0.323070\n",
+      "====> Train Epoch: 305 Average loss: 0.3382\n",
+      "====> Test Epoch: 305 Average loss: 0.4659\n",
+      "Train Epoch: 306 [0/800 (0%)]\tLoss: 0.363087\n",
+      "====> Train Epoch: 306 Average loss: 0.3449\n",
+      "====> Test Epoch: 306 Average loss: 0.4412\n",
+      "Train Epoch: 307 [0/800 (0%)]\tLoss: 0.336702\n",
+      "====> Train Epoch: 307 Average loss: 0.3388\n",
+      "====> Test Epoch: 307 Average loss: 0.4507\n",
+      "Train Epoch: 308 [0/800 (0%)]\tLoss: 0.303156\n",
+      "====> Train Epoch: 308 Average loss: 0.3464\n",
+      "====> Test Epoch: 308 Average loss: 0.4495\n",
+      "Train Epoch: 309 [0/800 (0%)]\tLoss: 0.338911\n",
+      "====> Train Epoch: 309 Average loss: 0.3318\n",
+      "====> Test Epoch: 309 Average loss: 0.4288\n",
+      "Train Epoch: 310 [0/800 (0%)]\tLoss: 0.291174\n",
+      "====> Train Epoch: 310 Average loss: 0.3339\n",
+      "====> Test Epoch: 310 Average loss: 0.4526\n",
+      "Train Epoch: 311 [0/800 (0%)]\tLoss: 0.291725\n",
+      "====> Train Epoch: 311 Average loss: 0.3362\n",
+      "====> Test Epoch: 311 Average loss: 0.4517\n",
+      "Train Epoch: 312 [0/800 (0%)]\tLoss: 0.311413\n",
+      "====> Train Epoch: 312 Average loss: 0.3346\n",
+      "====> Test Epoch: 312 Average loss: 0.4113\n",
+      "Train Epoch: 313 [0/800 (0%)]\tLoss: 0.276459\n",
+      "====> Train Epoch: 313 Average loss: 0.3324\n",
+      "====> Test Epoch: 313 Average loss: 0.4090\n",
+      "Train Epoch: 314 [0/800 (0%)]\tLoss: 0.285265\n",
+      "====> Train Epoch: 314 Average loss: 0.3352\n",
+      "====> Test Epoch: 314 Average loss: 0.4904\n",
+      "Train Epoch: 315 [0/800 (0%)]\tLoss: 0.316015\n",
+      "====> Train Epoch: 315 Average loss: 0.3448\n",
+      "====> Test Epoch: 315 Average loss: 0.4302\n",
+      "Train Epoch: 316 [0/800 (0%)]\tLoss: 0.301770\n",
+      "====> Train Epoch: 316 Average loss: 0.3295\n",
+      "====> Test Epoch: 316 Average loss: 0.4241\n",
+      "Train Epoch: 317 [0/800 (0%)]\tLoss: 0.381173\n",
+      "====> Train Epoch: 317 Average loss: 0.3396\n",
+      "====> Test Epoch: 317 Average loss: 0.3963\n",
+      "Train Epoch: 318 [0/800 (0%)]\tLoss: 0.334012\n",
+      "====> Train Epoch: 318 Average loss: 0.3361\n",
+      "====> Test Epoch: 318 Average loss: 0.4548\n",
+      "Train Epoch: 319 [0/800 (0%)]\tLoss: 0.356340\n",
+      "====> Train Epoch: 319 Average loss: 0.3321\n",
+      "====> Test Epoch: 319 Average loss: 0.4149\n",
+      "Train Epoch: 320 [0/800 (0%)]\tLoss: 0.300155\n",
+      "====> Train Epoch: 320 Average loss: 0.3324\n",
+      "====> Test Epoch: 320 Average loss: 0.4163\n",
+      "Train Epoch: 321 [0/800 (0%)]\tLoss: 0.367943\n",
+      "====> Train Epoch: 321 Average loss: 0.3389\n",
+      "====> Test Epoch: 321 Average loss: 0.4134\n",
+      "Train Epoch: 322 [0/800 (0%)]\tLoss: 0.349321\n",
+      "====> Train Epoch: 322 Average loss: 0.3379\n",
+      "====> Test Epoch: 322 Average loss: 0.4064\n",
+      "Train Epoch: 323 [0/800 (0%)]\tLoss: 0.365664\n",
+      "====> Train Epoch: 323 Average loss: 0.3386\n",
+      "====> Test Epoch: 323 Average loss: 0.4354\n",
+      "Train Epoch: 324 [0/800 (0%)]\tLoss: 0.309426\n",
+      "====> Train Epoch: 324 Average loss: 0.3307\n",
+      "====> Test Epoch: 324 Average loss: 0.3631\n",
+      "Train Epoch: 325 [0/800 (0%)]\tLoss: 0.288450\n",
+      "====> Train Epoch: 325 Average loss: 0.3301\n",
+      "====> Test Epoch: 325 Average loss: 0.4009\n",
+      "Train Epoch: 326 [0/800 (0%)]\tLoss: 0.377187\n",
+      "====> Train Epoch: 326 Average loss: 0.3304\n",
+      "====> Test Epoch: 326 Average loss: 0.4147\n",
+      "Train Epoch: 327 [0/800 (0%)]\tLoss: 0.328444\n",
+      "====> Train Epoch: 327 Average loss: 0.3313\n",
+      "====> Test Epoch: 327 Average loss: 0.3786\n",
+      "Train Epoch: 328 [0/800 (0%)]\tLoss: 0.315062\n",
+      "====> Train Epoch: 328 Average loss: 0.3304\n",
+      "====> Test Epoch: 328 Average loss: 0.3916\n",
+      "Train Epoch: 329 [0/800 (0%)]\tLoss: 0.285129\n",
+      "====> Train Epoch: 329 Average loss: 0.3369\n",
+      "====> Test Epoch: 329 Average loss: 0.4158\n",
+      "Train Epoch: 330 [0/800 (0%)]\tLoss: 0.331442\n",
+      "====> Train Epoch: 330 Average loss: 0.3328\n",
+      "====> Test Epoch: 330 Average loss: 0.4472\n",
+      "Train Epoch: 331 [0/800 (0%)]\tLoss: 0.289979\n",
+      "====> Train Epoch: 331 Average loss: 0.3344\n",
+      "====> Test Epoch: 331 Average loss: 0.4276\n",
+      "Train Epoch: 332 [0/800 (0%)]\tLoss: 0.272703\n",
+      "====> Train Epoch: 332 Average loss: 0.3318\n",
+      "====> Test Epoch: 332 Average loss: 0.4568\n",
+      "Train Epoch: 333 [0/800 (0%)]\tLoss: 0.353512\n",
+      "====> Train Epoch: 333 Average loss: 0.3324\n",
+      "====> Test Epoch: 333 Average loss: 0.3967\n",
+      "Train Epoch: 334 [0/800 (0%)]\tLoss: 0.291632\n",
+      "====> Train Epoch: 334 Average loss: 0.3367\n",
+      "====> Test Epoch: 334 Average loss: 0.4176\n",
+      "Train Epoch: 335 [0/800 (0%)]\tLoss: 0.316842\n",
+      "====> Train Epoch: 335 Average loss: 0.3325\n",
+      "====> Test Epoch: 335 Average loss: 0.4055\n",
+      "Train Epoch: 336 [0/800 (0%)]\tLoss: 0.349011\n",
+      "====> Train Epoch: 336 Average loss: 0.3307\n",
+      "====> Test Epoch: 336 Average loss: 0.3797\n",
+      "Train Epoch: 337 [0/800 (0%)]\tLoss: 0.295706\n",
+      "====> Train Epoch: 337 Average loss: 0.3333\n",
+      "====> Test Epoch: 337 Average loss: 0.4061\n",
+      "Train Epoch: 338 [0/800 (0%)]\tLoss: 0.307059\n",
+      "====> Train Epoch: 338 Average loss: 0.3291\n",
+      "====> Test Epoch: 338 Average loss: 0.4608\n",
+      "Train Epoch: 339 [0/800 (0%)]\tLoss: 0.321857\n",
+      "====> Train Epoch: 339 Average loss: 0.3300\n",
+      "====> Test Epoch: 339 Average loss: 0.4152\n",
+      "Train Epoch: 340 [0/800 (0%)]\tLoss: 0.310734\n",
+      "====> Train Epoch: 340 Average loss: 0.3343\n",
+      "====> Test Epoch: 340 Average loss: 0.4410\n",
+      "Train Epoch: 341 [0/800 (0%)]\tLoss: 0.279672\n",
+      "====> Train Epoch: 341 Average loss: 0.3377\n",
+      "====> Test Epoch: 341 Average loss: 0.4697\n",
+      "Train Epoch: 342 [0/800 (0%)]\tLoss: 0.337047\n",
+      "====> Train Epoch: 342 Average loss: 0.3380\n",
+      "====> Test Epoch: 342 Average loss: 0.4208\n",
+      "Train Epoch: 343 [0/800 (0%)]\tLoss: 0.307215\n",
+      "====> Train Epoch: 343 Average loss: 0.3345\n",
+      "====> Test Epoch: 343 Average loss: 0.4338\n",
+      "Train Epoch: 344 [0/800 (0%)]\tLoss: 0.326842\n",
+      "====> Train Epoch: 344 Average loss: 0.3321\n",
+      "====> Test Epoch: 344 Average loss: 0.4025\n",
+      "Train Epoch: 345 [0/800 (0%)]\tLoss: 0.341801\n",
+      "====> Train Epoch: 345 Average loss: 0.3374\n",
+      "====> Test Epoch: 345 Average loss: 0.3962\n",
+      "Train Epoch: 346 [0/800 (0%)]\tLoss: 0.347197\n",
+      "====> Train Epoch: 346 Average loss: 0.3286\n",
+      "====> Test Epoch: 346 Average loss: 0.3871\n",
+      "Train Epoch: 347 [0/800 (0%)]\tLoss: 0.300998\n",
+      "====> Train Epoch: 347 Average loss: 0.3293\n",
+      "====> Test Epoch: 347 Average loss: 0.4133\n",
+      "Train Epoch: 348 [0/800 (0%)]\tLoss: 0.348177\n",
+      "====> Train Epoch: 348 Average loss: 0.3339\n",
+      "====> Test Epoch: 348 Average loss: 0.4325\n",
+      "Train Epoch: 349 [0/800 (0%)]\tLoss: 0.309043\n",
+      "====> Train Epoch: 349 Average loss: 0.3305\n",
+      "====> Test Epoch: 349 Average loss: 0.4534\n",
+      "Train Epoch: 350 [0/800 (0%)]\tLoss: 0.328488\n",
+      "====> Train Epoch: 350 Average loss: 0.3343\n",
+      "====> Test Epoch: 350 Average loss: 0.3967\n",
+      "Train Epoch: 351 [0/800 (0%)]\tLoss: 0.315321\n",
+      "====> Train Epoch: 351 Average loss: 0.3291\n",
+      "====> Test Epoch: 351 Average loss: 0.4052\n",
+      "Train Epoch: 352 [0/800 (0%)]\tLoss: 0.335394\n",
+      "====> Train Epoch: 352 Average loss: 0.3316\n",
+      "====> Test Epoch: 352 Average loss: 0.4063\n",
+      "Train Epoch: 353 [0/800 (0%)]\tLoss: 0.284462\n",
+      "====> Train Epoch: 353 Average loss: 0.3303\n",
+      "====> Test Epoch: 353 Average loss: 0.4389\n",
+      "Train Epoch: 354 [0/800 (0%)]\tLoss: 0.285787\n",
+      "====> Train Epoch: 354 Average loss: 0.3321\n",
+      "====> Test Epoch: 354 Average loss: 0.4097\n",
+      "Train Epoch: 355 [0/800 (0%)]\tLoss: 0.302833\n",
+      "====> Train Epoch: 355 Average loss: 0.3309\n",
+      "====> Test Epoch: 355 Average loss: 0.4290\n",
+      "Train Epoch: 356 [0/800 (0%)]\tLoss: 0.337092\n",
+      "====> Train Epoch: 356 Average loss: 0.3332\n",
+      "====> Test Epoch: 356 Average loss: 0.3972\n",
+      "Train Epoch: 357 [0/800 (0%)]\tLoss: 0.330725\n",
+      "====> Train Epoch: 357 Average loss: 0.3301\n",
+      "====> Test Epoch: 357 Average loss: 0.4276\n",
+      "Train Epoch: 358 [0/800 (0%)]\tLoss: 0.307993\n",
+      "====> Train Epoch: 358 Average loss: 0.3436\n",
+      "====> Test Epoch: 358 Average loss: 0.3978\n",
+      "Train Epoch: 359 [0/800 (0%)]\tLoss: 0.346117\n",
+      "====> Train Epoch: 359 Average loss: 0.3360\n",
+      "====> Test Epoch: 359 Average loss: 0.4206\n",
+      "Train Epoch: 360 [0/800 (0%)]\tLoss: 0.356067\n",
+      "====> Train Epoch: 360 Average loss: 0.3343\n",
+      "====> Test Epoch: 360 Average loss: 0.4169\n",
+      "Train Epoch: 361 [0/800 (0%)]\tLoss: 0.350705\n",
+      "====> Train Epoch: 361 Average loss: 0.3371\n",
+      "====> Test Epoch: 361 Average loss: 0.3994\n",
+      "Train Epoch: 362 [0/800 (0%)]\tLoss: 0.351215\n",
+      "====> Train Epoch: 362 Average loss: 0.3342\n",
+      "====> Test Epoch: 362 Average loss: 0.4148\n",
+      "Train Epoch: 363 [0/800 (0%)]\tLoss: 0.286418\n",
+      "====> Train Epoch: 363 Average loss: 0.3338\n",
+      "====> Test Epoch: 363 Average loss: 0.4186\n",
+      "Train Epoch: 364 [0/800 (0%)]\tLoss: 0.288507\n",
+      "====> Train Epoch: 364 Average loss: 0.3318\n",
+      "====> Test Epoch: 364 Average loss: 0.4451\n",
+      "Train Epoch: 365 [0/800 (0%)]\tLoss: 0.334312\n",
+      "====> Train Epoch: 365 Average loss: 0.3307\n",
+      "====> Test Epoch: 365 Average loss: 0.4014\n",
+      "Train Epoch: 366 [0/800 (0%)]\tLoss: 0.343201\n",
+      "====> Train Epoch: 366 Average loss: 0.3306\n",
+      "====> Test Epoch: 366 Average loss: 0.4413\n",
+      "Train Epoch: 367 [0/800 (0%)]\tLoss: 0.295437\n",
+      "====> Train Epoch: 367 Average loss: 0.3281\n",
+      "====> Test Epoch: 367 Average loss: 0.4113\n",
+      "Train Epoch: 368 [0/800 (0%)]\tLoss: 0.315285\n",
+      "====> Train Epoch: 368 Average loss: 0.3300\n",
+      "====> Test Epoch: 368 Average loss: 0.4243\n",
+      "Train Epoch: 369 [0/800 (0%)]\tLoss: 0.306689\n",
+      "====> Train Epoch: 369 Average loss: 0.3416\n",
+      "====> Test Epoch: 369 Average loss: 0.4039\n",
+      "Train Epoch: 370 [0/800 (0%)]\tLoss: 0.334016\n",
+      "====> Train Epoch: 370 Average loss: 0.3431\n",
+      "====> Test Epoch: 370 Average loss: 0.3866\n",
+      "Train Epoch: 371 [0/800 (0%)]\tLoss: 0.310103\n",
+      "====> Train Epoch: 371 Average loss: 0.3333\n",
+      "====> Test Epoch: 371 Average loss: 0.4259\n",
+      "Train Epoch: 372 [0/800 (0%)]\tLoss: 0.361169\n",
+      "====> Train Epoch: 372 Average loss: 0.3397\n",
+      "====> Test Epoch: 372 Average loss: 0.4412\n",
+      "Train Epoch: 373 [0/800 (0%)]\tLoss: 0.301764\n",
+      "====> Train Epoch: 373 Average loss: 0.3348\n",
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+      "Train Epoch: 374 [0/800 (0%)]\tLoss: 0.310320\n",
+      "====> Train Epoch: 374 Average loss: 0.3283\n",
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+      "Train Epoch: 375 [0/800 (0%)]\tLoss: 0.290700\n",
+      "====> Train Epoch: 375 Average loss: 0.3387\n",
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+      "Train Epoch: 376 [0/800 (0%)]\tLoss: 0.336341\n",
+      "====> Train Epoch: 376 Average loss: 0.3326\n",
+      "====> Test Epoch: 376 Average loss: 0.3879\n",
+      "Train Epoch: 377 [0/800 (0%)]\tLoss: 0.337496\n",
+      "====> Train Epoch: 377 Average loss: 0.3344\n",
+      "====> Test Epoch: 377 Average loss: 0.4621\n",
+      "Train Epoch: 378 [0/800 (0%)]\tLoss: 0.329568\n",
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+      "Train Epoch: 379 [0/800 (0%)]\tLoss: 0.293539\n",
+      "====> Train Epoch: 379 Average loss: 0.3295\n",
+      "====> Test Epoch: 379 Average loss: 0.4079\n",
+      "Train Epoch: 380 [0/800 (0%)]\tLoss: 0.315705\n",
+      "====> Train Epoch: 380 Average loss: 0.3351\n",
+      "====> Test Epoch: 380 Average loss: 0.4215\n",
+      "Train Epoch: 381 [0/800 (0%)]\tLoss: 0.303921\n",
+      "====> Train Epoch: 381 Average loss: 0.3366\n",
+      "====> Test Epoch: 381 Average loss: 0.3973\n",
+      "Train Epoch: 382 [0/800 (0%)]\tLoss: 0.318811\n",
+      "====> Train Epoch: 382 Average loss: 0.3345\n",
+      "====> Test Epoch: 382 Average loss: 0.4278\n",
+      "Train Epoch: 383 [0/800 (0%)]\tLoss: 0.363972\n",
+      "====> Train Epoch: 383 Average loss: 0.3310\n",
+      "====> Test Epoch: 383 Average loss: 0.4223\n",
+      "Train Epoch: 384 [0/800 (0%)]\tLoss: 0.306730\n",
+      "====> Train Epoch: 384 Average loss: 0.3291\n",
+      "====> Test Epoch: 384 Average loss: 0.4119\n",
+      "Train Epoch: 385 [0/800 (0%)]\tLoss: 0.262912\n",
+      "====> Train Epoch: 385 Average loss: 0.3303\n",
+      "====> Test Epoch: 385 Average loss: 0.4188\n",
+      "Train Epoch: 386 [0/800 (0%)]\tLoss: 0.293751\n",
+      "====> Train Epoch: 386 Average loss: 0.3358\n",
+      "====> Test Epoch: 386 Average loss: 0.4000\n",
+      "Train Epoch: 387 [0/800 (0%)]\tLoss: 0.308802\n",
+      "====> Train Epoch: 387 Average loss: 0.3389\n",
+      "====> Test Epoch: 387 Average loss: 0.4250\n",
+      "Train Epoch: 388 [0/800 (0%)]\tLoss: 0.303437\n",
+      "====> Train Epoch: 388 Average loss: 0.3389\n",
+      "====> Test Epoch: 388 Average loss: 0.4091\n",
+      "Train Epoch: 389 [0/800 (0%)]\tLoss: 0.335299\n",
+      "====> Train Epoch: 389 Average loss: 0.3536\n",
+      "====> Test Epoch: 389 Average loss: 0.4688\n",
+      "Train Epoch: 390 [0/800 (0%)]\tLoss: 0.299154\n",
+      "====> Train Epoch: 390 Average loss: 0.3450\n",
+      "====> Test Epoch: 390 Average loss: 0.4323\n",
+      "Train Epoch: 391 [0/800 (0%)]\tLoss: 0.328258\n",
+      "====> Train Epoch: 391 Average loss: 0.3340\n",
+      "====> Test Epoch: 391 Average loss: 0.4240\n",
+      "Train Epoch: 392 [0/800 (0%)]\tLoss: 0.341202\n",
+      "====> Train Epoch: 392 Average loss: 0.3361\n",
+      "====> Test Epoch: 392 Average loss: 0.4288\n",
+      "Train Epoch: 393 [0/800 (0%)]\tLoss: 0.322524\n",
+      "====> Train Epoch: 393 Average loss: 0.3392\n",
+      "====> Test Epoch: 393 Average loss: 0.4217\n",
+      "Train Epoch: 394 [0/800 (0%)]\tLoss: 0.289331\n",
+      "====> Train Epoch: 394 Average loss: 0.3352\n",
+      "====> Test Epoch: 394 Average loss: 0.4067\n",
+      "Train Epoch: 395 [0/800 (0%)]\tLoss: 0.285881\n",
+      "====> Train Epoch: 395 Average loss: 0.3308\n",
+      "====> Test Epoch: 395 Average loss: 0.3786\n",
+      "Train Epoch: 396 [0/800 (0%)]\tLoss: 0.315578\n",
+      "====> Train Epoch: 396 Average loss: 0.3303\n",
+      "====> Test Epoch: 396 Average loss: 0.4313\n",
+      "Train Epoch: 397 [0/800 (0%)]\tLoss: 0.285900\n",
+      "====> Train Epoch: 397 Average loss: 0.3291\n",
+      "====> Test Epoch: 397 Average loss: 0.4074\n",
+      "Train Epoch: 398 [0/800 (0%)]\tLoss: 0.317220\n",
+      "====> Train Epoch: 398 Average loss: 0.3356\n",
+      "====> Test Epoch: 398 Average loss: 0.4151\n",
+      "Train Epoch: 399 [0/800 (0%)]\tLoss: 0.297941\n",
+      "====> Train Epoch: 399 Average loss: 0.3319\n",
+      "====> Test Epoch: 399 Average loss: 0.3805\n",
+      "Train Epoch: 400 [0/800 (0%)]\tLoss: 0.283515\n",
+      "====> Train Epoch: 400 Average loss: 0.3391\n",
+      "====> Test Epoch: 400 Average loss: 0.3854\n",
+      "Train Epoch: 401 [0/800 (0%)]\tLoss: 0.286378\n",
+      "====> Train Epoch: 401 Average loss: 0.3375\n",
+      "====> Test Epoch: 401 Average loss: 0.4315\n",
+      "Train Epoch: 402 [0/800 (0%)]\tLoss: 0.298358\n",
+      "====> Train Epoch: 402 Average loss: 0.3307\n",
+      "====> Test Epoch: 402 Average loss: 0.3764\n",
+      "Train Epoch: 403 [0/800 (0%)]\tLoss: 0.327767\n",
+      "====> Train Epoch: 403 Average loss: 0.3285\n",
+      "====> Test Epoch: 403 Average loss: 0.4075\n",
+      "Train Epoch: 404 [0/800 (0%)]\tLoss: 0.346063\n",
+      "====> Train Epoch: 404 Average loss: 0.3292\n",
+      "====> Test Epoch: 404 Average loss: 0.4632\n",
+      "Train Epoch: 405 [0/800 (0%)]\tLoss: 0.281409\n",
+      "====> Train Epoch: 405 Average loss: 0.3304\n",
+      "====> Test Epoch: 405 Average loss: 0.4197\n",
+      "Train Epoch: 406 [0/800 (0%)]\tLoss: 0.327079\n",
+      "====> Train Epoch: 406 Average loss: 0.3291\n",
+      "====> Test Epoch: 406 Average loss: 0.4060\n",
+      "Train Epoch: 407 [0/800 (0%)]\tLoss: 0.295730\n",
+      "====> Train Epoch: 407 Average loss: 0.3353\n",
+      "====> Test Epoch: 407 Average loss: 0.4439\n",
+      "Train Epoch: 408 [0/800 (0%)]\tLoss: 0.288089\n",
+      "====> Train Epoch: 408 Average loss: 0.3311\n",
+      "====> Test Epoch: 408 Average loss: 0.4464\n",
+      "Train Epoch: 409 [0/800 (0%)]\tLoss: 0.344026\n",
+      "====> Train Epoch: 409 Average loss: 0.3271\n",
+      "====> Test Epoch: 409 Average loss: 0.4570\n",
+      "Train Epoch: 410 [0/800 (0%)]\tLoss: 0.320497\n",
+      "====> Train Epoch: 410 Average loss: 0.3288\n",
+      "====> Test Epoch: 410 Average loss: 0.4227\n",
+      "Train Epoch: 411 [0/800 (0%)]\tLoss: 0.348150\n",
+      "====> Train Epoch: 411 Average loss: 0.3281\n",
+      "====> Test Epoch: 411 Average loss: 0.3876\n",
+      "Train Epoch: 412 [0/800 (0%)]\tLoss: 0.342558\n",
+      "====> Train Epoch: 412 Average loss: 0.3262\n",
+      "====> Test Epoch: 412 Average loss: 0.4094\n",
+      "Train Epoch: 413 [0/800 (0%)]\tLoss: 0.303100\n",
+      "====> Train Epoch: 413 Average loss: 0.3273\n",
+      "====> Test Epoch: 413 Average loss: 0.4252\n",
+      "Train Epoch: 414 [0/800 (0%)]\tLoss: 0.357713\n",
+      "====> Train Epoch: 414 Average loss: 0.3325\n",
+      "====> Test Epoch: 414 Average loss: 0.4520\n",
+      "Train Epoch: 415 [0/800 (0%)]\tLoss: 0.329182\n",
+      "====> Train Epoch: 415 Average loss: 0.3359\n",
+      "====> Test Epoch: 415 Average loss: 0.3983\n",
+      "Train Epoch: 416 [0/800 (0%)]\tLoss: 0.341245\n",
+      "====> Train Epoch: 416 Average loss: 0.3343\n",
+      "====> Test Epoch: 416 Average loss: 0.4107\n",
+      "Train Epoch: 417 [0/800 (0%)]\tLoss: 0.305917\n",
+      "====> Train Epoch: 417 Average loss: 0.3343\n",
+      "====> Test Epoch: 417 Average loss: 0.4111\n",
+      "Train Epoch: 418 [0/800 (0%)]\tLoss: 0.341696\n",
+      "====> Train Epoch: 418 Average loss: 0.3311\n",
+      "====> Test Epoch: 418 Average loss: 0.4375\n",
+      "Train Epoch: 419 [0/800 (0%)]\tLoss: 0.316266\n",
+      "====> Train Epoch: 419 Average loss: 0.3305\n",
+      "====> Test Epoch: 419 Average loss: 0.3989\n",
+      "Train Epoch: 420 [0/800 (0%)]\tLoss: 0.299821\n",
+      "====> Train Epoch: 420 Average loss: 0.3313\n",
+      "====> Test Epoch: 420 Average loss: 0.4100\n",
+      "Train Epoch: 421 [0/800 (0%)]\tLoss: 0.311232\n",
+      "====> Train Epoch: 421 Average loss: 0.3326\n",
+      "====> Test Epoch: 421 Average loss: 0.3979\n",
+      "Train Epoch: 422 [0/800 (0%)]\tLoss: 0.304882\n",
+      "====> Train Epoch: 422 Average loss: 0.3326\n",
+      "====> Test Epoch: 422 Average loss: 0.4510\n",
+      "Train Epoch: 423 [0/800 (0%)]\tLoss: 0.359913\n",
+      "====> Train Epoch: 423 Average loss: 0.3393\n",
+      "====> Test Epoch: 423 Average loss: 0.3944\n",
+      "Train Epoch: 424 [0/800 (0%)]\tLoss: 0.297654\n",
+      "====> Train Epoch: 424 Average loss: 0.3307\n",
+      "====> Test Epoch: 424 Average loss: 0.4376\n",
+      "Train Epoch: 425 [0/800 (0%)]\tLoss: 0.334163\n",
+      "====> Train Epoch: 425 Average loss: 0.3355\n",
+      "====> Test Epoch: 425 Average loss: 0.4149\n",
+      "Train Epoch: 426 [0/800 (0%)]\tLoss: 0.266352\n",
+      "====> Train Epoch: 426 Average loss: 0.3294\n",
+      "====> Test Epoch: 426 Average loss: 0.3953\n",
+      "Train Epoch: 427 [0/800 (0%)]\tLoss: 0.292960\n",
+      "====> Train Epoch: 427 Average loss: 0.3348\n",
+      "====> Test Epoch: 427 Average loss: 0.4609\n",
+      "Train Epoch: 428 [0/800 (0%)]\tLoss: 0.310400\n",
+      "====> Train Epoch: 428 Average loss: 0.3345\n",
+      "====> Test Epoch: 428 Average loss: 0.4420\n",
+      "Train Epoch: 429 [0/800 (0%)]\tLoss: 0.309425\n",
+      "====> Train Epoch: 429 Average loss: 0.3306\n",
+      "====> Test Epoch: 429 Average loss: 0.4613\n",
+      "Train Epoch: 430 [0/800 (0%)]\tLoss: 0.299877\n",
+      "====> Train Epoch: 430 Average loss: 0.3328\n",
+      "====> Test Epoch: 430 Average loss: 0.4410\n",
+      "Train Epoch: 431 [0/800 (0%)]\tLoss: 0.302383\n",
+      "====> Train Epoch: 431 Average loss: 0.3332\n",
+      "====> Test Epoch: 431 Average loss: 0.4263\n",
+      "Train Epoch: 432 [0/800 (0%)]\tLoss: 0.306035\n",
+      "====> Train Epoch: 432 Average loss: 0.3294\n",
+      "====> Test Epoch: 432 Average loss: 0.4537\n",
+      "Train Epoch: 433 [0/800 (0%)]\tLoss: 0.263938\n",
+      "====> Train Epoch: 433 Average loss: 0.3295\n",
+      "====> Test Epoch: 433 Average loss: 0.3996\n",
+      "Train Epoch: 434 [0/800 (0%)]\tLoss: 0.285378\n",
+      "====> Train Epoch: 434 Average loss: 0.3306\n",
+      "====> Test Epoch: 434 Average loss: 0.3859\n",
+      "Train Epoch: 435 [0/800 (0%)]\tLoss: 0.307526\n",
+      "====> Train Epoch: 435 Average loss: 0.3319\n",
+      "====> Test Epoch: 435 Average loss: 0.4259\n",
+      "Train Epoch: 436 [0/800 (0%)]\tLoss: 0.315348\n",
+      "====> Train Epoch: 436 Average loss: 0.3293\n",
+      "====> Test Epoch: 436 Average loss: 0.3799\n",
+      "Train Epoch: 437 [0/800 (0%)]\tLoss: 0.285385\n",
+      "====> Train Epoch: 437 Average loss: 0.3266\n",
+      "====> Test Epoch: 437 Average loss: 0.4479\n",
+      "Train Epoch: 438 [0/800 (0%)]\tLoss: 0.310536\n",
+      "====> Train Epoch: 438 Average loss: 0.3297\n",
+      "====> Test Epoch: 438 Average loss: 0.4154\n",
+      "Train Epoch: 439 [0/800 (0%)]\tLoss: 0.315510\n",
+      "====> Train Epoch: 439 Average loss: 0.3286\n",
+      "====> Test Epoch: 439 Average loss: 0.4498\n",
+      "Train Epoch: 440 [0/800 (0%)]\tLoss: 0.344934\n",
+      "====> Train Epoch: 440 Average loss: 0.3446\n",
+      "====> Test Epoch: 440 Average loss: 0.4166\n",
+      "Train Epoch: 441 [0/800 (0%)]\tLoss: 0.304907\n",
+      "====> Train Epoch: 441 Average loss: 0.3331\n",
+      "====> Test Epoch: 441 Average loss: 0.4133\n",
+      "Train Epoch: 442 [0/800 (0%)]\tLoss: 0.337056\n",
+      "====> Train Epoch: 442 Average loss: 0.3300\n",
+      "====> Test Epoch: 442 Average loss: 0.4585\n",
+      "Train Epoch: 443 [0/800 (0%)]\tLoss: 0.377294\n",
+      "====> Train Epoch: 443 Average loss: 0.3345\n",
+      "====> Test Epoch: 443 Average loss: 0.4174\n",
+      "Train Epoch: 444 [0/800 (0%)]\tLoss: 0.290419\n",
+      "====> Train Epoch: 444 Average loss: 0.3343\n",
+      "====> Test Epoch: 444 Average loss: 0.4455\n",
+      "Train Epoch: 445 [0/800 (0%)]\tLoss: 0.355932\n",
+      "====> Train Epoch: 445 Average loss: 0.3301\n",
+      "====> Test Epoch: 445 Average loss: 0.4050\n",
+      "Train Epoch: 446 [0/800 (0%)]\tLoss: 0.281759\n",
+      "====> Train Epoch: 446 Average loss: 0.3320\n",
+      "====> Test Epoch: 446 Average loss: 0.4121\n",
+      "Train Epoch: 447 [0/800 (0%)]\tLoss: 0.302326\n",
+      "====> Train Epoch: 447 Average loss: 0.3277\n",
+      "====> Test Epoch: 447 Average loss: 0.3842\n",
+      "Train Epoch: 448 [0/800 (0%)]\tLoss: 0.271311\n",
+      "====> Train Epoch: 448 Average loss: 0.3310\n",
+      "====> Test Epoch: 448 Average loss: 0.4225\n",
+      "Train Epoch: 449 [0/800 (0%)]\tLoss: 0.328627\n",
+      "====> Train Epoch: 449 Average loss: 0.3313\n",
+      "====> Test Epoch: 449 Average loss: 0.4406\n",
+      "Train Epoch: 450 [0/800 (0%)]\tLoss: 0.317599\n",
+      "====> Train Epoch: 450 Average loss: 0.3305\n",
+      "====> Test Epoch: 450 Average loss: 0.3650\n",
+      "Train Epoch: 451 [0/800 (0%)]\tLoss: 0.342773\n",
+      "====> Train Epoch: 451 Average loss: 0.3307\n",
+      "====> Test Epoch: 451 Average loss: 0.4025\n",
+      "Train Epoch: 452 [0/800 (0%)]\tLoss: 0.299045\n",
+      "====> Train Epoch: 452 Average loss: 0.3284\n",
+      "====> Test Epoch: 452 Average loss: 0.4259\n",
+      "Train Epoch: 453 [0/800 (0%)]\tLoss: 0.321818\n",
+      "====> Train Epoch: 453 Average loss: 0.3288\n",
+      "====> Test Epoch: 453 Average loss: 0.3996\n",
+      "Train Epoch: 454 [0/800 (0%)]\tLoss: 0.296154\n",
+      "====> Train Epoch: 454 Average loss: 0.3308\n",
+      "====> Test Epoch: 454 Average loss: 0.4309\n",
+      "Train Epoch: 455 [0/800 (0%)]\tLoss: 0.324190\n",
+      "====> Train Epoch: 455 Average loss: 0.3293\n",
+      "====> Test Epoch: 455 Average loss: 0.3855\n",
+      "Train Epoch: 456 [0/800 (0%)]\tLoss: 0.304105\n",
+      "====> Train Epoch: 456 Average loss: 0.3285\n",
+      "====> Test Epoch: 456 Average loss: 0.4241\n",
+      "Train Epoch: 457 [0/800 (0%)]\tLoss: 0.307249\n",
+      "====> Train Epoch: 457 Average loss: 0.3282\n",
+      "====> Test Epoch: 457 Average loss: 0.4169\n",
+      "Train Epoch: 458 [0/800 (0%)]\tLoss: 0.312528\n",
+      "====> Train Epoch: 458 Average loss: 0.3302\n",
+      "====> Test Epoch: 458 Average loss: 0.3975\n",
+      "Train Epoch: 459 [0/800 (0%)]\tLoss: 0.305962\n",
+      "====> Train Epoch: 459 Average loss: 0.3334\n",
+      "====> Test Epoch: 459 Average loss: 0.4435\n",
+      "Train Epoch: 460 [0/800 (0%)]\tLoss: 0.357999\n",
+      "====> Train Epoch: 460 Average loss: 0.3325\n",
+      "====> Test Epoch: 460 Average loss: 0.3893\n",
+      "Train Epoch: 461 [0/800 (0%)]\tLoss: 0.306467\n",
+      "====> Train Epoch: 461 Average loss: 0.3340\n",
+      "====> Test Epoch: 461 Average loss: 0.4215\n",
+      "Train Epoch: 462 [0/800 (0%)]\tLoss: 0.323375\n",
+      "====> Train Epoch: 462 Average loss: 0.3350\n",
+      "====> Test Epoch: 462 Average loss: 0.4246\n",
+      "Train Epoch: 463 [0/800 (0%)]\tLoss: 0.326692\n",
+      "====> Train Epoch: 463 Average loss: 0.3262\n",
+      "====> Test Epoch: 463 Average loss: 0.4005\n",
+      "Train Epoch: 464 [0/800 (0%)]\tLoss: 0.354387\n",
+      "====> Train Epoch: 464 Average loss: 0.3280\n",
+      "====> Test Epoch: 464 Average loss: 0.4259\n",
+      "Train Epoch: 465 [0/800 (0%)]\tLoss: 0.354573\n",
+      "====> Train Epoch: 465 Average loss: 0.3393\n",
+      "====> Test Epoch: 465 Average loss: 0.4147\n",
+      "Train Epoch: 466 [0/800 (0%)]\tLoss: 0.303800\n",
+      "====> Train Epoch: 466 Average loss: 0.3412\n",
+      "====> Test Epoch: 466 Average loss: 0.4573\n",
+      "Train Epoch: 467 [0/800 (0%)]\tLoss: 0.382437\n",
+      "====> Train Epoch: 467 Average loss: 0.3368\n",
+      "====> Test Epoch: 467 Average loss: 0.4339\n",
+      "Train Epoch: 468 [0/800 (0%)]\tLoss: 0.307622\n",
+      "====> Train Epoch: 468 Average loss: 0.3284\n",
+      "====> Test Epoch: 468 Average loss: 0.4097\n",
+      "Train Epoch: 469 [0/800 (0%)]\tLoss: 0.293374\n",
+      "====> Train Epoch: 469 Average loss: 0.3305\n",
+      "====> Test Epoch: 469 Average loss: 0.4191\n",
+      "Train Epoch: 470 [0/800 (0%)]\tLoss: 0.306203\n",
+      "====> Train Epoch: 470 Average loss: 0.3338\n",
+      "====> Test Epoch: 470 Average loss: 0.4223\n",
+      "Train Epoch: 471 [0/800 (0%)]\tLoss: 0.337388\n",
+      "====> Train Epoch: 471 Average loss: 0.3326\n",
+      "====> Test Epoch: 471 Average loss: 0.3999\n",
+      "Train Epoch: 472 [0/800 (0%)]\tLoss: 0.314001\n",
+      "====> Train Epoch: 472 Average loss: 0.3311\n",
+      "====> Test Epoch: 472 Average loss: 0.4319\n",
+      "Train Epoch: 473 [0/800 (0%)]\tLoss: 0.339449\n",
+      "====> Train Epoch: 473 Average loss: 0.3259\n",
+      "====> Test Epoch: 473 Average loss: 0.4413\n",
+      "Train Epoch: 474 [0/800 (0%)]\tLoss: 0.370001\n",
+      "====> Train Epoch: 474 Average loss: 0.3315\n",
+      "====> Test Epoch: 474 Average loss: 0.4141\n",
+      "Train Epoch: 475 [0/800 (0%)]\tLoss: 0.354314\n",
+      "====> Train Epoch: 475 Average loss: 0.3328\n",
+      "====> Test Epoch: 475 Average loss: 0.4293\n",
+      "Train Epoch: 476 [0/800 (0%)]\tLoss: 0.308028\n",
+      "====> Train Epoch: 476 Average loss: 0.3351\n",
+      "====> Test Epoch: 476 Average loss: 0.4333\n",
+      "Train Epoch: 477 [0/800 (0%)]\tLoss: 0.309831\n",
+      "====> Train Epoch: 477 Average loss: 0.3370\n",
+      "====> Test Epoch: 477 Average loss: 0.4018\n",
+      "Train Epoch: 478 [0/800 (0%)]\tLoss: 0.314408\n",
+      "====> Train Epoch: 478 Average loss: 0.3291\n",
+      "====> Test Epoch: 478 Average loss: 0.4390\n",
+      "Train Epoch: 479 [0/800 (0%)]\tLoss: 0.308332\n",
+      "====> Train Epoch: 479 Average loss: 0.3267\n",
+      "====> Test Epoch: 479 Average loss: 0.3957\n",
+      "Train Epoch: 480 [0/800 (0%)]\tLoss: 0.322499\n",
+      "====> Train Epoch: 480 Average loss: 0.3300\n",
+      "====> Test Epoch: 480 Average loss: 0.3739\n",
+      "Train Epoch: 481 [0/800 (0%)]\tLoss: 0.288729\n",
+      "====> Train Epoch: 481 Average loss: 0.3260\n",
+      "====> Test Epoch: 481 Average loss: 0.4330\n",
+      "Train Epoch: 482 [0/800 (0%)]\tLoss: 0.329343\n",
+      "====> Train Epoch: 482 Average loss: 0.3327\n",
+      "====> Test Epoch: 482 Average loss: 0.4121\n",
+      "Train Epoch: 483 [0/800 (0%)]\tLoss: 0.306637\n",
+      "====> Train Epoch: 483 Average loss: 0.3350\n",
+      "====> Test Epoch: 483 Average loss: 0.4438\n",
+      "Train Epoch: 484 [0/800 (0%)]\tLoss: 0.286781\n",
+      "====> Train Epoch: 484 Average loss: 0.3323\n",
+      "====> Test Epoch: 484 Average loss: 0.4280\n",
+      "Train Epoch: 485 [0/800 (0%)]\tLoss: 0.304832\n",
+      "====> Train Epoch: 485 Average loss: 0.3328\n",
+      "====> Test Epoch: 485 Average loss: 0.4156\n",
+      "Train Epoch: 486 [0/800 (0%)]\tLoss: 0.308274\n",
+      "====> Train Epoch: 486 Average loss: 0.3336\n",
+      "====> Test Epoch: 486 Average loss: 0.4549\n",
+      "Train Epoch: 487 [0/800 (0%)]\tLoss: 0.320666\n",
+      "====> Train Epoch: 487 Average loss: 0.3406\n",
+      "====> Test Epoch: 487 Average loss: 0.4086\n",
+      "Train Epoch: 488 [0/800 (0%)]\tLoss: 0.295135\n",
+      "====> Train Epoch: 488 Average loss: 0.3407\n",
+      "====> Test Epoch: 488 Average loss: 0.4365\n",
+      "Train Epoch: 489 [0/800 (0%)]\tLoss: 0.331129\n",
+      "====> Train Epoch: 489 Average loss: 0.3370\n",
+      "====> Test Epoch: 489 Average loss: 0.3875\n",
+      "Train Epoch: 490 [0/800 (0%)]\tLoss: 0.319115\n",
+      "====> Train Epoch: 490 Average loss: 0.3298\n",
+      "====> Test Epoch: 490 Average loss: 0.4059\n",
+      "Train Epoch: 491 [0/800 (0%)]\tLoss: 0.333036\n",
+      "====> Train Epoch: 491 Average loss: 0.3308\n",
+      "====> Test Epoch: 491 Average loss: 0.4339\n",
+      "Train Epoch: 492 [0/800 (0%)]\tLoss: 0.320206\n",
+      "====> Train Epoch: 492 Average loss: 0.3290\n",
+      "====> Test Epoch: 492 Average loss: 0.4417\n",
+      "Train Epoch: 493 [0/800 (0%)]\tLoss: 0.292040\n",
+      "====> Train Epoch: 493 Average loss: 0.3346\n",
+      "====> Test Epoch: 493 Average loss: 0.4089\n",
+      "Train Epoch: 494 [0/800 (0%)]\tLoss: 0.298197\n",
+      "====> Train Epoch: 494 Average loss: 0.3320\n",
+      "====> Test Epoch: 494 Average loss: 0.4325\n",
+      "Train Epoch: 495 [0/800 (0%)]\tLoss: 0.325547\n",
+      "====> Train Epoch: 495 Average loss: 0.3355\n",
+      "====> Test Epoch: 495 Average loss: 0.4352\n",
+      "Train Epoch: 496 [0/800 (0%)]\tLoss: 0.310787\n",
+      "====> Train Epoch: 496 Average loss: 0.3273\n",
+      "====> Test Epoch: 496 Average loss: 0.4133\n",
+      "Train Epoch: 497 [0/800 (0%)]\tLoss: 0.292689\n",
+      "====> Train Epoch: 497 Average loss: 0.3272\n",
+      "====> Test Epoch: 497 Average loss: 0.4040\n",
+      "Train Epoch: 498 [0/800 (0%)]\tLoss: 0.305203\n",
+      "====> Train Epoch: 498 Average loss: 0.3256\n",
+      "====> Test Epoch: 498 Average loss: 0.4090\n",
+      "Train Epoch: 499 [0/800 (0%)]\tLoss: 0.302636\n",
+      "====> Train Epoch: 499 Average loss: 0.3276\n",
+      "====> Test Epoch: 499 Average loss: 0.4244\n",
+      "Train Epoch: 500 [0/800 (0%)]\tLoss: 0.308832\n",
+      "====> Train Epoch: 500 Average loss: 0.3286\n",
+      "====> Test Epoch: 500 Average loss: 0.3816\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-4 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-4 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-4 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-4 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-4 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=3, topology=&#x27;circle&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ImmersionEstimator<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=3, topology=&#x27;circle&#x27;)</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "ImmersionEstimator(device='cuda', extrinsic_dim=3, topology='circle')"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "immersion_estimator.fit(X, labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "immersion = immersion_estimator.estimate_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "\n",
+    "intrinsic_coords = torch.tensor(intrinsic_coords, device=device)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "recon_points = immersion(intrinsic_coords).detach().cpu().numpy().squeeze()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "marker": {
+          "size": 3
+         },
+         "mode": "markers",
+         "scene": "scene",
+         "type": "scatter3d",
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('a4cb67c1-7f83-4b74-aa21-f5cc03275aec');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.graph_objects as go\n",
+    "from plotly.subplots import make_subplots\n",
+    "\n",
+    "# plot manifold points in 3d and recon points in 3d in separate subplots\n",
+    "\n",
+    "fig = make_subplots(\n",
+    "    rows=1, cols=2, specs=[[{\"type\": \"scatter3d\"}, {\"type\": \"scatter3d\"}]]\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=manifold_points[:, 0],\n",
+    "        y=manifold_points[:, 1],\n",
+    "        z=manifold_points[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=1,\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=recon_points[:, 0],\n",
+    "        y=recon_points[:, 1],\n",
+    "        z=recon_points[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=2,\n",
+    ")\n",
+    "\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "neurometry",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From fe16028a870575cf264b0cbfa353ab208ccb513a Mon Sep 17 00:00:00 2001
From: franciscoeacosta <facosta@ucsb.edu>
Date: Sun, 22 Sep 2024 02:40:53 -0700
Subject: [PATCH 4/6] implement ablated immersion estimator, reorg tutorials

---
 .../geometry/immersion_estimator.py           |   151 +-
 .../estimators/geometry/metric_estimator.py   |    32 +-
 .../estimators/geometry/models/losses.py      |     1 -
 .../geometry/models/spherical_vae.py          |     1 -
 .../geometry/models/train_config.py           |     6 +-
 ...4_methods_estimate_manifold_geometry.ipynb | 52554 ++++++++--------
 ..._methods_estimate_manifold_immersion.ipynb |  9026 ---
 ...nb => 05_analyze_task_optimized_rnn.ipynb} |    50 +-
 ...ipynb => 06_analyze_digital_twin_V4.ipynb} |     2 +-
 .../07_analyze_electrophys_hippocampus.ipynb  |    25 +
 .../04_explore_hyperbolic_geometry.ipynb      |     0
 ...4_methods_estimate_manifold_geometry.ipynb | 29839 +++++++++
 .../05_explore_diffeomorphisms_of_space.ipynb |     0
 .../06_application_synthetic_v1.ipynb         |     0
 .../071_application_dual_agent_rnns.ipynb     |     0
 .../07_application_rnns_grid_cells.ipynb      |     0
 ...08_applications_synthetic_grid_cells.ipynb |     0
 ..._methods_estimate_manifold_curvature.ipynb |     0
 tutorials/{ => move}/11_visualize_rnn.ipynb   |     0
 tutorials/{ => move}/plot_klein_bottle.py     |     0
 tutorials/{ => old_curvature}/load_runs.py    |     0
 21 files changed, 55084 insertions(+), 36603 deletions(-)
 delete mode 100644 tutorials/04_methods_estimate_manifold_immersion.ipynb
 rename tutorials/{09_application_rnns_grid_cells_xu.ipynb => 05_analyze_task_optimized_rnn.ipynb} (99%)
 rename tutorials/{12_application_digitaltwin_v4.ipynb => 06_analyze_digital_twin_V4.ipynb} (99%)
 create mode 100644 tutorials/07_analyze_electrophys_hippocampus.ipynb
 rename tutorials/{ => move}/04_explore_hyperbolic_geometry.ipynb (100%)
 create mode 100644 tutorials/move/04_methods_estimate_manifold_geometry.ipynb
 rename tutorials/{ => move}/05_explore_diffeomorphisms_of_space.ipynb (100%)
 rename tutorials/{ => move}/06_application_synthetic_v1.ipynb (100%)
 rename tutorials/{ => move}/071_application_dual_agent_rnns.ipynb (100%)
 rename tutorials/{ => move}/07_application_rnns_grid_cells.ipynb (100%)
 rename tutorials/{ => move}/08_applications_synthetic_grid_cells.ipynb (100%)
 rename tutorials/{ => move}/10_methods_estimate_manifold_curvature.ipynb (100%)
 rename tutorials/{ => move}/11_visualize_rnn.ipynb (100%)
 rename tutorials/{ => move}/plot_klein_bottle.py (100%)
 rename tutorials/{ => old_curvature}/load_runs.py (100%)

diff --git a/neurometry/estimators/geometry/immersion_estimator.py b/neurometry/estimators/geometry/immersion_estimator.py
index a8efba4..7272276 100644
--- a/neurometry/estimators/geometry/immersion_estimator.py
+++ b/neurometry/estimators/geometry/immersion_estimator.py
@@ -3,57 +3,49 @@
 os.environ["GEOMSTATS_BACKEND"] = "pytorch"
 import geomstats.backend as gs
 import torch
+import torch.optim as optim
 from sklearn.base import BaseEstimator
 from sklearn.model_selection import train_test_split
 from torch.utils.data import DataLoader, TensorDataset
 
 import neurometry.estimators.geometry.models.train_config as train_config
-from neurometry.estimators.geometry.models.spherical_vae import SphericalVAE
-from neurometry.estimators.geometry.models.toroidal_vae import ToroidalVAE
-from neurometry.estimators.geometry.models.train import train_test
 
 
 class ImmersionEstimator(BaseEstimator):
-    def __init__(self, extrinsic_dim, topology, device):
+    def __init__(self, extrinsic_dim, topology, device, verbose=False):
         self.estimate_ = None
+        self.verbose = verbose
         self.device = device
         self.extrinsic_dim = extrinsic_dim
         self.topology = topology
-        self.latent_dims = {"circle": 2, "sphere": 3, "torus": 3}
+        self.latent_dims = {"circle": 2, "sphere": 3, "torus": 4}
         self.model = self._get_model()
 
     def _get_model(self):
-        if self.topology == "circle" or self.topology == "sphere":
-            return SphericalVAE(
-                extrinsic_dim=self.extrinsic_dim,
-                latent_dim=self.latent_dims[self.topology],
-            ).to(self.device)
-        if self.topology == "torus":
-            return ToroidalVAE(
-                extrinsic_dim=self.extrinsic_dim,
-                latent_dim=self.latent_dims[self.topology],
-            ).to(self.device)
-        raise ValueError("Topology not supported")
+        return NeuralEmbedding(
+            latent_dim=self.latent_dims[self.topology], extrinsic_dim=self.extrinsic_dim
+        ).to(self.device)
 
-    def _intrinsic_to_extrinsic(self):
+    def intrinsic_to_extrinsic(self, x):
         if self.topology == "circle":
-            return lambda x: gs.array([gs.cos(x), gs.sin(x)])
+            return gs.array([gs.cos(x), gs.sin(x)]).T
         if self.topology == "sphere":
-            return lambda x: gs.array(
+            return gs.array(
                 [
-                    gs.sin(x[0]) * gs.cos(x[1]),
-                    gs.sin(x[0]) * gs.sin(x[1]),
-                    gs.cos(x[0]),
+                    gs.sin(x[:, 0]) * gs.cos(x[:, 1]),
+                    gs.sin(x[:, 0]) * gs.sin(x[:, 1]),
+                    gs.cos(x[:, 0]),
                 ]
-            )
+            ).T
         if self.topology == "torus":
-            return lambda x: gs.array(
+            return gs.array(
                 [
-                    (1 - gs.cos(x[0])) * gs.cos(x[1]),
-                    (1 - gs.cos(x[0])) * gs.sin(x[1]),
-                    gs.sin(x[0]),
+                    gs.cos(x[:, 0]),
+                    gs.sin(x[:, 0]),
+                    gs.cos(x[:, 1]),
+                    gs.sin(x[:, 1]),
                 ]
-            )
+            ).T
         raise ValueError("Topology not supported")
 
     def fit(self, X, y=None):
@@ -73,20 +65,99 @@ def fit(self, X, y=None):
             shuffle=True,
         )
 
-        optimizer = torch.optim.Adam(
-            self.model.parameters(), lr=train_config.lr, amsgrad=True
-        )
-        train_losses, test_losses, best_model = train_test(
-            model=self.model,
-            train_loader=train_loader,
-            test_loader=test_loader,
-            optimizer=optimizer,
-            scheduler=None,
-            config=train_config,
+        trainer = Trainer(
+            self.model,
+            train_loader,
+            test_loader,
+            criterion=torch.nn.MSELoss(),
+            learning_rate=train_config.lr,
+            scheduler=False,
+            verbose=self.verbose,
         )
+        trainer.train(train_config.num_epochs)
+
+        self.trainer = trainer
 
-        self.estimate_ = lambda task_variable: best_model.decode(
-            self._intrinsic_to_extrinsic()(task_variable).T
+        self.model.eval()
+        self.estimate_ = lambda task_variable: self.model(
+            self.intrinsic_to_extrinsic(task_variable)
         )
 
         return self
+
+
+class NeuralEmbedding(torch.nn.Module):
+    def __init__(
+        self, latent_dim, extrinsic_dim, hidden_dims=64, num_hidden=4, sft_beta=4.5
+    ):
+        super().__init__()
+
+        self.fc1 = torch.nn.Linear(latent_dim, hidden_dims)
+        self.fc_hidden = torch.nn.ModuleList(
+            [torch.nn.Linear(hidden_dims, hidden_dims) for _ in range(num_hidden)]
+        )
+        self.fc_output = torch.nn.Linear(hidden_dims, extrinsic_dim)
+        self.softplus = torch.nn.Softplus(beta=sft_beta)
+
+    def forward(self, x):
+        h = self.softplus(self.fc1(x))
+        for fc in self.fc_hidden:
+            h = self.softplus(fc(h))
+        return self.fc_output(h)
+
+
+class Trainer:
+    def __init__(
+        self,
+        model,
+        train_loader,
+        test_loader,
+        criterion,
+        learning_rate,
+        scheduler=False,
+        verbose=False,
+    ):
+        self.model = model
+        self.train_loader = train_loader
+        self.test_loader = test_loader
+        self.criterion = criterion
+        self.optimizer = optim.Adam(model.parameters(), lr=learning_rate)
+        if scheduler:
+            self.scheduler = optim.lr_scheduler.StepLR(
+                self.optimizer, step_size=10, gamma=0.1
+            )
+        self.verbose = verbose
+
+    def train(self, num_epochs=10):
+        train_losses = []
+        test_losses = []
+        for epoch in range(num_epochs):
+            self.model.train()
+            train_loss = 0.0
+            for inputs, targets in self.train_loader:
+                self.optimizer.zero_grad()
+                outputs = self.model(inputs)
+                loss = self.criterion(outputs, targets)
+                loss.backward()
+                self.optimizer.step()
+                train_loss += loss.item()
+            avg_train_loss = train_loss / len(self.train_loader)
+            train_losses.append(avg_train_loss)
+            avg_test_loss = self.evaluate()
+            test_losses.append(avg_test_loss)
+            if self.verbose:
+                print(
+                    f"Epoch {epoch+1}/{num_epochs}, Train Loss: {avg_train_loss}, Test Loss: {avg_test_loss}"
+                )
+        self.train_losses = train_losses
+        self.test_losses = test_losses
+
+    def evaluate(self):
+        self.model.eval()
+        test_loss = 0.0
+        with torch.no_grad():
+            for inputs, targets in self.test_loader:
+                outputs = self.model(inputs)
+                loss = self.criterion(outputs, targets)
+                test_loss += loss.item()
+        return test_loss / len(self.test_loader)
diff --git a/neurometry/estimators/geometry/metric_estimator.py b/neurometry/estimators/geometry/metric_estimator.py
index e4cd230..cc1d5be 100644
--- a/neurometry/estimators/geometry/metric_estimator.py
+++ b/neurometry/estimators/geometry/metric_estimator.py
@@ -1,24 +1,18 @@
-# import os
+import os
 
-# os.environ["GEOMSTATS_BACKEND"] = "pytorch"
-# from geomstats.geometry.base import ImmersedSet
-# from geomstats.geometry.euclidean import Euclidean
-# from geomstats.geometry.pullback_metric import PullbackMetric
+os.environ["GEOMSTATS_BACKEND"] = "pytorch"
+from geomstats.geometry.base import ImmersedSet
+from geomstats.geometry.euclidean import Euclidean
 
 
-# class NeuralManifoldIntrinsic(ImmersedSet):
-#     def __init__(self, dim, neural_embedding_dim, neural_immersion, equip=True):
-#         self.neural_embedding_dim = neural_embedding_dim
-#         super().__init__(dim=dim, equip=equip)
-#         self.neural_immersion = neural_immersion
+class NeuralManifoldIntrinsic(ImmersedSet):
+    def __init__(self, dim, neural_embedding_dim, neural_immersion, equip=True):
+        self.neural_embedding_dim = neural_embedding_dim
+        super().__init__(dim=dim, equip=equip)
+        self.neural_immersion = neural_immersion
 
-#     def immersion(self, point):
-#         return self.neural_immersion(point)
+    def immersion(self, point):
+        return self.neural_immersion(point)
 
-#     def _define_embedding_space(self):
-#         return Euclidean(dim=self.neural_embedding_dim)
-
-#     neural_manifold = NeuralManifoldIntrinsic(
-#         dim, embedding_dim, immersion, equip=False
-#     )
-#     neural_manifold.equip_with_metric(PullbackMetric)
+    def _define_embedding_space(self):
+        return Euclidean(dim=self.neural_embedding_dim)
diff --git a/neurometry/estimators/geometry/models/losses.py b/neurometry/estimators/geometry/models/losses.py
index 21fb2a8..c331feb 100644
--- a/neurometry/estimators/geometry/models/losses.py
+++ b/neurometry/estimators/geometry/models/losses.py
@@ -173,4 +173,3 @@ def moving_forward_loss(z, config):
     if len(loss) == 0:
         return torch.zeros(1).to(config.device)
     return torch.mean(loss)
-
diff --git a/neurometry/estimators/geometry/models/spherical_vae.py b/neurometry/estimators/geometry/models/spherical_vae.py
index cc79c39..62b4870 100644
--- a/neurometry/estimators/geometry/models/spherical_vae.py
+++ b/neurometry/estimators/geometry/models/spherical_vae.py
@@ -212,7 +212,6 @@ def _elbo(self, x, x_mu, posterior_params):
 
         recon_loss = torch.mean((x - x_mu).pow(2))
 
-
         return train_config.recon_weight * recon_loss + train_config.kld_weight * kld
 
     def _latent_regularization_loss(self, labels, z):
diff --git a/neurometry/estimators/geometry/models/train_config.py b/neurometry/estimators/geometry/models/train_config.py
index 4bb241a..44b37be 100644
--- a/neurometry/estimators/geometry/models/train_config.py
+++ b/neurometry/estimators/geometry/models/train_config.py
@@ -4,10 +4,10 @@
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # training
-num_epochs = 500
-batch_size = 64
+num_epochs = 200
+batch_size = 32
 lr = 1e-3
 
 recon_weight = 1.0  # weight for the reconstruction loss
 kld_weight = 0.03  # 0.03  # weight for KL loss
-latent_weight = 10  # weight for latent regularization loss
+latent_weight = 100  # weight for latent regularization loss
diff --git a/tutorials/04_methods_estimate_manifold_geometry.ipynb b/tutorials/04_methods_estimate_manifold_geometry.ipynb
index 88a2ee8..a966073 100644
--- a/tutorials/04_methods_estimate_manifold_geometry.ipynb
+++ b/tutorials/04_methods_estimate_manifold_geometry.ipynb
@@ -4,19 +4,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Classify Neural Manifold Topology"
+    "# Estimate Neural Manifold Immersion"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Set-up + Imports"
+    "## Set Up + Imports"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 238,
    "metadata": {},
    "outputs": [
     {
@@ -41,25681 +41,707 @@
     "%autoreload 2\n",
     "%load_ext jupyter_black\n",
     "\n",
-    "import os\n",
+    "import neurometry.datasets.synthetic as synthetic\n",
+    "import numpy as np\n",
     "\n",
     "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import torch\n",
+    "\n",
+    "\n",
+    "import os\n",
     "\n",
     "os.environ[\"GEOMSTATS_BACKEND\"] = \"pytorch\"\n",
     "import geomstats.backend as gs\n",
-    "import neurometry.datasets.synthetic as synthetic"
+    "import torch"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Synthetic circle analysis"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 312,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "noise level: 0.71%\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "import neurometry.datasets.synthetic as synthetic\n",
-    "\n",
-    "circle_task_points = synthetic.hypersphere(1, 1000)\n",
-    "circle_noisy_points, circle_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=circle_task_points,\n",
-    "    encoding_dim=10,\n",
+    "task_points, intrinsic_coords = synthetic.hypersphere(1, 1000)\n",
+    "noisy_points, manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=task_points,\n",
+    "    encoding_dim=3,\n",
     "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(10),\n",
-    "    poisson_multiplier=100,\n",
+    "    scales=gs.array([5, 3, 1]),\n",
+    "    fano_factor=0.1,\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 313,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from neurometry.estimators.geometry.immersion_estimator import ImmersionEstimator\n",
+    "\n",
+    "extrinsic_dim = 3\n",
+    "topology = \"circle\"\n",
+    "device = \"cuda\"\n",
+    "\n",
+    "immersion_estimator = ImmersionEstimator(\n",
+    "    extrinsic_dim, topology, device=device, verbose=True\n",
+    ")\n",
+    "\n",
+    "latents = immersion_estimator.intrinsic_to_extrinsic(intrinsic_coords).squeeze()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 314,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/200, Train Loss: 13022.06607155235, Test Loss: 11866.508007193383\n",
+      "Epoch 2/200, Train Loss: 8618.303601918711, Test Loss: 4035.902180384047\n",
+      "Epoch 3/200, Train Loss: 3506.947428379754, Test Loss: 2918.8028884944165\n",
+      "Epoch 4/200, Train Loss: 2998.2627454944236, Test Loss: 2960.5285708899637\n",
+      "Epoch 5/200, Train Loss: 2943.1006402080316, Test Loss: 2854.7209811061157\n",
+      "Epoch 6/200, Train Loss: 2931.749965913282, Test Loss: 2906.7113782873034\n",
+      "Epoch 7/200, Train Loss: 2936.539423533661, Test Loss: 2869.982490885765\n",
+      "Epoch 8/200, Train Loss: 2924.5017225906395, Test Loss: 2927.270978193271\n",
+      "Epoch 9/200, Train Loss: 2925.263847975524, Test Loss: 2780.0403350470656\n",
+      "Epoch 10/200, Train Loss: 2921.043327633271, Test Loss: 2839.904050959253\n",
+      "Epoch 11/200, Train Loss: 2905.3423914164487, Test Loss: 2866.2912308967966\n",
+      "Epoch 12/200, Train Loss: 2876.427814198662, Test Loss: 2829.4151015565185\n",
+      "Epoch 13/200, Train Loss: 2779.8973905041703, Test Loss: 2673.4944191285686\n",
+      "Epoch 14/200, Train Loss: 2228.9491204374194, Test Loss: 1400.3976173857802\n",
+      "Epoch 15/200, Train Loss: 581.9834140784118, Test Loss: 347.7742810896095\n",
+      "Epoch 16/200, Train Loss: 279.0328247109313, Test Loss: 267.3305055635849\n",
+      "Epoch 17/200, Train Loss: 245.75622916679703, Test Loss: 263.6164780319128\n",
+      "Epoch 18/200, Train Loss: 240.68186166147058, Test Loss: 246.66219983676436\n",
+      "Epoch 19/200, Train Loss: 237.38749625808438, Test Loss: 279.4329071476583\n",
+      "Epoch 20/200, Train Loss: 234.5714734116473, Test Loss: 265.0156918540006\n",
+      "Epoch 21/200, Train Loss: 231.79229446742386, Test Loss: 279.2706086243095\n",
+      "Epoch 22/200, Train Loss: 229.0386950753332, Test Loss: 249.94186853725634\n",
+      "Epoch 23/200, Train Loss: 227.31539005782253, Test Loss: 268.75888290801004\n",
+      "Epoch 24/200, Train Loss: 224.451204087807, Test Loss: 248.40102634320124\n",
+      "Epoch 25/200, Train Loss: 221.43353973405112, Test Loss: 261.67802879136224\n",
+      "Epoch 26/200, Train Loss: 220.20762645825585, Test Loss: 273.82256446995797\n",
+      "Epoch 27/200, Train Loss: 216.8689131767153, Test Loss: 237.06024181351796\n",
+      "Epoch 28/200, Train Loss: 213.77894809375042, Test Loss: 240.26168916206117\n",
+      "Epoch 29/200, Train Loss: 211.60635354746665, Test Loss: 252.11766448825193\n",
+      "Epoch 30/200, Train Loss: 209.21178646748385, Test Loss: 260.092256280038\n",
+      "Epoch 31/200, Train Loss: 202.79718661209427, Test Loss: 241.52946227609323\n",
+      "Epoch 32/200, Train Loss: 194.87351492525858, Test Loss: 230.76113112748914\n",
+      "Epoch 33/200, Train Loss: 181.05125346479946, Test Loss: 192.13371221101397\n",
+      "Epoch 34/200, Train Loss: 153.56953441472442, Test Loss: 156.07161616470881\n",
+      "Epoch 35/200, Train Loss: 91.97569775646785, Test Loss: 56.56133262001696\n",
+      "Epoch 36/200, Train Loss: 26.815740785373166, Test Loss: 19.558717344291274\n",
+      "Epoch 37/200, Train Loss: 16.52103507874917, Test Loss: 15.952853481531998\n",
+      "Epoch 38/200, Train Loss: 13.58144190250396, Test Loss: 14.01960901155492\n",
+      "Epoch 39/200, Train Loss: 12.836103158344738, Test Loss: 13.863664165425158\n",
+      "Epoch 40/200, Train Loss: 12.315041795453169, Test Loss: 11.806134492512886\n",
+      "Epoch 41/200, Train Loss: 11.76138155573257, Test Loss: 12.063178828959058\n",
+      "Epoch 42/200, Train Loss: 11.179732268351385, Test Loss: 11.508513510793687\n",
+      "Epoch 43/200, Train Loss: 11.189405334737547, Test Loss: 11.760025788343384\n",
+      "Epoch 44/200, Train Loss: 10.93132931872994, Test Loss: 10.761865696993798\n",
+      "Epoch 45/200, Train Loss: 10.838990171532553, Test Loss: 11.41829957247278\n",
+      "Epoch 46/200, Train Loss: 10.71024981766642, Test Loss: 10.848896291883566\n",
+      "Epoch 47/200, Train Loss: 10.634998890933032, Test Loss: 10.895327969624399\n",
+      "Epoch 48/200, Train Loss: 10.68274010705295, Test Loss: 11.32860870929207\n",
+      "Epoch 49/200, Train Loss: 10.421924024059225, Test Loss: 11.571128517912175\n",
+      "Epoch 50/200, Train Loss: 10.409696850767475, Test Loss: 11.736795351597083\n",
+      "Epoch 51/200, Train Loss: 11.102182471691105, Test Loss: 12.956047146141959\n",
+      "Epoch 52/200, Train Loss: 10.994703279510636, Test Loss: 13.17528889908434\n",
+      "Epoch 53/200, Train Loss: 10.482852547091355, Test Loss: 11.898595168607349\n",
+      "Epoch 54/200, Train Loss: 10.416190271918822, Test Loss: 10.924367498999512\n",
+      "Epoch 55/200, Train Loss: 10.210945332522176, Test Loss: 11.43018198040949\n",
+      "Epoch 56/200, Train Loss: 10.782676653098546, Test Loss: 11.04902838432696\n",
+      "Epoch 57/200, Train Loss: 10.763412235093108, Test Loss: 10.859743072117222\n",
+      "Epoch 58/200, Train Loss: 10.339436268494127, Test Loss: 10.490132593006257\n",
+      "Epoch 59/200, Train Loss: 10.542175790212186, Test Loss: 11.062322965313768\n",
+      "Epoch 60/200, Train Loss: 10.515446976184366, Test Loss: 10.643298152949187\n",
+      "Epoch 61/200, Train Loss: 10.129465570403294, Test Loss: 10.874929821086694\n",
+      "Epoch 62/200, Train Loss: 10.33095289254145, Test Loss: 11.038826062315238\n",
+      "Epoch 63/200, Train Loss: 10.607780176477222, Test Loss: 11.117567014450696\n",
+      "Epoch 64/200, Train Loss: 10.19363055203544, Test Loss: 11.502888288373672\n",
+      "Epoch 65/200, Train Loss: 10.395164764760532, Test Loss: 12.286309922334661\n",
+      "Epoch 66/200, Train Loss: 10.489277835265082, Test Loss: 12.147076416175407\n",
+      "Epoch 67/200, Train Loss: 10.297389446751724, Test Loss: 11.487427999800166\n",
+      "Epoch 68/200, Train Loss: 10.0532093981172, Test Loss: 10.783335880098052\n",
+      "Epoch 69/200, Train Loss: 10.00805927965536, Test Loss: 10.517746803451905\n",
+      "Epoch 70/200, Train Loss: 10.038053454807573, Test Loss: 10.524892050300585\n",
+      "Epoch 71/200, Train Loss: 10.249230543577973, Test Loss: 11.073625057481442\n",
+      "Epoch 72/200, Train Loss: 10.45075518826603, Test Loss: 11.42113223852472\n",
+      "Epoch 73/200, Train Loss: 10.487131999981225, Test Loss: 10.570602616595844\n",
+      "Epoch 74/200, Train Loss: 10.220835674571193, Test Loss: 10.895753993079435\n",
+      "Epoch 75/200, Train Loss: 10.169529125904287, Test Loss: 10.883637800501536\n",
+      "Epoch 76/200, Train Loss: 10.268290528991837, Test Loss: 11.839045803259603\n",
+      "Epoch 77/200, Train Loss: 10.841278901725104, Test Loss: 13.286651308136339\n",
+      "Epoch 78/200, Train Loss: 10.78742451158501, Test Loss: 10.868974746991341\n",
+      "Epoch 79/200, Train Loss: 10.184991181320887, Test Loss: 11.489565595819442\n",
+      "Epoch 80/200, Train Loss: 9.927987072603319, Test Loss: 11.906069808679359\n",
+      "Epoch 81/200, Train Loss: 10.229912019206585, Test Loss: 11.056351778753053\n",
+      "Epoch 82/200, Train Loss: 10.224477222643996, Test Loss: 10.983212042660464\n",
+      "Epoch 83/200, Train Loss: 10.534749195451557, Test Loss: 10.981141283742133\n",
+      "Epoch 84/200, Train Loss: 10.03709890637773, Test Loss: 11.091489528134302\n",
+      "Epoch 85/200, Train Loss: 10.099075219602044, Test Loss: 10.215108201629263\n",
+      "Epoch 86/200, Train Loss: 9.957683713049423, Test Loss: 10.696675303985618\n",
+      "Epoch 87/200, Train Loss: 10.548157830056248, Test Loss: 10.841509217747175\n",
+      "Epoch 88/200, Train Loss: 11.518595731549267, Test Loss: 12.169079221187564\n",
+      "Epoch 89/200, Train Loss: 10.042051033225153, Test Loss: 11.729942718219364\n",
+      "Epoch 90/200, Train Loss: 10.119450966510573, Test Loss: 11.207343911274242\n",
+      "Epoch 91/200, Train Loss: 10.41091179659802, Test Loss: 10.694221713934525\n",
+      "Epoch 92/200, Train Loss: 10.56489884217293, Test Loss: 12.265211287976276\n",
+      "Epoch 93/200, Train Loss: 10.458070270826122, Test Loss: 11.641027302346824\n",
+      "Epoch 94/200, Train Loss: 10.504942763502745, Test Loss: 11.058611111962534\n",
+      "Epoch 95/200, Train Loss: 10.548172735467055, Test Loss: 11.000239800035514\n",
+      "Epoch 96/200, Train Loss: 10.245151854108455, Test Loss: 11.04323252110764\n",
+      "Epoch 97/200, Train Loss: 10.191355638964907, Test Loss: 11.36048088953506\n",
+      "Epoch 98/200, Train Loss: 9.924821653795432, Test Loss: 11.75451218909611\n",
+      "Epoch 99/200, Train Loss: 10.330173887084506, Test Loss: 13.351181120901066\n",
+      "Epoch 100/200, Train Loss: 10.838888420624166, Test Loss: 13.823539535519176\n",
+      "Epoch 101/200, Train Loss: 10.453439593661505, Test Loss: 11.017190055960508\n",
+      "Epoch 102/200, Train Loss: 10.36379832834558, Test Loss: 10.153877488902717\n",
+      "Epoch 103/200, Train Loss: 10.261569604917467, Test Loss: 11.63506595178647\n",
+      "Epoch 104/200, Train Loss: 10.030633530976703, Test Loss: 12.98612818928918\n",
+      "Epoch 105/200, Train Loss: 10.516783408807225, Test Loss: 12.411771616249382\n",
+      "Epoch 106/200, Train Loss: 11.723875801195627, Test Loss: 14.518145701813138\n",
+      "Epoch 107/200, Train Loss: 10.953136398023542, Test Loss: 11.480414953544896\n",
+      "Epoch 108/200, Train Loss: 10.490797649613818, Test Loss: 12.078476891010268\n",
+      "Epoch 109/200, Train Loss: 10.574833275822863, Test Loss: 11.29328176777963\n",
+      "Epoch 110/200, Train Loss: 10.618192868035145, Test Loss: 12.077397393585514\n",
+      "Epoch 111/200, Train Loss: 10.659403823924361, Test Loss: 11.75574367947267\n",
+      "Epoch 112/200, Train Loss: 10.136886238475372, Test Loss: 12.441191867571947\n",
+      "Epoch 113/200, Train Loss: 10.42011253567286, Test Loss: 11.143815747493239\n",
+      "Epoch 114/200, Train Loss: 11.008284384802122, Test Loss: 11.46021107680554\n",
+      "Epoch 115/200, Train Loss: 10.817967284863048, Test Loss: 11.915131627573961\n",
+      "Epoch 116/200, Train Loss: 10.153092769335945, Test Loss: 10.568478333836405\n",
+      "Epoch 117/200, Train Loss: 10.645266961321623, Test Loss: 11.236809955086718\n",
+      "Epoch 118/200, Train Loss: 10.531840968945703, Test Loss: 13.324285602372624\n",
+      "Epoch 119/200, Train Loss: 10.219342748924332, Test Loss: 11.83394631601235\n",
+      "Epoch 120/200, Train Loss: 10.508616401148757, Test Loss: 14.55446090382992\n",
+      "Epoch 121/200, Train Loss: 10.541280977049324, Test Loss: 10.582763624228578\n",
+      "Epoch 122/200, Train Loss: 10.656432892575117, Test Loss: 10.803629422166404\n",
+      "Epoch 123/200, Train Loss: 10.151317978603426, Test Loss: 10.581207787907042\n",
+      "Epoch 124/200, Train Loss: 10.336319523696458, Test Loss: 11.344743150047892\n",
+      "Epoch 125/200, Train Loss: 10.166030341868, Test Loss: 13.813791344556348\n",
+      "Epoch 126/200, Train Loss: 10.092743927755372, Test Loss: 10.776318576583618\n",
+      "Epoch 127/200, Train Loss: 10.113921768874539, Test Loss: 11.404366889515973\n",
+      "Epoch 128/200, Train Loss: 10.924066937889807, Test Loss: 9.971519365672515\n",
+      "Epoch 129/200, Train Loss: 10.446296324875595, Test Loss: 10.594064106762302\n",
+      "Epoch 130/200, Train Loss: 11.167741104478774, Test Loss: 12.793943451311602\n",
+      "Epoch 131/200, Train Loss: 10.521995408035934, Test Loss: 10.49897520536827\n",
+      "Epoch 132/200, Train Loss: 10.428246720334194, Test Loss: 13.231898942024616\n",
+      "Epoch 133/200, Train Loss: 10.793708156397104, Test Loss: 12.60166338113954\n",
+      "Epoch 134/200, Train Loss: 11.021249109847336, Test Loss: 11.260395768368387\n",
+      "Epoch 135/200, Train Loss: 10.952955900195018, Test Loss: 14.230480686985752\n",
+      "Epoch 136/200, Train Loss: 11.503802173193101, Test Loss: 12.949232517923068\n",
+      "Epoch 137/200, Train Loss: 10.822156605041187, Test Loss: 11.822374905189267\n",
+      "Epoch 138/200, Train Loss: 10.435474336806072, Test Loss: 13.536567867461878\n",
+      "Epoch 139/200, Train Loss: 10.340400126585987, Test Loss: 12.953669338136015\n",
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-       "                            \n",
-       "var gd = document.getElementById('4b9dbb5e-16e9-4704-a149-be226c7ca480');\n",
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-       "        if (!display || display === 'none') {{\n",
-       "            console.log([gd, 'removed!']);\n",
-       "            Plotly.purge(gd);\n",
-       "            observer.disconnect();\n",
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-       "// Listen for the removal of the full notebook cells\n",
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-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot noisy_points and manifold_points in 3D with plotly\n",
-    "\n",
-    "import plotly.graph_objects as go\n",
-    "\n",
-    "fig = go.Figure()\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=circle_noisy_points[:, 0],\n",
-    "        y=circle_noisy_points[:, 1],\n",
-    "        z=circle_noisy_points[:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3),\n",
-    "    )\n",
-    ")\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=circle_manifold_points[:, 0],\n",
-    "        y=circle_manifold_points[:, 1],\n",
-    "        z=circle_manifold_points[:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3),\n",
-    "    )\n",
-    ")\n",
-    "\n",
-    "fig.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from neurometry.estimators.topology.persistent_homology import compute_diagrams_shuffle\n",
-    "\n",
-    "\n",
-    "import neurometry.datasets.synthetic as synthetic\n",
-    "\n",
-    "circle_task_points = synthetic.hypersphere(1, 1000)\n",
-    "circle_noisy_points, circle_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=circle_task_points,\n",
-    "    encoding_dim=10,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(10),\n",
-    "    poisson_multiplier=100,\n",
-    ")\n",
-    "\n",
-    "num_shuffles = 100\n",
-    "\n",
-    "circle_noisy_diagrams = compute_diagrams_shuffle(\n",
-    "    circle_noisy_points, num_shuffles=num_shuffles, homology_dimensions=[0, 1, 2]\n",
-    ")\n",
-    "\n",
-    "\n",
-    "from gtda.diagrams import PersistenceEntropy\n",
-    "\n",
-    "circle_PE = PersistenceEntropy()\n",
-    "\n",
-    "circle_features = circle_PE.fit_transform(circle_noisy_diagrams)\n",
-    "\n",
-    "# manifold_diagrams = compute_diagrams_shuffle(manifold_points, num_shuffles=num_shuffles)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "X = noisy_points\n",
-    "\n",
-    "\n",
-    "def _shuffle_entries(data, rng):\n",
-    "    return np.array([rng.permutation(row) for row in data])\n",
-    "\n",
-    "\n",
-    "seed = 0\n",
-    "rng = np.random.default_rng(seed)\n",
-    "shuffled_Xs = [_shuffle_entries(X, rng) for _ in range(num_shuffles)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
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-       "                            \n",
-       "var gd = document.getElementById('b002dd44-9735-4463-91a0-ef7f7a400613');\n",
-       "var x = new MutationObserver(function (mutations, observer) {{\n",
-       "        var display = window.getComputedStyle(gd).display;\n",
-       "        if (!display || display === 'none') {{\n",
-       "            console.log([gd, 'removed!']);\n",
-       "            Plotly.purge(gd);\n",
-       "            observer.disconnect();\n",
-       "        }}\n",
-       "}});\n",
-       "\n",
-       "// Listen for the removal of the full notebook cells\n",
-       "var notebookContainer = gd.closest('#notebook-container');\n",
-       "if (notebookContainer) {{\n",
-       "    x.observe(notebookContainer, {childList: true});\n",
-       "}}\n",
-       "\n",
-       "// Listen for the clearing of the current output cell\n",
-       "var outputEl = gd.closest('.output');\n",
-       "if (outputEl) {{\n",
-       "    x.observe(outputEl, {childList: true});\n",
-       "}}\n",
-       "\n",
-       "                        })                };                });            </script>        </div>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import plotly.graph_objects as go\n",
-    "\n",
-    "fig = go.Figure()\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=X[:, 0],\n",
-    "        y=X[:, 1],\n",
-    "        z=X[:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3),\n",
-    "    )\n",
-    ")\n",
-    "\n",
-    "i = 5\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=shuffled_Xs[i][:, 0],\n",
-    "        y=shuffled_Xs[i][:, 1],\n",
-    "        z=shuffled_Xs[i][:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3),\n",
-    "    )\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
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                       {\"responsive\": true}                    ).then(function(){\n",
-       "                            \n",
-       "var gd = document.getElementById('f6812aac-2dae-4cc9-82b5-75180cb2aa10');\n",
-       "var x = new MutationObserver(function (mutations, observer) {{\n",
-       "        var display = window.getComputedStyle(gd).display;\n",
-       "        if (!display || display === 'none') {{\n",
-       "            console.log([gd, 'removed!']);\n",
-       "            Plotly.purge(gd);\n",
-       "            observer.disconnect();\n",
-       "        }}\n",
-       "}});\n",
-       "\n",
-       "// Listen for the removal of the full notebook cells\n",
-       "var notebookContainer = gd.closest('#notebook-container');\n",
-       "if (notebookContainer) {{\n",
-       "    x.observe(notebookContainer, {childList: true});\n",
-       "}}\n",
-       "\n",
-       "// Listen for the clearing of the current output cell\n",
-       "var outputEl = gd.closest('.output');\n",
-       "if (outputEl) {{\n",
-       "    x.observe(outputEl, {childList: true});\n",
-       "}}\n",
-       "\n",
-       "                        })                };                });            </script>        </div>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from gtda.plotting import plot_diagram\n",
-    "\n",
-    "plot_diagram(noisy_diagrams[0])"
-   ]
-  },
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-   "source": [
-    "plot_diagram(noisy_diagrams[70])"
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-  },
-  {
-   "cell_type": "code",
-   "execution_count": 62,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from gtda.diagrams import PersistenceEntropy\n",
-    "\n",
-    "circle_PE = PersistenceEntropy()\n",
-    "\n",
-    "circle_features = circle_PE.fit_transform(circle_noisy_diagrams)"
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-   "execution_count": 40,
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+       "<style>#sk-container-id-15 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-15 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-15 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-15 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-15 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
        "\n",
-       "// Listen for the removal of the full notebook cells\n",
-       "var notebookContainer = gd.closest('#notebook-container');\n",
-       "if (notebookContainer) {{\n",
-       "    x.observe(notebookContainer, {childList: true});\n",
-       "}}\n",
+       "#sk-container-id-15 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
        "\n",
-       "// Listen for the clearing of the current output cell\n",
-       "var outputEl = gd.closest('.output');\n",
-       "if (outputEl) {{\n",
-       "    x.observe(outputEl, {childList: true});\n",
-       "}}\n",
+       "#sk-container-id-15 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
        "\n",
-       "                        })                };                });            </script>        </div>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# 3d plot with plotly\n",
-    "fig = go.Figure()\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=features[1:, 0],\n",
-    "        y=features[1:, 1],\n",
-    "        z=features[1:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"blue\"),\n",
-    "    )\n",
-    ")\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=[features[0, 0]],\n",
-    "        y=[features[0, 1]],\n",
-    "        z=[features[0, 2]],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"red\"),\n",
-    "    )\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-15 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-15 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-15 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-15 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-15 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-15 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-15 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-15 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-15 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-15 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-15 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-15 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-15\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=3, topology=&#x27;circle&#x27;,\n",
+       "                   verbose=True)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" checked><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ImmersionEstimator<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=3, topology=&#x27;circle&#x27;,\n",
+       "                   verbose=True)</pre></div> </div></div></div></div>"
+      ],
       "text/plain": [
-       "<Figure size 2000x1000 with 4 Axes>"
+       "ImmersionEstimator(device='cuda', extrinsic_dim=3, topology='circle',\n",
+       "                   verbose=True)"
       ]
      },
+     "execution_count": 314,
      "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from neurometry.estimators.topology.plotting import plot_all_barcodes_with_null\n",
-    "\n",
-    "plot_all_barcodes_with_null(\n",
-    "    noisy_diagrams, \"noisy\", diagrams_2=manifold_diagrams, dataset_name_2=\"manifold\"\n",
-    ");"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def _get_lifespan_from_diagram(diagram):\n",
-    "    birth = diagram[:, 0]\n",
-    "    death = diagram[:, 1]\n",
-    "    if np.isfinite(death).any():\n",
-    "        inf_value = 3 * np.max(death[death != np.inf])\n",
-    "    else:\n",
-    "        inf_value = 1000\n",
-    "    death[death == np.inf] = inf_value\n",
-    "    lifespan = death - birth\n",
-    "    indices = np.argsort(-lifespan)[:20]\n",
-    "\n",
-    "    return lifespan[indices]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def estimate_betti_numbers(points, num_shuffles, homology_dimensions=(0, 1, 2)):\n",
-    "    all_diagrams = compute_diagrams_shuffle(\n",
-    "        points, num_shuffles=num_shuffles, homology_dimensions=homology_dimensions\n",
-    "    )\n",
-    "    diagram = all_diagrams[0]\n",
-    "    shuffled_diagrams = all_diagrams[1:]\n",
-    "\n",
-    "    betti_numbers = {dim: None for dim in homology_dimensions}\n",
-    "\n",
-    "    for dim in homology_dimensions:\n",
-    "        filtered_diagram = diagram[diagram[:, 2] == dim]\n",
-    "        lifespan = _get_lifespan_from_diagram(filtered_diagram)\n",
-    "        filtered_shuffled_diagrams = np.array(\n",
-    "            [\n",
-    "                shuffled_diagrams[i, shuffled_diagrams[i, :, 2] == 1]\n",
-    "                for i in range(shuffled_diagrams.shape[0])\n",
-    "            ]\n",
-    "        )\n",
-    "        betti_number = []\n",
-    "        for diag in filtered_shuffled_diagrams:\n",
-    "            shuffled_lifespan = _get_lifespan_from_diagram(diag)\n",
-    "            significant_features = (lifespan > shuffled_lifespan).astype(int)\n",
-    "            betti_number.append(sum(significant_features))\n",
-    "        betti_numbers[dim] = (np.mean(betti_number), np.std(betti_number))\n",
-    "\n",
-    "    return betti_numbers"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: (1.28, 2.209434316742636), 1: (1.0, 0.0), 2: (0.0, 0.0)}\n"
-     ]
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "betti_numbers = estimate_betti_numbers(\n",
-    "    manifold_points, num_shuffles=100, homology_dimensions=(0, 1, 2)\n",
-    ")\n",
-    "print(betti_numbers)"
+    "immersion_estimator.fit(X=latents, y=noisy_points)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 267,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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SDQB5uvXWW2Pvvff+zPNvvfVWTJs2Ld54441mgfu4446LSZMmtWWJJWv48OHx+OOPx6BBg5o9v2rVqqiuro6//vWvaw3cEydOjD/+8Y/NbvNVKCeddFL8+te//kzfNTU18be//S1eeumlZoF7/Pjx8atf/argdQDQPgjdAJCnHj16xOOPPx4XXnjhejf02mmnneK2226L22+/PZWwuLHaeeed49VXX40rr7zyM+F7TWVlZTFmzJh44oknYtKkSdGxY8fUajrttNNixowZMXbs2Mhm1/51qX///nH99dfHnXfeaT4BWKdMsua9TgCAvHz88cfxzDPPxGuvvRaLFy+OTp06Rd++fWPEiBExdOjQYpe3UXj99dfjhRdeiI8++iiWLVsWvXr1iq233joOOOCAguxS3loffPBBPPHEEzFnzpxYvnx59OnTJ3bfffcYPnx4ZDKZNq8HgI2L0A0AAAApcXo5AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASsqKXUC+crlczJ07NyoqKty2AwAAgDaRJEnU1dVF3759I5td93r2Rh+6586dG/369St2GQAAAGyC3nvvvdhmm23W+fpGH7orKioi4pM3WllZWeRqAAAA2BTU1tZGv379mjLpumz0oXv1KeWVlZVCNwAAAG3q8y5ztpEaAAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJCSsmIX0N7MmjUrcrlcscsAANqBbDYbQ4YMKXYZAORB6C6wXC4ndAMAABARQndqGpKGqGusS3WMig4VUZYxhQAAAKVKYktJXWNd3FVzT6pjjK8aFz3LeqY6BgAAABvORmoAAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApMR9ulNS0aEixleNS30MAAAASpfQnZKyTFn0LOtZ7DIAAAAoIqG7wLJZZ+wDAIXhewXAxs8nOQAAAKTESneB5XK5yOVyxS4DAACAEiB0p6QhaYi6xrpUx6joUBFlGVMIAABQqiS2lNQ11sVdNfekOsb4qnE2awMAAChhrukGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICXu052Sig4VMb5qXOpjAAAAULqE7pSUZcqiZ1nPYpcBAABAEQndBZbNOmMfACgM3ysANn4+yQEAACAlVroLLJfLRS6XK3YZAAAAlAChOyUNSUPUNdalOkZFh4ooy5hCAACAUiWxpaSusS7uqrkn1THGV42zWRsAAEAJc003AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASvLavTyXy8Xjjz8ejz76aLz22mvx+uuvx6JFi6K+vj6WL18eXbt2je7du8dmm20WO+ywQ+y4444xevToOOiggyKblfcBAABo3zYodNfW1sZPf/rT+PWvfx2LFi1q9lqSJE2/19XVRV1dXXz44Yfx6quvRkTEpZdeGptttll885vfjH/+53+OysrKPMoHAACA0pVJ1kzJLTB16tT4yle+EosWLYpWNm0+cCYTvXr1it///vdxyCGHbHA/tbW1UVVVFTU1NSUR4KurqyOXy0VD0hB1jXWpjlXRoSLKMm61DgDtVTabjaFDhxa7DADWoqVZtFWJ7U9/+lMcffTRsWrVqqbA3b1799h3331jzz33jP79+8eWW24ZXbt2jc6dO8eKFSti+fLl8eGHH8a7774bM2bMiGeffTbq6uoiSZJYsGBBHHbYYXHvvffG4Ycfnt87LjFlmbLoWdaz2GUAAABQRC0O3QsXLoyTTz45Vq5cGRERgwYNiksuuSTGjx8fnTt3bvGAK1eujLvuuisuvvjimDVrVqxatSomTpwYr776amy22WatfwclxrXqAECh+F4BsPFr8Sf5zTffHB999FFkMpk49NBD46WXXorjjz++VYE7IqJTp04xYcKE+Nvf/haHHnpoRETMnz8/br755lb1AwAAAKWuxSvdd999d0REdO3aNe64447o1q1bXgN37do1br/99hgwYEAsX7487rrrrvj+97+fV5+lIJfLRS6XK3YZAAAAlIAWh+7Zs2c3rXIX6jTwXr16xaGHHhp//OMf46233ipIn6WiLTZSi7CZGgAAQClrcVpbvHhxRET06dOnoAWs7m/JkiUF7bfY6hrr4q6ae1IfZ3zVOBu2AQAAlKgWX9O9xRZbRETEm2++WdACVve3un8AAABoL1ocunfaaadIkiQef/zxePnllwsy+N///vd47LHHIpPJxE477VSQPgEAAKBUtDh0H3fccRERkSRJHHXUUfHqq6/mNfBrr70W48aNa7rf94QJE/LqDwAAAEpNq0L3brvtFhERb7/9duy1117xrW99K6ZNm9bi3bpzuVxMnz49vv3tb8dee+0Vb7/9dmQymdh9992bQj0AAAC0Fy3eSK1jx45x++23x5gxY+KDDz6IFStWxPXXXx/XX399lJeXxy677BIDBgyILbbYIrp27RqdOnWKlStXxvLly2PevHnxzjvvxN///vdYunRpRETTCvdWW20Vt99+e5SV2YEbAACA9qVVSXeHHXaI6dOnx4QJE+LJJ59sCs719fXx7LPPxrPPPrve9quPX+3AAw+M2267LbbeeutWlg0AAAClr8Wnl6+29dZbx+OPPx73339/fOELX4jOnTtHxCeB+vN+IiI6d+4cX/jCF+L++++Pxx57TOAGAACg3cokn15+bqWlS5fG008/Ha+99lq88cYbsXDhwqivr4+PP/44unTpEt27d49evXrF9ttvHzvuuGPst99+UV5eXqj6o7a2NqqqqqKmpiYqKysL1u+Gqq6ujlwuFw1JQ9Q11qU+XkWHiijLODUfANqjbDYbQ4cOLXYZAKxFS7No3mmtvLw8/uEf/iH+4R/+Id+u2pWyTFn0LOtZ7DIAAAAoIkukBZbNtvqMfQCAtfK9AmDj55McAAAAUmKlu8ByuVyL71sOAABA+yZ0p8RGagAAAEhrKalrrIu7au5JfZzxVeNs2AYAAFCiXNMNAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEryvk/3yy+/HDvvvHMhamlXKjpUxPiqcW0yDgAAAKUp79C96667xsiRI+Mb3/hGHHfccVFeXl6IujZ6ZZmy6FnWs9hlAAAAUESZJEmSfDrIZrORyWQiIqK8vDyOPfbYOPXUU2OfffYpSIGfp7a2NqqqqqKmpiYqKyvbZMz1mTVrVuRyuWKXAQC0A9lsNoYMGVLsMgBYi5Zm0byv6e7WrVskSRJJkkR9fX3cdNNNsf/++8cuu+wSV199dSxatCjfIQAAAGCjlPdKd319fdxxxx1x0003xbPPPvt/Hf/v6nenTp1i3Lhxceqpp8ahhx6aX7VrUWor3dXV1Va6AYCCyGazMXTo0GKXAcBatDSL5h261/Taa6/FDTfcEL/73e9i/vz5/zfI/wbwAQMGxCmnnBInn3xybL311gUZs1RDd0PSEHWNdamPV9GhIsoyeV+aDwCUIKEboHQVJXSv1tDQEPfee2/cdNNN8ec//7lp5Xd1+M5mszF27Ng47bTT4otf/GJ06NBhg8cq1dC9uGFx3FVzT+rjja8aZ8M2AGinhG6A0tVm13SvTVlZWYwfPz4eeOCBeOedd+KSSy6JQYMGNV373djYGA899FCMHz8+ttlmm/jBD34QM2fOTKMUAAAAKJpUQveatt566/jXf/3XmDVrVvzlL3+JCRMmRJcuXZoC+Lx58+LKK6+MHXbYIQ4++OC49dZbY+XKlWmXBQAAAKlLPXSvafTo0XHrrbfGzJkzY+TIkRHxf6ecJ0kSTz75ZJx44omx9dZbx0UXXRRLlixpy/IAAACgoNo0dE+bNi1OP/30GDZsWEyfPr1Z4F79v0mSxMKFC+PSSy+N7bffPh544IG2LBEAAAAKJvXQvXDhwvjP//zP2HnnnWO//faLG2+8Merq6poC9rBhw+Kqq66Kd999NyZNmhQHHnhgRHwSwOfPnx9HH310s1uRAQAAwMYildCdJEk89NBD8ZWvfCW23nrrOPfcc+O1115rCtpdu3aNk046KZ588sn4+9//Ht/73vdim222iZNOOikee+yxeP7552O//faLiE92Qr/sssvSKBMAAABSVdAbPL/99ttx0003xc033xxz5syJiP87dTwiYtddd43TTjstvv71r0dVVdU6+9ljjz3ikUceie222y7ef//9eOqppwpZJgAAALSJvEP3ypUr46677oobb7wxpk6d2uz67IiI8vLyOPbYY+O0005r2jytJTp37hxjxoyJ3/72t7F48eJ8y2xzFR0qYnzVuDYZBwAAgNKUd+jeaqutmnYZX3NVe/fdd4/TTz89vva1r0VFxYYFwx49euRbXtGUZcqiZ1nPYpcBAABAEeUduhcvXhyZTCaSJInu3bvHhAkT4rTTTovhw4fnXdyQIUPi4IMPzruftpTNtumG8ABAO+Z7BcDGL5OsuTy9AbLZbOy1115x+umnx/HHHx/l5eWFqq1Famtro6qqKmpqaqKysrJNx16bWbNmRS6XK3YZAEA7kM1mY8iQIcUuA4C1aGkWzXule8aMGbH77rvn2027kcvlhG4AAAAiogChW+Beu4akIeoa61Ifp6JDRZRlCroJPQAAAAUiraWkrrEu7qq5J/VxxleNs2EbAABAibI7BwAAAKQk75XuU045Ja/22Ww2Kisro0ePHrHjjjvGiBEjYuDAgfmWBQAAAEWXd+i++eabI5PJFKKWJvvss0+cf/75cdRRRxW0XwAAAGhLBTm9PEmSZj9re641rz/77LNx9NFHx6mnnlqI8gAAAKAo8l7pnjRpUkREvPfee3HppZfGihUrIpPJxAEHHBAjR46MbbbZJrp37x5Lly6N999/P6ZPnx5PPPFEJEkSXbp0iQsuuCC22GKLWLRoUbz00kvxwAMPRE1NTUR8soreu3fvuOKKK/ItEwAAANpcJlm99JyHadOmxZFHHhmLFy+Oo446Kq666qoYMGDAOo9/991345xzzonJkydHr1694oEHHoi99947IiKWLl0aP/zhD+Oaa66JiIiOHTvGa6+9FoMGDVprXy29IXlbqa6ujlwuF4sbFtu9HADISzabjaFDhxa7DADWoqVZNO/TyxctWhRf/vKXY/HixTFx4sSYPHnyegN3RET//v3jrrvuilNOOSUWLlzY1D4iory8PH7xi1/EN77xjYiIaGhoiJtuuinfMgEAAKDN5b3S/dOf/jR+8IMfRGVlZcydOze6devW4rZLly6NrbfeOurq6uLyyy+P8847r+m1+fPnR79+/WLVqlWx7777xpNPPrnWPkp1pbshaYi6xrrUx6voUBFlGbdbB4D2yEo3QOlqaRbNO63dddddkclkYtSoUa0K3BGfrGqPGjUq7r333vjDH/7QLHT36dMnRowYEU899VS89dZb+ZbZ5soyZU77BgAA2MTlHbpnz54dERFbbLHFBrXffPPNm/WzpiFDhsRTTz0VixYt2vAC21g2W5AN4QEAfK8AaAfy/iSvr6+PiIgPP/xwg9rPmzevWT9r6tKlS7P/BQAAgI1J3ivdW221VcyePTumTJkS9fX10b179xa3rauriylTpkQmk4mtttrqM6+v3lytd+/e+ZbZZnK5XORyuWKXAQAAQAnIO3SPGjUqZs+eHfX19XHmmWfGb3/72xa3/c53vhN1dXWRyWTikEMO+czrr7zySmQymaZT0DcmbbWRWoTN1AAAAEpV3kntm9/8Ztx8882RJEn87ne/i0WLFsVVV10VgwcPXmebt956K84+++x44IEHIiIik8nEGWec0eyYOXPmxKuvvhoREbvuumu+Zba5usa6NrlPd4R7dQMAAJSqvEP3iBEj4pxzzomf//znkclk4sEHH4wHH3ww9t577xg5cmT069cvunXrFsuWLYv3338/pk2bFtOnT48kSWL13crOPvvsGDFiRLN+J02aFEmSRCaTiUMPPTTfMgEAAKDNFeSc5CuvvDIaGxvjqquuanpu+vTpMX369LUev+atwc8666z42c9+9pljevbsGRdffHFERBx55JGFKBMAAADaVMEuBP6P//iPOPLII+OCCy5oWslenxEjRsSll166zlXsM888s1ClAQAAQFEUdPetMWPGxJgxY+LVV1+NqVOnxosvvhjz589v2tW8d+/esfvuu8chhxwSO+20UyGHBgAAgJKTypbXw4YNi2HDhqXRNQAAAGw0ssUuAAAAANoroRsAAABSksrp5RER1dXVMWPGjFiwYEHU1dVFRUVF9O7dO/bcc88YOnRoWsOWjIoOFTG+alybjQUAAEDpKWjorq2tjV/84hdx3XXXxQcffLDO4/r27RtnnHFGfPe7343KyspCllAyyjJl0bOsZ7HLAAAAoIgyyefd26uFnnnmmZgwYUK89957n3u7sIiITCYT/fv3j9tvvz322WefDR63trY2qqqqoqampiQC/KxZsyKXyxW7DACgHchmszFkyJBilwHAWrQ0ixZkpfv555+Pww47LJYuXdr0XDabjaFDh8bAgQOjvLw8li5dGm+//XZUV1c3hdJ33nknxo4dG1OnTo0999yzEKUAAABAycg7dDc0NMTxxx8f9fX1ERFRVVUV//Iv/xInn3xy9O7d+zPHL1y4MCZNmhQ/+clPoqamJurr6+P444+PV155JTp06JBvOUWXy+WsdAMAABARBQjdt956a8ycOTMymUwMGjQo/vKXv8SAAQPWeXyvXr3i3HPPja985SvxD//wDzFr1qyYOXNm3HrrrXHiiSfmW07JaEgaoq6xrk3GquhQEWWZ1PbEAwAAYAPlndTuvffept//+7//e72Be00DBgyI22+/Pfbee++IiJg8eXK7Ct11jXVxV809bTLW+KpxNm0DAAAoQXnfp3vGjBmRyWRi5MiRrb4ue6+99oqRI0dGkiTxwgsv5FsKAAAAlJS8Q/dHH30UERHDhg3boPar263uBwAAANqLvEN3x44dIyJixYoVG9R+5cqVzfoBAACA9iLv0L3llltGkiQxbdq0DWq/ut2WW26ZbykAAABQUvIO3QcccEBERLz55ptx5513tqrtH/7wh6adz1f3AwAAAO1F3qH72GOPbfr91FNPjYceeqhF7R5++OE45ZRT1toPAAAAtAd5h+6xY8fG6NGjI0mSqK+vjyOPPDKOOeaYuO+++2LhwoXNjl20aFHcf//98eUvfzkOP/zwqK+vj0wmE6NHj46xY8fmWwoAAACUlEySJEm+ncyfPz/23XffeOuttz7pNJNpeq1r165RXl4eS5cujeXLlzc9v3rYIUOGxFNPPRV9+vTZoLFra2ujqqoqampqorKyMo93URjV1dWRy+WiIWmIusa6NhmzokNFlGXyvuU6AFBistlsDB06tNhlALAWLc2iBUlqffr0iaeffjomTpwYDz30UKyZ45ctWxbLli1ba7sjjjgiJk2atMGBu5SVZcqiZ1nPYpcBAABAERVseXTzzTePBx98MKZMmRLXX399TJkyZa333t58881j1KhR8c1vfjMOOeSQQg1fMrLZvM/YBwCICN8rANqDgp+TPGrUqBg1alRERMydOzfmz58f9fX10b179+jTp0/07du30EMCAABASUr1QuC+fftuciE7l8tFLpcrdhkAAACUALtvpaQtN1JbzYZqAAAApUVCS0ldY13cVXNPm445vmqczdsAAABKiN05AAAAICUtWukePXp02nVEJpOJRx55JPVxAAAAoK20KHRPnTo1MplMakUkSZJq/wAAAFAMLb6mO0mSNOsAAACAdqdFoXvKlClp1wEAAADtTotC98EHH5x2HQAAANDu2L0cAAAAUuI+3Smp6FAR46vGtfmYAAAAlA6hOyVlmbLoWdaz2GUAAABQRKmE7pkzZ8aUKVNixowZsWDBgqirq4uKioro3bt37LnnnjFq1KjYbrvt0hi66LJZZ+wDAIXhewXAxq+gofu5556LH/7why3a7Xz06NFx2WWXxfDhwwtZQtENGTKk2CUAAABQIjJJgW7A/ctf/jLOPffcaGhoaPE9vTt27Bg/+9nP4rvf/e4Gj1tbWxtVVVVRU1MTlZWVG9xPocyaNStyuVyxywAA2oFsNusP+gAlqqVZtCAr3bfcckucddZZkclkmgL3LrvsEvvvv38MHDgwysvLY+nSpfH222/H008/HS+99FJERKxatSrOPvvs6NGjR5xwwgmFKKXocrmc0A0AAEBEFGCle9GiRTFkyJBYsmRJRESMGDEirrnmmhgxYsQ62/z1r3+N7373uzFt2rSIiOjRo0e8+eab0bNn6zceK7WV7urq6sjlctGQNERdY12bjl3RoSLKMvbGA4D2IpvNxtChQ4tdBgBr0WYr3TfccEMsWbIkMplMjB07Nu69997o1KnTetsMHz48Hn/88TjqqKPiz3/+c9TU1MQNN9wQ5513Xr7llIy6xrq4q+aeNh1zfNU4O6YDAACUkLy3xPzTn/4UERGdOnWK3/72t58buFfr2LFj3HzzzdG5c+eIiHjggQfyLQUAAABKSt6hu7q6OjKZTIwaNSo233zzVrXdYostYtSoUZEkSVRXV+dbCgAAAJSUvEP3woULIyKiX79+G9R+dbtFixblWwoAAACUlLxDd0VFRURseGhevHhxs34AAACgvcg7dPfr1y+SJImpU6dGQ0NDq9quWrUqpkyZEplMZoNXygEAAKBU5R26Dz300Ij4ZKX7Rz/6Uava/tu//VvT6eljxozJtxQAAAAoKXmH7okTJ0aHDh0iIuKyyy6LH/zgB7FixYr1tlm5cmVccMEFcemll0ZERIcOHeKUU07JtxQAAAAoKZkkSZJ8O/ne974X11xzTWQymYj4ZFfyCRMmxH777RcDBgyI8vLyWLp0abz77rvx9NNPxx133BEffPBBJEkSmUwmvvOd78TVV1+9QWO39IbkbaW6ujpyuVw0JA1R11jXpmNXdKiIskzet14HAEpENpuNoUOHFrsMANaipVm0IKG7sbExjjnmmLjvvvsik8k0hel1WXPIo446Ku6+++7IZjds0b1UQzcAQL6EboDS1dIsWpBl0Q4dOsQ999wTV155Zfz7v/971NfXx+dl+e7du8eFF14Y55577noD+sZmQ/94AADwab5XAGz8CrLSvaa6urq47bbb4tFHH40XXngh5s+fH/X19dG9e/fo06dP7LHHHjF69Og4/vjjC3KbsFJb6Z41a5aVbgCgILLZbAwZMqTYZQCwFm16enkxlVrodno5AFAoTi8HKF1teno5n2UjNQAAACS0lNQ11sVdNfe06Zjjq8ZFz7KebTomAAAA62Z3DgAAAEhJKivdS5cujbfffjtqa2tj1apVLW530EEHpVEOAAAAFEXBQnddXV1cffXVcccdd8Trr7/+ubcM+7RMJhMNDQ2FKgcAAACKriChe/r06TFu3LiYN29eRESrAzcAAAC0R3mH7jlz5sTYsWOjtra26blOnTrF4MGDY7PNNouyMnu1AQAAsGnKOxFfdtllUVtbG5lMJrbYYov42c9+Fsccc0x06dKlEPUBAADARivv0P3QQw9FRETHjh3jkUceiR133DHvogAAAKA9KMjp5ZlMJkaPHi1wr6GiQ0WMrxrX5mMCAABQOvIO3T179ox58+ZF//79C1FPu1GWKYueZT2LXQYAAABFlHfoHjx4cMybNy8WLlxYiHo2etlsttglAADthO8VABu/vD/JjzvuuEiSJB5//HH32QYAAIA15L3SPXHixLjsssvigw8+iMsvvzz+9V//tRB1bbRyuVzkcrlilwEAAEAJyDt0l5eXx+TJk+PQQw+NH/3oR5EkSfzwhz/c5O/P3ZA0RF1jXZuPW9GhIsoym/Y/ewAAgFKRSZIkKURHr7/+epxwwgkxY8aM2GKLLeKLX/xi7LTTTlFVVRWZTKZFfZx44omtHre2tjaqqqqipqYmKisrW92+0KqrqyOXy8XihsVxV809bT7++KpxNnADgHYim83G0KFDi10GAGvR0ixasCXRzp07x8477xzPP/98fPjhh3HDDTe0qn0mk9mg0A0AAAClqiCh+3/+53/imGOOieXLlzetahdoAR0AAAA2WnmH7tdeey2+9KUvxYoVK5qe69+/f+y8887Rs2fPTf7abgAAADZdeSfiyy+/PFasWBGZTCa23377uOGGG2K//fYrRG0AAACwUcs7dD/66KMREdGtW7f4y1/+En379s27KAAAAGgPsvl28NFHH0Umk4kxY8YI3AAAALCGvEN3r169IiJiyy23zLsYAAAAaE/yPr18++23j3nz5sWHH35YiHrajYoOFTG+alxRxgUAAKA05B26jzvuuHjsscfisccei6VLl0Z5eXkh6trolWXKomdZz2KXAQAAQBHlHbonTpwY1157bfz973+Pc889N6699tpC1LXRymbzPmMfACAifK8AaA/y/iTv3LlzTJ48Obbbbru4/vrrY+LEiTF//vxC1AYAAAAbtUySJEk+HVxyySUREVFTUxP/9V//FStXroxOnTrFgQceGDvvvHNUVVVFJpNpUV8XXXRRq8evra2NqqqqqKmpicrKyla3L7Tq6urI5XLFLgMAaAey2WwMHTq02GUAsBYtzaJ5h+5sNvuZUJ0kSYuD9poaGxtb3aZUQ3dD0hB1jXVFqaGiQ0WUZfK+cgAAKDKhG6B0tTSLFiSZrS23tzbLb0hIL2V1jXVxV809RRl7fNU4m7gBAACUgLxD98UXX1yIOgAAAKDdEboBAAAgJe5DAQAAACkRugEAACAlQjcAAACkJJX7StXV1cUzzzwTM2bMiAULFkRdXV1UVFRE7969Y88994x99903Kioq0hgaAAAASkZBQ/e7774bl1xySdx2222xYsWKdR7XpUuXOP744+PCCy+M/v37F7IEAAAAKBmZpLU31F6Hu+++O0499dSora1t0T26M5lMVFZWxk033RRHH330Bo/b0huSt5Xq6urI5XLRkDREXWNdUWqo6FARZZlUTmIAANpQNpuNoUOHFrsMANaipVm0IMnsoYceiuOOOy4aGxubAvdmm20We++9dwwcODDKy8tj6dKl8fbbb8dzzz0XCxcujIiImpqaOO644+K+++6LsWPHFqKUklGWKYueZT2LXQYAAABFlHfoXrZsWZx66qnR0NAQEREDBw6MK664Io4++ugoK/ts942NjTF58uQ4//zzY/bs2bFq1ao49dRTo7q6Orp27ZpvOUWXzdqbDgAoDN8rADZ+eX+ST5o0KT744IPIZDIxfPjwmDFjRnzlK19Za+COiOjQoUN8+ctfjhkzZsTw4cMjImLu3LkxadKkfEsBAACAkpL3Svf9998fEZ+E6dtvvz169OjRonZVVVVx2223xY477hi5XC7uu++++Pa3v51vOUWXy+Uil8sVuwwAAABKQN6h++WXX45MJhMHHHBADB48uFVthwwZEgcddFBMmTIlXn755XxLKSk2UgMAACDvZLZgwYKI+CRAb4jBgwfHlClTmvppL+oa6+KumnuKMvb4qnE2cQMAACgBeV/TvXrzs/r6+g1qv7pde9hEDQAAANaUd+ju27dvJEkSTzzxRKvbJkkSTz75ZGQymejbt2++pQAAAEBJyTt0jxo1KiI+2YH8mmuuaVXba6+9Nt5///2IiDjkkEPyLQUAAABKSt6h++tf/3rT79///vfjuuuua1G73/zmN3HOOec0PT7hhBPyLQUAAABKSt6he+TIkfHVr341kiSJhoaGOPPMM2OvvfaKX/7yl/H888/HggULYvny5bFgwYKYMWNGXHPNNTFixIg444wzYtWqVZHJZOKrX/1qjBw5shDvBwAAAEpGQe4rddNNN8Xs2bPjueeei4iIF198Mc4+++z1tkmSJCIiRowYETfeeGMhygAAAICSkvdKd0REt27dYurUqXHGGWdEJpOJJEk+9yebzca3vvWtmDJlSnTr1q0QZQAAAEBJySSrl5wL5K233orf/OY38eijj8aLL74Yq1atanqtY8eOsfvuu8fo0aPjtNNOi0GDBuU9Xm1tbVRVVUVNTU1UVlbm3V++qqurI5fLRUPSEHWNdUWpoaJDRZRlCnISAwBQRNlsNoYOHVrsMgBYi5Zm0YIns0GDBsVll13W9Limpibq6+uje/fuUVVVVejhSlZZpix6lvUsdhkAAAAUUerLoVVVVZtU2M5mC3LGPgCA7xUA7YBPcgAAAEiJC38LLJfLRS6XK3YZAAAAlAChOyXF3EgtwmZqAAAApaDFqWz06NFp1hGZTCYeeeSRVMdoS3WNdXFXzT1FG3981TgbuQEAABRZi0P31KlTI5PJpFJEkiSp9Q0AAADF0qrzjwt8S28AAABo11ocui+++OIWHffggw/Gc889F5lMJi666KINLgwAAAA2dgUP3QsWLIjnnnuuVW0AAACgPXKfbgAAAEiJ0A0AAAApEboBAAAgJa3avZyWq+hQEeOrxhV1fAAAAIpL6E5JWaYsepb1LHYZAAAAFJHQXWDZrDP2AYDC8L0CYOPnkxwAAABSYqW7wHK5XORyuWKXAQAAQAkQulPSkDREXWNd0cav6FARZRnTCwAAUExSWUrqGuvirpp7ijb++KpxNnIDAAAoshaH7ksuuaRFx02fPr3VbVa76KKLWnU8AAAAlLJMkiRJSw7MZrORyWRSLaaxsbHVbWpra6OqqipqamqisrIyhapap7q6OnK5XCxuWGylGwDISzabjaFDhxa7DADWoqVZtFWnl7cwn2+QtAM9AAAAtLUWh+6DDjpIMAYAAIBWaHHonjp1aoplAAAAQPuTLXYBAAAA0F4J3QAAAJAS9+lOSUWHihhfNa6o4wMAAFBcQndKyjJlbtkFAACwiRO6CyybdcY+AFAYvlcAbPx8kgMAAEBKrHQXWC6Xi1wuV+wyAAAAKAFCd0oakoaoa6wrdhlR0aEiyjKmGQAAoBiksZTUNdbFXTX3FLuMGF81zoZuAAAAReKabgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABS4j7dKanoUBHjq8YVu4yo6FBR7BIAAAA2WUJ3SsoyZdGzrGexywAAAKCIhO4Cy2adsQ8AFIbvFQAbP5/kAAAAkBIr3QWWy+Uil8sVuwwAAABKgNCdkoakIeoa64pdRpOKDhVRljHdAAAAbUkKS0ldY13cVXNPsctoMr5qnI3dAAAA2phrugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIift0p6SiQ0WMrxpX7DKaVHSoKHYJAAAAmxyhOyVlmbLoWdaz2GUAAABQREJ3gWWzztgHAArD9wqAjZ9PcgAAAEiJle4Cy+Vykcvlil0GAAAAJUDoTklD0hB1jXXFLmOTUNGhIsoy/lUGAABKj6SSkrrGurir5p5il7FJGF81zqZ1AABASXJNNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApcZ/ulFR0qIjxVeOKXcYmoaJDRbFLAAAAWCuhOyVlmbLoWdaz2GUAAABQREJ3gWWzztgHAArD9wqAjZ/QXWBDhgwpdgkAAACUCH8+BQAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKSkrdgH5SpIkIiJqa2uLXAkAAACbitUZdHUmXZeNPnTX1dVFRES/fv2KXAkAAACbmrq6uqiqqlrn65nk82J5icvlcjF37tyoqKiITCZT7HLWqba2Nvr16xfvvfdeVFZWFrscPsX8lDbzU9rMT2kzP6XPHJU281PazE9pa+/zkyRJ1NXVRd++fSObXfeV2xv9Snc2m41tttmm2GW0WGVlZbv8F669MD+lzfyUNvNT2sxP6TNHpc38lDbzU9ra8/ysb4V7NRupAQAAQEqEbgAAAEiJ0N1GOnfuHBdffHF07ty52KWwFuantJmf0mZ+Spv5KX3mqLSZn9Jmfkqb+fnERr+RGgAAAJQqK90AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASElZsQvIVy6Xi7lz50ZFRUVkMplilwMAAMAmIEmSqKuri759+0Y2u+717I0+dM+dOzf69etX7DIAAADYBL333nuxzTbbrPP1jT50V1RURMQnb7SysrLI1QAAALApqK2tjX79+jVl0nXZ6EP36lPKKysrhW4AAADa1Odd5mwjNQAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApKSt2Ae3NrFmzIpfLFbsMgJKVzWZjyJAhxS4DAKBNCN0FlsvlhG4AAAAiwunlAAAAkBqhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQErKil1Ae5PN+jsGwPr4nAQANiW++QDQpnK5XMyaNavYZQAAtAkr3QWWy+Uil8sVuwwAAABKgJVuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVlxS6gvclm/R0D4PP4rAQANhVCd4ENGTKk2CUAAABQIoTuAps1a1bkcrlilwFQ0rLZrD9SAgCbBKG7wHK5nNANAABARNhIDQAAAFIjdAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUFP0+3R9++GGsXLkyIiL69+9f5GoAAACgcIoeuo844oh46aWXIpPJRENDQ7HLAQAAgIIpeuiOiEiSpNglAAAAQMG5phsAAABSUhIr3e1JNuvvGACfx2clALCp8K0HAAAAUtLile7Ro0enUsCsWbNS6bdYcrlc5HK5YpcBAABACWhx6J46dWpkMpk0awEAAIB2pdXXdNtpHAAAAFqmxaG7Y8eO0dDQEJlMJr73ve9Fjx49ClLAddddF/PmzStIXwAAAFBKWhy6d91113j++ecjk8nE4YcfHocddlhBCrjnnnuEbgAAANqlFu9ePmLEiKbfn3vuuVSKAQAAgPakxaF7+PDhTb8L3QAAAPD5rHQDAABASlp8TfdOO+0U3bp1i2XLlsW8efPi/fffj2222SbvArbaaqtYsmRJ3v0AAABAqWlx6M5ms3Hrrbc2BeROnToVpIAHH3ywIP0AAABAqWnVfbq/9KUvpVUHAAAAtDstvqYbAAAAaJ1WrXTz+bJZf8cA+Dw+KwGATYVvPQAAAJASK90FlsvlIpfLFbsMAAAASoCVbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASEneofvll18uRB0AAADQ7uQdunfdddfYd99948Ybb4ylS5cWoiYAAABoFzJJkiT5dJDNZiOTyURERHl5eRx77LFx6qmnxj777FOQAj9PbW1tVFVVRU1NTVRWVrbJmOsza9asyOVyxS4DoKRls9kYMmRIscsAANhgLc2iea90d+vWLZIkiSRJor6+Pm666abYf//9Y5dddomrr746Fi1alO8QALQzuVwuZs2aVewyAABSl/dKd319fdxxxx1x0003xbPPPvt/Hf/v6nenTp1i3Lhxceqpp8ahhx6aX7VrUWor3dXV1Va6AVogm83G0KFDi10GAMAGabOV7u7du8c3vvGNePrpp+OVV16Jc845J/r06dO0+r1ixYr4/e9/H4cddlgMGjQo/v3f/z3mzJmT77AAAABQ8gp6y7Add9wxfv7zn8ecOXPizjvvjCOOOCKy2WxTAH/nnXfi4osvjoEDB8aRRx4Z99xzTzQ2NhayBAAAACgZqdynu6ysLMaPHx8PPPBAvPPOO3HJJZfEoEGDmsJ3Y2NjPPTQQzF+/PjYZptt4gc/+EHMnDkzjVIAAACgaFIJ3Wvaeuut41//9V9j1qxZ8Ze//CUmTJgQXbp0aQrg8+bNiyuvvDJ22GGHOPjgg+PWW2+NlStXpl0WAAAApC710L2m0aNHx6233hozZ86MkSNHRsT/bbiWJEk8+eSTceKJJ8bWW28dF110USxZsqQtywMAAICCatPQPW3atDj99NNj2LBhMX369GaBe/X/JkkSCxcujEsvvTS23377eOCBB9qyRAAAACiY1EP3woUL4z//8z9j5513jv322y9uvPHGqKurawrYw4YNi6uuuirefffdmDRpUhx44IER8UkAnz9/fhx99NHNbkUGAAAAG4u879O9NkmSxJ///Oe48cYb47777otVq1Y1PR8R0bVr1/jqV78ap512Wuy3336faf/CCy/Ed7/73Xj66acjIuKLX/xi3HvvvWsdy326ATZO7tMNAGzMWppFywo56Ntvvx033XRT3HzzzU334l4z0++6665x2mmnxde//vWoqqpaZz977LFHPPLII7HddtvF+++/H0899VQhywQAAIA2kXfoXrlyZdx1111x4403xtSpU5tdnx0RUV5eHscee2ycdtppTZuntUTnzp1jzJgx8dvf/jYWL16cb5kAAADQ5vIO3VtttVXTLuNrrmrvvvvucfrpp8fXvva1qKio2KC+e/TokW95AAAAUDR5h+7FixdHJpOJJEmie/fuMWHChDjttNNi+PDheRc3ZMiQOPjgg/Pupy1ls226ITzARsvnJQCwKch7I7VsNht77bVXnH766XH88cdHeXl5oWprkVLbSG3WrFk2UgNogWw2G0OGDCl2GQAAG6TNNlKbMWNG7L777vl2027kcjmhGwAAgIgowH26BW4AAABYOxfUAQAAQEqEbgAAAEhJ3td0n3LKKXm1z2azUVlZGT169Igdd9wxRowYEQMHDsy3LAAAACi6vEP3zTffHJlMphC1NNlnn33i/PPPj6OOOqqg/QIAAEBbKsjp5UmSNPtZ23Otef3ZZ5+No48+Ok499dRClAcAAABFkfdK96RJkyIi4r333otLL700VqxYEZlMJg444IAYOXJkbLPNNtG9e/dYunRpvP/++zF9+vR44oknIkmS6NKlS1xwwQWxxRZbxKJFi+Kll16KBx54IGpqaiLik1X03r17xxVXXJFvmQAAANDmMsnqpec8TJs2LY488shYvHhxHHXUUXHVVVfFgAED1nn8u+++G+ecc05Mnjw5evXqFQ888EDsvffeERGxdOnS+OEPfxjXXHNNRER07NgxXnvttRg0aNBa+2rpDcnbSnV1tft0A7RANpuNoUOHFrsMAIAN0tIsmvfp5YsWLYovf/nLsXjx4pg4cWJMnjx5vYE7IqJ///5x1113xSmnnBILFy5sah8RUV5eHr/4xS/iG9/4RkRENDQ0xE033ZRvmQAAANDm8g7dN9xwQ8yZMycqKiril7/8ZavaXn311VFZWRlz5syJG264odlrl156aXTq1CkiIqZOnZpvmQAAANDm8g7dd911V2QymRg1alR069atVW3Ly8tj1KhRkSRJ/OEPf2j2Wp8+fWLEiBGRJEm89dZb+ZYJAAAAbS7vjdRmz54dERFbbLHFBrXffPPNm/WzpiFDhsRTTz0VixYt2vAC21g2W5AN4QHaPZ+XAMCmIO9vPPX19RER8eGHH25Q+3nz5jXrZ01dunRp9r8AtB+5XC5mzZpV7DIAAFKV90r3VlttFbNnz44pU6ZEfX19dO/evcVt6+rqYsqUKZHJZGKrrbb6zOurN1fr3bt3vmW2mVwuZ/dyAAAAIqIAK92jRo2KiE9Wqs8888xWtf3Od74TdXV1ERFxyCGHfOb1V155JTKZTNMp6AAAALAxyTt0f/Ob32y6Lu93v/tdfPGLX4w333xzvW3eeuutOOqoo+J3v/tdRERkMpk444wzmh0zZ86cePXVVyMiYtddd823TAAAAGhzeZ9ePmLEiDjnnHPi5z//eWQymXjwwQfjwQcfjL333jtGjhwZ/fr1i27dusWyZcvi/fffj2nTpsX06dMjSZJIkiQiIs4+++wYMWJEs34nTZoUSZJEJpOJQw89NN8yAQAAoM3lHbojIq688spobGyMq666qum56dOnx/Tp09d6/OqwHRFx1llnxc9+9rPPHNOzZ8+4+OKLIyLiyCOPLESZAAAA0KYyyZoJOE+PPPJIXHDBBesM22saMWJEXHrppXmvYtfW1kZVVVXU1NREZWVlXn0VQnV1tY3UAFoom83G0KFDi10GAECrtTSLFmSle7UxY8bEmDFj4tVXX42pU6fGiy++GPPnz2/a1bx3796x++67xyGHHBI77bRTIYcGAACAklPQ0L3asGHDYtiwYWl0DQAAABuNvHcvBwAAANZO6AYAAICUpHJ6ecQnG4rNmDEjFixYEHV1dVFRURG9e/eOPffc06Y5AAAAbBIKGrpra2vjF7/4RVx33XXxwQcfrPO4vn37xhlnnBHf/e53S2LHcQAAAEhDwW4Z9swzz8SECRPivffei5Z0mclkon///nH77bfHPvvss8Hjltotw2bNmuWWYQAtlM1mY8iQIcUuAwCg1dr0lmHPP/98HHbYYbF06dKm51bfe3XgwIFRXl4eS5cujbfffrvZfazfeeedGDt2bEydOjX23HPPQpQCAAAAJSPv0N3Q0BDHH3981NfXR0REVVVV/Mu//EucfPLJ0bt3788cv3Dhwpg0aVL85Cc/iZqamqivr4/jjz8+XnnllejQoUO+5RRdLpez0g0AAEBEFGD38ltvvTVmzpwZmUwmBg8eHC+++GKcd955aw3cERG9evWKc889N1544YUYPHhwRETMnDkzbr311nxLAQAAgJKSd+i+9957m37/7//+7xgwYECL2g0YMCBuv/32yGQyERExefLkfEsBAACAkpJ36J4xY0ZkMpkYOXJkq6/L3muvvWLkyJGRJEm88MIL+ZYCAAAAJSXv0P3RRx9FRMSwYcM2qP3qdqv7AQAAgPYi79DdsWPHiIhYsWLFBrVfuXJls34AAACgvcg7dG+55ZaRJElMmzZtg9qvbrflllvmWwoAAACUlLxD9wEHHBAREW+++WbceeedrWr7hz/8oWnn89X9AAAAQHuRd+g+9thjm34/9dRT46GHHmpRu4cffjhOOeWUtfYDAAAA7UHeoXvs2LExevToSJIk6uvr48gjj4xjjjkm7rvvvli4cGGzYxctWhT3339/fPnLX47DDz886uvrI5PJxOjRo2Ps2LH5lgIAAAAlJZMkSZJvJ/Pnz49999033nrrrU86/d97b0dEdO3aNcrLy2Pp0qWxfPnypudXDztkyJB46qmnok+fPhs0dm1tbVRVVUVNTU1UVlbm8S4Ko7q6OnK5XLHLANgoZLPZGDp0aLHLAABotZZm0bxXuiMi+vTpE08//XQcfvjhEfFJoF79s2zZspg/f34sW7as2fMREUcccUQ8+eSTGxy4AQAAoJSVFaqjzTffPB588MGYMmVKXH/99TFlypS13nt78803j1GjRsU3v/nNOOSQQwo1fMnIZgvydwyATYLPTACgvStY6F5t1KhRMWrUqIiImDt3bsyfPz/q6+uje/fu0adPn+jbt2+hhwQAAICSVPDQvaa+fftuciE7l8u5phsAAICIKNA13QAAAMBnCd0AAACQEqEbAAAAUtKia7pHjx6ddh2RyWTikUceSX0cAAAAaCstCt1Tp06NTCaTWhFJkqTaPwAAABRDi3cvT5IkzToAAACg3WlR6J4yZUradQAAAEC706LQffDBB6ddBwAAALQ7di8HAACAlAjdAAAAkBKhGwAAAFLS4t3LW2PmzJkxZcqUmDFjRixYsCDq6uqioqIievfuHXvuuWeMGjUqtttuuzSGLrps1t8xAFrKZyYA0N4VNHQ/99xz8cMf/rBFu52PHj06Lrvsshg+fHghSwAAAICSUbDQ/ctf/jLOPffcaGhoaNE9vR955JHYf//942c/+1l897vfLVQZRZfL5SKXyxW7DAAAAEpAQUL3LbfcEmeddVZkMpmmwL3LLrvE/vvvHwMHDozy8vJYunRpvP322/H000/HSy+9FBERq1atirPPPjt69OgRJ5xwQiFKAQAAgJKRSVqyLL0eixYtiiFDhsSSJUsiImLEiBFxzTXXxIgRI9bZ5q9//Wt897vfjWnTpkVERI8ePeLNN9+Mnj17tnr82traqKqqipqamqisrNyg91BI1dXVVroBWiibzcbQoUOLXQYAQKu1NIvmvYPNDTfcEEuWLIlMJhOHHXZYPPHEE+sN3BERw4cPj8cffzwOO+ywiIioqamJG264Id9SAAAAoKTkHbr/9Kc/RUREp06d4re//W106tSpRe06duwYN998c3Tu3DkiIh544IF8SwEAAICSknforq6ujkwmE6NGjYrNN9+8VW232GKLGDVqVCRJEtXV1fmWAgAAACUl79C9cOHCiIjo16/fBrVf3W7RokX5lgIAAAAlJe/QXVFREREbHpoXL17crB8AAABoL/IO3f369YskSWLq1KnR0NDQqrarVq2KKVOmRCaT2eCVcgAAAChVeYfuQw89NCI+Wen+0Y9+1Kq2//Zv/9Z0evqYMWPyLQUAAABKSt6he+LEidGhQ4eIiLjsssviBz/4QaxYsWK9bVauXBkXXHBBXHrppRER0aFDhzjllFPyLQUAAABKSlm+HQwbNiy+9a1vxTXXXBOZTCauvPLKuOWWW2LChAmx3377xYABA6K8vDyWLl0a7777bjz99NNxxx13xAcffBBJkkQmk4lvfetbseOOOxbi/QAAAEDJyCRJkuTbSWNjYxxzzDFx3333RSaTaQrT67LmkEcddVTcfffdkc1u2KJ7bW1tVFVVRU1NTVRWVm5QH4U0a9asyOVyxS4DYKOQzWZjyJAhxS4DAKDVWppF8z69POKT08PvueeeuPzyy6O8vDwiPgnW6/qJiOjevXtcccUVMXny5A0O3ABs3HK5XMyaNavYZQAApKYgK91rqquri9tuuy0effTReOGFF2L+/PlRX18f3bt3jz59+sQee+wRo0ePjuOPP74gtwkrtZXu6upqK90ArZDNZmPo0KHFLgMAoFVamkULHrrbmtANsHETugGAjVGbnl4OAAAAfJbQDQAAACkRugEAACAled+ne22WLl0ab7/9dtTW1saqVata3O6ggw5KoxwAAAAoioKF7rq6urj66qvjjjvuiNdffz1auz9bJpOJhoaGQpUDAAAARVeQ0D19+vQYN25czJs3LyKi1YEbAAAA2qO8Q/ecOXNi7NixUVtb2/Rcp06dYvDgwbHZZptFWVkqZ7ADAABAycs7EV922WVRW1sbmUwmtthii/jZz34WxxxzTHTp0qUQ9QEAAMBGK+/Q/dBDD0VERMeOHeORRx6JHXfcMe+iAAAAoD3I+5Zhc+bMiUwmE6NHjxa4AQAAYA15r3T37Nkz5s2bF/379y9EPRu9bNatzwFaw+cmANCe5R26Bw8eHPPmzYuFCxcWop6N3pAhQ4pdAgAAACUi79B93HHHxVNPPRWPP/54NDQ0bPK7lc+aNStyuVyxywDYaGSzWX+wBADarbwT8sSJE+Oyyy6LDz74IC6//PL413/910LUtdHK5XJCNwAAABFRgI3UysvLY/LkydG9e/f40Y9+FP/2b/8WDQ0NhagNAAAANmqZJEmSQnT0+uuvxwknnBAzZsyILbbYIr74xS/GTjvtFFVVVZHJZFrUx4knntjqcWtra6OqqipqamqisrKy1e0Lrbq62ko3QCtks9kYOnRoscsAAGiVlmbRgl2A3blz59h5553j+eefjw8//DBuuOGGVrXPZDIbFLoBAACgVBUkdP/P//xPHHPMMbF8+fKmVe0CLaADAADARivv0P3aa6/Fl770pVixYkXTc/3794+dd945evbsucnvZg4AAMCmK+9EfPnll8eKFSsik8nE9ttvHzfccEPst99+hagNAAAANmp5h+5HH300IiK6desWf/nLX6Jv3755FwUAAADtQd63DPvoo48ik8nEmDFjBG4AAABYQ96hu1evXhERseWWW+ZdDAAAALQneYfu7bffPiIiPvzww7yLAQAAgPYk79B93HHHRZIk8dhjj8XSpUsLURMAAAC0C3lvpDZx4sS49tpr4+9//3uce+65ce211xairo1WNpv33zEANik+NwGA9izvbzqdO3eOyZMnx3bbbRfXX399TJw4MebPn1+I2gAAAGCjlkmSJMmng0suuSQiImpqauK//uu/YuXKldGpU6c48MADY+edd46qqqrIZDIt6uuiiy5q9fi1tbVRVVUVNTU1UVlZ2er2hVZdXR25XK7YZQBsNLLZbAwdOrTYZQAAtEpLs2jeoTubzX4mVCdJ0uKgvabGxsZWtxG6ATZuQjcAsDFqaRbN+5ruiE9CdkueW58NCekAAABQyvIO3RdffHEh6gAAAIB2R+gGAACAlLhPCwAAAKRE6AYAAICUCN0AAACQkoLsXv5pdXV18cwzz8SMGTNiwYIFUVdXFxUVFdG7d+/Yc889Y999942Kioo0hgYAAICSUdDQ/e6778Yll1wSt912W6xYsWKdx3Xp0iWOP/74uPDCC6N///6FLAEAAABKRsFOL7/77rtjt912i0mTJsXHH38cSZKs82f58uVx0003xW677RaTJ08uVAkAAABQUgqy0v3QQw/FcccdF42NjZEkSUREbLbZZrH33nvHwIEDo7y8PJYuXRpvv/12PPfcc7Fw4cKIiKipqYnjjjsu7rvvvhg7dmwhSgEAAICSkXfoXrZsWZx66qnR0NAQEREDBw6MK664Io4++ugoK/ts942NjTF58uQ4//zzY/bs2bFq1ao49dRTo7q6Orp27ZpvOUWXzdqbDqA1fG4CAO1Z3t90Jk2aFB988EFkMpkYPnx4zJgxI77yla+sNXBHRHTo0CG+/OUvx4wZM2L48OERETF37tyYNGlSvqUAsBHK5XIxa9asYpcBAJCKvFe677///oj4JEzffvvt0aNHjxa1q6qqittuuy123HHHyOVycd9998W3v/3tfMspulwuF7lcrthlAAAAUALyXul++eWXI5PJxAEHHBCDBw9uVdshQ4bEQQcdFEmSxMsvv5xvKQAAAFBS8g7dCxYsiIhPAvSGWB3UV/cDAAAA7UXeoXv15mf19fUb1H51u/awiRoAAACsKe/Q3bdv30iSJJ544olWt02SJJ588snIZDLRt2/ffEsBAACAkpJ36B41alREfLID+TXXXNOqttdee228//77ERFxyCGH5FsKAAAAlJS8Q/fXv/71pt+///3vx3XXXdeidr/5zW/inHPOaXp8wgkn5FsKAAAAlJS8Q/fIkSPjq1/9aiRJEg0NDXHmmWfGXnvtFb/85S/j+eefjwULFsTy5ctjwYIFMWPGjLjmmmtixIgRccYZZ8SqVasik8nEV7/61Rg5cmQh3g8AAACUjEySJEm+nSxbtixGjRoVzz33XGQymRa1WT3s3nvvHY8++mh069Ztg8aura2NqqqqqKmpicrKyg3qo5Cqq6vdpxuglbLZbAwdOrTYZQAAtFhLs2jeK90REd26dYupU6fGGWecEZlMJpIk+dyfbDYb3/rWt2LKlCkbHLgBAACglBUkdEd8csuv//qv/4rq6uo4//zzY8SIEdGxY8dmx3Ts2DFGjBgR559/flRXV8evfvUrtwoDAACg3SordIeDBg2Kyy67rOlxTU1N1NfXR/fu3aOqqqrQwwEAAEDJKnjo/rSqqqpNKmxnswU7eQBgk+GzEwBor3zLAQAAgJSkvtK9qcnlcnYvBwAAICKsdAMAAEBqWrzSPXr06DTriEwmE4888kiqYwAAAEBbanHonjp1amQymVSKSJIktb4BAACgWFp1TXeSJGnVAQAAAO1Oi0P3xRdf3KLjHnzwwXjuuecik8nERRddtMGFAQAAwMau4KF7wYIF8dxzz7WqDQAAALRHdi8HAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABISavu083ny2b9HQOgtXx2AgDtlW85ABRdLpeLWbNmFbsMAICCs9JdYLlcLnK5XLHLAAAAoARY6QYAAICUCN0AAACQkhafXn7JJZe06Ljp06e3us1qF110UauOBwAAgFKWSZIkacmB2Ww2MplMqsU0Nja2uk1tbW1UVVVFTU1NVFZWplBV61RXV7umG2ADZLPZGDp0aLHLAABokZZm0VZtpNbCfL5B0g70AAAA0NZaHLoPOuggwRgAAABaocWhe+rUqSmWAQAAAO2P3csBAAAgJUI3AAAApEToBgAAgJQI3QAAAJCSVt0yjM+Xzfo7BsCG8PkJALRHvuEAAABASqx0F1gul4tcLlfsMgAAACgBVroBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlJQVu4D2Jpv1dwyADeHzEwBoj3zDAaAk5HK5mDVrVrHLAAAoKCvdBZbL5SKXyxW7DAAAAEqAlW4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJWXFLqC9yWb9HQNgQ/kMBQDaG6EbgJKRy+Wiurp6ra9ls9kYMmRIG1cEAJAfobvAcrlc5HK5YpcBAABACRC6U7Ji1cp4d8HcYpcB0G5kM5lY1SkpdhkAQBEM7jsgunTqUuwyNojQnZJ3F8yNo37yjWKXAQAAsNF7+TePxE4Dty92GRvEjjUAAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApMR9ulPSv3ff+OO/3FDsMgDajWwmEwMHDix2GQBAEQzuO6DYJWwwoTslnTt2iu22GljsMgDajWw2G0MHDi12GQAArSJ0F1g264x9gDT4fAUANkZCd4ENGTKk2CUAAABQIiwbAAAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAMAAEBKhG4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6AYAAICUCN0AAACQEqEbAAAAUiJ0AwAAQEqEbgAAAEiJ0A0AAAApEboBAAAgJUI3AAAApEToBgAAgJQI3QAAAJASoRsAAABSInQDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlJQVu4B8JUkSERG1tbVFrgQAAIBNxeoMujqTrstGH7rr6uoiIqJfv35FrgQAAIBNTV1dXVRVVa3z9UzyebG8xOVyuZg7d25UVFREJpMpdjnrVFtbG/369Yv33nsvKisri10On2J+Spv5KW3mp7SZn9Jnjkqb+Slt5qe0tff5SZIk6urqom/fvpHNrvvK7Y1+pTubzcY222xT7DJarLKysl3+C9demJ/SZn5Km/kpbean9Jmj0mZ+Spv5KW3teX7Wt8K9mo3UAAAAICVCNwAAAKRE6G4jnTt3josvvjg6d+5c7FJYC/NT2sxPaTM/pc38lD5zVNrMT2kzP6XN/Hxio99IDQAAAEqVlW4AAABIidANAAAAKRG6AQAAICVCNwAAAKRE6G4Dv/rVr2LgwIHRpUuXGDlyZEyfPr3YJW2SLrvsshgxYkRUVFTE5ptvHuPGjYs33nij2TEff/xxnHnmmdGrV6/o3r17jB8/PubNm1ekijdtl19+eWQymTj77LObnjM/xTVnzpz4+te/Hr169YquXbvGLrvsEn/961+bXk+SJC666KLYaqutomvXrnHooYfGzJkzi1jxpqWxsTEuvPDC2HbbbaNr164xePDg+Ld/+7dYc79Uc9R2Hn/88fjiF78Yffv2jUwmE/fcc0+z11syF4sWLYqvfe1rUVlZGT169IhTTz016uvr2/BdtF/rm59Vq1bF+eefH7vsskuUl5dH375948QTT4y5c+c268P8pOfz/vtZ0xlnnBGZTCauuuqqZs+bn/S0ZH5ee+21OOqoo6KqqirKy8tjxIgR8e677za9vql9pxO6U/bf//3f8f3vfz8uvvjimDFjRuy2225x2GGHxUcffVTs0jY5jz32WJx55pnx7LPPxsMPPxyrVq2KsWPHxtKlS5uOOeecc+K+++6LO++8Mx577LGYO3duHHPMMUWsetP03HPPxa9//evYddddmz1vfopn8eLFsf/++0fHjh3jT3/6U7z66qvx85//PHr27Nl0zE9/+tP4xS9+Edddd11MmzYtysvL47DDDouPP/64iJVvOq644oq49tpr45prronXXnstrrjiivjpT38av/zlL5uOMUdtZ+nSpbHbbrvFr371q7W+3pK5+NrXvhavvPJKPPzww3H//ffH448/HqeffnpbvYV2bX3zs2zZspgxY0ZceOGFMWPGjLj77rvjjTfeiKOOOqrZceYnPZ/3389qkydPjmeffTb69u37mdfMT3o+b37efPPNOOCAA2KHHXaIqVOnxksvvRQXXnhhdOnSpemYTe47XUKq9t577+TMM89setzY2Jj07ds3ueyyy4pYFUmSJB999FESEcljjz2WJEmSLFmyJOnYsWNy5513Nh3z2muvJRGRPPPMM8Uqc5NTV1eXbLfddsnDDz+cHHzwwclZZ52VJIn5Kbbzzz8/OeCAA9b5ei6XS7bccsvkyiuvbHpuyZIlSefOnZPbb7+9LUrc5B155JHJKaec0uy5Y445Jvna176WJIk5KqaISCZPntz0uCVz8eqrryYRkTz33HNNx/zpT39KMplMMmfOnDarfVPw6flZm+nTpycRkbzzzjtJkpiftrSu+Xn//feTrbfeOnn55ZeTAQMGJP/5n//Z9Jr5aTtrm59jjz02+frXv77ONpvidzor3SlauXJlPP/883HooYc2PZfNZuPQQw+NZ555poiVERFRU1MTERGbbbZZREQ8//zzsWrVqmbztcMOO0T//v3NVxs688wz48gjj2w2DxHmp9j++Mc/xvDhw+MrX/lKbL755rHHHnvEb37zm6bXZ8+eHR9++GGz+amqqoqRI0eanzay3377xSOPPBLV1dUREfG3v/0tnnzyyTjiiCMiwhyVkpbMxTPPPBM9evSI4cOHNx1z6KGHRjabjWnTprV5zZu6mpqayGQy0aNHj4gwP8WWy+XihBNOiPPOOy922mmnz7xufoonl8vFAw88EEOHDo3DDjssNt988xg5cmSzU9A3xe90QneKFixYEI2NjbHFFls0e36LLbaIDz/8sEhVEfHJB8LZZ58d+++/f+y8884REfHhhx9Gp06dmv4PdTXz1XbuuOOOmDFjRlx22WWfec38FNdbb70V1157bWy33Xbx5z//Ob71rW/F9773vfjtb38bEdE0Bz7viucHP/hBHHfccbHDDjtEx44dY4899oizzz47vva1r0WEOSolLZmLDz/8MDbffPNmr5eVlcVmm21mvtrYxx9/HOeff35MmDAhKisrI8L8FNsVV1wRZWVl8b3vfW+tr5uf4vnoo4+ivr4+Lr/88jj88MPjf/7nf+Loo4+OY445Jh577LGI2DS/05UVuwAohjPPPDNefvnlePLJJ4tdCv/rvffei7POOisefvjhZtf8UBpyuVwMHz48fvKTn0RExB577BEvv/xyXHfddXHSSScVuToiIn7/+9/HrbfeGrfddlvstNNO8eKLL8bZZ58dffv2NUewgVatWhVf/epXI0mSuPbaa4tdDvHJKunVV18dM2bMiEwmU+xy+JRcLhcREV/60pfinHPOiYiI3XffPZ5++um47rrr4uCDDy5meUVjpTtFvXv3jg4dOnxmJ7558+bFlltuWaSq+M53vhP3339/TJkyJbbZZpum57fccstYuXJlLFmypNnx5qttPP/88/HRRx/FnnvuGWVlZVFWVhaPPfZY/OIXv4iysrLYYostzE8RbbXVVjFs2LBmz+24445NO5GungOfd8Vz3nnnNa1277LLLnHCCSfEOeec03TmiDkqHS2Ziy233PIzm642NDTEokWLzFcbWR2433nnnXj44YebVrkjzE8xPfHEE/HRRx9F//79m74vvPPOO/FP//RPMXDgwIgwP8XUu3fvKCsr+9zvDJvadzqhO0WdOnWKvfbaKx555JGm53K5XDzyyCOx7777FrGyTVOSJPGd73wnJk+eHI8++mhsu+22zV7fa6+9omPHjs3m64033oh3333XfLWBMWPGxN///vd48cUXm36GDx8eX/va15p+Nz/Fs//++3/mFnvV1dUxYMCAiIjYdtttY8stt2w2P7W1tTFt2jTz00aWLVsW2Wzz/1vv0KFD06qDOSodLZmLfffdN5YsWRLPP/980zGPPvpo5HK5GDlyZJvXvKlZHbhnzpwZf/nLX6JXr17NXjc/xXPCCSfESy+91Oz7Qt++feO8886LP//5zxFhfoqpU6dOMWLEiPV+Z9gkv3MXeye39u6OO+5IOnfunNx8883Jq6++mpx++ulJjx49kg8//LDYpW1yvvWtbyVVVVXJ1KlTkw8++KDpZ9myZU3HnHHGGUn//v2TRx99NPnrX/+a7Lvvvsm+++5bxKo3bWvuXp4k5qeYpk+fnpSVlSWXXnppMnPmzOTWW29NunXrlvzud79rOubyyy9PevTokdx7773JSy+9lHzpS19Ktt1222T58uVFrHzTcdJJJyVbb711cv/99yezZ89O7r777qR3797JP//zPzcdY47aTl1dXfLCCy8kL7zwQhIRyX/8x38kL7zwQtPu1y2Zi8MPPzzZY489kmnTpiVPPvlkst122yUTJkwo1ltqV9Y3PytXrkyOOuqoZJtttklefPHFZt8ZVqxY0dSH+UnP5/3382mf3r08ScxPmj5vfu6+++6kY8eOyfXXX5/MnDkz+eUvf5l06NAheeKJJ5r62NS+0wndbeCXv/xl0r9//6RTp07J3nvvnTz77LPFLmmTFBFr/Zk0aVLTMcuXL0++/e1vJz179ky6deuWHH300ckHH3xQvKI3cZ8O3eanuO67775k5513Tjp37pzssMMOyfXXX9/s9Vwul1x44YXJFltskXTu3DkZM2ZM8sYbbxSp2k1PbW1tctZZZyX9+/dPunTpkgwaNCi54IILmoUEc9R2pkyZstb/zznppJOSJGnZXCxcuDCZMGFC0r1796SysjI5+eSTk7q6uiK8m/ZnffMze/bsdX5nmDJlSlMf5ic9n/ffz6etLXSbn/S0ZH5uvPHGZMiQIUmXLl2S3XbbLbnnnnua9bGpfafLJEmSpLuWDgAAAJsm13QDAABASoRuAAAASInQDQAAACkRugEAACAlQjcAAACkROgGAACAlAjdAAAAkBKhGwAAAFIidAOQqkwm0/SzLoccckjTMVOnTm274krYzTff3PTPZOLEicUuh/81derUpnk55JBDil0OABsBoRuAdVozDLfmR3CmNc4999ymf3cGDhwYSZJsUD+LFi2Kzp07N/V18803F7ZQANgAQjcAG4Uf/ehHTWHqRz/6UbHLaRWr1ut30kknNf3+zjvvxGOPPbZB/dxxxx2xcuXKiIgoLy+PL3/5ywWpDwDyUVbsAgDYOIwYMSL23nvvFh279dZbp1wN7ckuu+wSe+yxR7zwwgsREXHLLbds0Knbt9xyS9Pv48ePj+7duxeqRADYYEI3AC3yhS98YYNWmDf0VOFN3cSJEzepVfGTTjqpKXTfdddd8atf/Sq6du3a4vbV1dUxbdq0Zv0BQClwejkAUHTHH398dOzYMSIiamtr45577mlV+zVXufv37x+jRo0qZHkAsMGEbgCg6Pr06RNHHHFE0+M1Q/TnSZIkfve73zU9PuGEE9a7Wz4AtCWhG4BUteSWYeuzegf1H//4x03P/fjHP17rrumfPh174sSJn9nJesmSJXH11VfHQQcdFFtvvXWUlZVFJpOJJUuWNGv70UcfxaRJk+Kkk06KPfbYIzbbbLPo2LFj9OjRI3bYYYc4+eST489//vN6a189/sknn9z03G9/+9u11v7pa5hbu/lakiRx5513xoQJE2Lw4MHRvXv36N69ewwePDiOP/74+MMf/tCiU/3Xdvu2RYsWxRVXXBEjRoyI3r17R9euXWPQoEFx6qmnxssvv/y5fbbUmqeEP/zww/Hhhx+2qN1jjz0W77zzTtPjE088sdnrNTU1cfvtt8c3v/nNGDlyZPTu3Ts6deoUlZWVMXjw4JgwYUL8/ve/j1wuV5D3sSG3FWvtfycLFy6Mn//85/EP//AP0a9fv+jSpUv06NEjhg0bFmeeeWb89a9/zeMdAFBIrukGYJPx1FNPxYQJE+K9995b73G/+MUv4vvf/340NjZ+5rWampqoqamJN954I26++eYYPXp0/P73v49evXqlVfbnmjlzZhx77LFN10Sv6a233oq33norbr/99thrr73i97//fQwaNKjFfT/11FNx7LHHxpw5c5o9P3v27Jg9e3b89re/jWuvvTZOO+20vN/HP/7jP8Zmm20WixYtisbGxrjtttvi+9///ue2W3NVfN99942hQ4c2Pb777rvj+OOPjxUrVnym3apVq6Kuri7eeuutuOOOO2K33XaLyZMnx7bbbpv3e0nTr371q7jggguipqam2fMrVqyImpqaeO211+Laa6+Nk08+Oa699tro1KlTkSoFIELoBqDEHX300bHzzjvH9OnT47nnnouIde+kvs8++6yzn1mzZsXZZ58dNTU1UVFREQcddFD07ds3Fi9eHI8//nizY+fOndsUuAcNGhQ77rhj9OnTJ7p06fL/27v/mKrq/w/gT7FAEbxUaDgkNcsBARduYAt/3KnsEg3m1CER5XXlxB+5tJqJcyNzk4VzziU6IRRnVxJtNV0oiGDsSig/LuCPS+mwFJEEkuLyU/F8/rhfTvfCvdwD3qvy7fnY3M7hvt7v+7r34NjrvH8ctLa24tKlS7hy5QoAoLCwEBERESgtLYWLi4tZPxEREXBzc0NtbS3Onj0LAPD19cWCBQsG5Pfqq68O4Vv5l16vh1KpRFNTk/izwMBABAcHY9SoUdDpdLh06RIAoKKiAuHh4SguLjYrTK25fPkykpKSYDAYMHHiRMyZMwcvvPACbt++jcLCQnR2dqK3txerVq1CYGDgoN+/FM7OzoiPj0daWhoAYzFtq+ju7OzE8ePHxfP+G6jdvXtXLLgnT54Mf39/eHl5wdXVFQaDAXq9HpWVlRAEAdXV1Zg7dy6qqqqe6E2Uwaxfvx67d+8Wzz09PfHmm2/Cy8sLXV1d0Ol0uHz5MgRBwIEDB9DQ0ICffvoJTk6c3EhE9MQIREREViiVSgGAAEBITk4eVh997Qf7k2P6PkVFRRZjkpOTh5yLWq0W2zzzzDMCAGHt2rVCW1ubWVxPT4/Q29srnmdmZgpff/21UF9fb7Xv6upqITQ0VOx/27ZtVmMPHjwoxqnVakm5S2nT3d0tyOVyMW7ixInCmTNnBsTl5eUJnp6eYpxCoRB6enos9ml6LVxcXITRo0cLO3fuFO7fv28Wd/PmTSEgIECMnTdvnqTPZcvFixfNfmdqamoGjddoNGb53rt3z+z1EydOCCkpKcK1a9es9lFXVydERkaK/Xz44YdWY4uKisQ4pVI57Jj+pPw/yczMFGPGjx8vZGRkWLyOhYWFgre3txj71VdfScqBiIgcgyPdREQkSW5uLpqbm23GJSUlPZXP6X7w4AFWrFiBPXv2DHitb9fsPh988IHN/oKCglBQUABfX180NjZi7969SEpKwujRo+2Wsy0ajQbV1dUAjJ/h9OnTCAkJGRCnUqmQm5uL8PBwPHjwAJWVlcjOzh6w9rm/7u5u7N+/HytXrhzwmo+PD7KzsxEUFARBEHDu3DncuXMHkyZNeqTPFBYWBj8/P+j1egDG0e4dO3ZYjTedWr5w4UJ4eHiYvR4TE4OYmJhB33PatGk4efIkQkNDUVNTA41Ggx07duC5554b/gexs7a2Nnz66acAjDMC8vPz8cYbb1iMnTdvHs6cOQOFQoGuri6kpqbio48+gqur6+NMmYiI/g/nGhERkSRlZWVIS0uz+c90mvPTZMyYMUhNTbVrnzKZDIsWLQIA3LlzB1evXrVr/7bs379fPF69erXFgrtPWFiY2brrffv22ew/MDDQYsHdJyAgAGFhYQCMG7nZa/Mu0yniR44csbi2HjB+5wUFBRbbDdWzzz6LhIQEAEBXVxe0Wu2w+3KEAwcOiJv9rVmzxmrB3cfPz0/8PlpaWnD69GlHp0hERFZwpJuIiP4TVCrVsEYu7969i9LSUuj1ety7dw/t7e1mu4CbFppVVVUIDAy0S762tLW1mb23lNH5FStWiMV2WVkZ2tvbMW7cOKvxsbGxNvsMCQnBxYsXAQC///67zXgp3nvvPWzevBkPHz5EQ0MDCgoKEBkZOSBOo9GIBbmXl5fFGFOtra0oLS3FlStX0NLSAoPBYLZjeW1trXhcVVVlc4T8ccrNzRWP3333XUlt5s+fL96Y0Wq1WLx4sUNyIyKiwbHoJiIiSZKTk/HFF1886TSG7fXXXx9S/NWrV/H555/j1KlTVkda+5My/d5eampqxLzc3NwQFBRks01wcDDGjRuH9vZ29Pb2orq6GuHh4VbjpdxAMN1w7J9//pGQuW3e3t6IiIhAfn4+AODw4cMWC2rTqeUJCQlWp/bX19dj06ZNOH78uMVdzC15nNdSil9++UU8Tk9Px6FDh2y2qa+vF49t7dhPRESOw6KbiIj+EyZMmCA5Ni8vDwsXLpRcoPVpa2sbalrDZjqN38fHR9LznZ2cnODj4yOO6NoqLGUymc0+TdfD379/32a8VGq1Wiy6f/jhBxgMBri5uYmvm+7K3hdviU6nw4IFC3Dv3r0hvf/jvJa2GAwGs3y++eabIfcx1M9PRET2wzXdRET0nzB27FhJcU1NTYiLixML7ilTpiAlJQVarRYNDQ3o6OjAw4cPIQgCBEFAcnKy2NZ0qrKjGQwG8XiwKeL9mcbaKiylFPKOsmjRIowfPx4A0NHRYfZYMMB8lDskJMTiqHx3dzeWLFkiFpwTJkzAli1bUFRUhFu3bqG9vd3sWh48eFBs+zivpS39n8c9HA8ePLBDJkRENBwc6SYiIjKRkZEhFjlyuRzFxcVi8WfJkxoRNR31bW9vl9zONNbd3d2uOdnT2LFjERsbi8zMTADGKebLly8HYCwgs7OzxVhro9zff/89bty4AcA4Zb2srGzQ3dWf1LW0VeD3v6ny119/PVU7qxMR0eA40k1ERGTi7Nmz4vGWLVsGLbgB4I8//nB0ShaZTpevr68329zNmocPH5qt7fX09HRIbvZiWkyfO3dOzD0vLw9//vknAOP0dmsbi5ley/Xr19t8nJm9rqXplHspI8y2RrI9PDzg4uIinjc2Ng4/OSIieuxYdBMR0YjwuKY6NzQ0iMe2NhLr7e3F+fPnbfbpiNyDgoLEjcPa2trM1jdbU11dLY50jx49GnK53O552dPs2bPx8ssvAzDeMPj2228BmE8tj4qKsrpefyjXEgCKi4sfJV2R6Y2alpYWm/FSrt3MmTPFYym/c0RE9PRg0U1ERCPCmDFjxGN7btjVn5PTv38aOzo6Bo398ccfJY06OiJ3d3d3hIaGiudZWVk22/RN1QaMRdxQ1oI/CaNGjcKyZcvE88OHD+Pvv//GiRMnxJ8N9mzuoVzLiooKlJWVPUK2/5oyZYp4o+X69etm6+8tycnJsdlndHS0eLxv3z5JMxuIiOjpwKKbiIhGBNNHU92+fdth79M3sgrArLjrr6mpCRs2bJDUp6NyT0xMFI/T0tJQU1NjNbaiokJ8ZjMArFq1ym55ONKyZcvEAlav12Pjxo3o6uoCADz//PNmxWh/Uq9lR0cHVq5caaeMjSPdvr6+AIzTyzUajdVYnU6HjIwMm30mJibCw8MDAFBZWYmtW7dKzqe5uVnyY++IiMj+WHQTEdGIEBAQIB7n5+fbZUdnS2JiYsTjlJQUcUqzqcrKSiiVSty6dUvSaLFp7hcuXMDNmzftkmtCQoI4RbynpweRkZEoKioaEFdQUICoqChxfbFCoUB8fLxdcnC0adOmYc6cOeJ5enq6eBwfHw9nZ2erbU2v5aFDh7Bz584Bxef169ehUqlQWVlp15F/03XmmzZtglarHRBz6tQpqFQqScsPZDIZdu3aJZ5v3boVarXa6u+SIAg4f/481qxZg5deegmdnZ3D+BRERGQP3L2ciIhGhJkzZ8LHxwe3bt3CnTt34OvrC5VKBU9PT7FoCQsLQ1xc3CO9j1qtxs6dO/Hbb7+hu7sb77//PrZv3w65XI4xY8bg8uXLKC8vB2Dc3TwyMhKpqamD9unl5YXw8HCUlJSgq6sLcrkcb731FiZNmiROgZ4+fTpWr149pFydnZ2RnZ0NpVKJpqYmNDY2Yv78+ZDL5QgODgYAVFVVobq6WmwzceJEZGdnm2329bRTq9UW11sPNrUcAFQqFebOnYvi4mIIgoDPPvsMaWlpUCgUkMlkuHbtGkpKStDb2wtvb298/PHH2Lhxo11yXrduHfbt24eGhga0trZi7ty5mDVrFnx9fdHV1YXy8nLxeelZWVnizuyDWb58Oerq6rBt2zYAxrXtGo0GwcHB8PX1hZubGwwGA+rr61FVVeWwG1NERDQ0LLqJiGhEcHJywt69e7FkyRL09PSgsbHRbEMtwFiEPWrR7eLigpMnTyIqKgp1dXUAjNOa9Xq9WdysWbNw9OhRSVODAWD37t2YP38+2tra0Nraiu+++87sdaVSOeSiGwD8/Pyg1WrxzjvvQKfTATBumGZaaPdRKBTIycnB9OnTh/w+T1JsbCzWrVtnti7bz88PYWFhNtvm5OTg7bffRmVlJQDgxo0b4mPE+vj7++PYsWO4ePGi3XKWyWQ4efIkIiMj0dzcDEEQoNVqzUa8nZ2dsWvXLqjVaklFNwB8+eWXCAgIwIYNG9DQ0IDe3l5UVFSgoqLCapuZM2eOqJssRET/33B6ORERjRjR0dEoLy9HYmIiXnvtNbi7uztkZ/AZM2ZAp9Nh+/btCA0Nhbu7O1xcXDBlyhRER0fjyJEj+Pnnn+Ht7S25z9DQUNTU1OCTTz5BSEgIZDKZuPu4PfItLy/H0aNHsXTpUkydOhWurq5wdXXF1KlTERcXh2PHjqG8vHzEFdyAcdO4RYsWmf3M1ih3nxdffBElJSXYs2cPZs+eDQ8PDzg7O2Py5MlYsGAB0tPTUVZWBn9/f7vnrVAoUFtbi82bNyMwMBBubm5wdXXFjBkzsHbtWuh0OqxZs2bI/S5duhR1dXXIyspCfHw8XnnlFfH3afz48fDz88PixYuxa9cu/Prrr7hw4YLZI8eIiOjxGiVw+0siIiIiIiIih+BINxEREREREZGDsOgmIiIiIiIichAW3UREREREREQOwqKbiIiIiIiIyEFYdBMRERERERE5CItuIiIiIiIiIgdh0U1ERERERETkICy6iYiIiIiIiByERTcRERERERGRg7DoJiIiIiIiInIQFt1EREREREREDsKim4iIiIiIiMhBWHQTEREREREROQiLbiIiIiIiIiIHYdFNRERERERE5CD/A/gqX9IZ1Gz8AAAAAElFTkSuQmCC",
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",
       "text/plain": [
-       "<Figure size 1000x1000 with 2 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -25723,218 +749,34 @@
     }
    ],
    "source": [
-    "homology_dimensions = (0, 1)\n",
-    "points = manifold_points\n",
-    "num_shuffles = 100\n",
-    "\n",
-    "all_diagrams = compute_diagrams_shuffle(\n",
-    "    points, num_shuffles=num_shuffles, homology_dimensions=homology_dimensions\n",
-    ")\n",
-    "\n",
-    "plot_all_barcodes_with_null(all_diagrams, \"manifold\")\n",
-    "\n",
-    "\n",
-    "diagram = all_diagrams[0]\n",
-    "lifespan = _get_lifespan_from_diagram(diagram)\n",
-    "shuffled_diagrams = all_diagrams[1:]\n",
-    "\n",
-    "betti_numbers = {dim: None for dim in homology_dimensions}\n",
-    "\n",
-    "for dim in homology_dimensions:\n",
-    "    betti_number = []\n",
-    "    for shuffled_diagram in shuffled_diagrams:\n",
-    "        shuffled_lifespan = _get_lifespan_from_diagram(shuffled_diagram)\n",
-    "        significant_features = (lifespan > shuffled_lifespan).astype(int)\n",
-    "        betti_number.append(sum(significant_features))\n",
-    "    betti_numbers[dim] = np.mean(betti_number)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_betti_numbers(diagrams):\n",
-    "    original_diagram = diagrams[0]\n",
-    "    shuffled_diagrams = diagrams[1:]\n",
-    "\n",
-    "    dims = np.unique(original_diagram[:, 2]).astype(int)\n",
-    "\n",
-    "    betti_numbers = {dim: None for dim in dims}\n",
-    "    for i, dim in enumerate(dims):\n",
-    "        diagram_dim = original_diagram[original_diagram[:, 2] == dim]\n",
-    "        null_diagram_dim = shuffled_diagrams[:, :, 2] == dim\n",
-    "        null_diagram = shuffled_diagrams[null_diagram_dim]\n",
-    "\n",
-    "        null_lifespans_dim = _get_lifespan_from_diagram(null_diagram)\n",
-    "        lifespans_dim = _get_lifespan_from_diagram(diagram_dim)\n",
-    "\n",
-    "        comparison = (lifespans_dim > null_lifespans_dim).astype(int)\n",
-    "\n",
-    "        betti_numbers[dim] = sum(comparison)\n",
-    "\n",
-    "    return betti_numbers"
+    "plt.plot(immersion_estimator.trainer.train_losses)\n",
+    "plt.plot(immersion_estimator.trainer.test_losses);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 303,
    "metadata": {},
    "outputs": [],
    "source": [
-    "betti = get_betti_numbers(noisy_diagrams)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{0: 0, 1: 5, 2: 2}"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "betti"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Classify circle, sphere, torus point clouds"
+    "immersion_estimator.model.to(\"cpu\")\n",
+    "immersion = immersion_estimator.estimate_"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 269,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import neurometry.datasets.synthetic as synthetic\n",
-    "from neurometry.estimators.topology.persistent_homology import compute_diagrams_shuffle\n",
-    "from gtda.diagrams import PersistenceEntropy\n",
-    "\n",
-    "num_points = 1000\n",
-    "encoding_dim = 10\n",
-    "poisson_multiplier = 100\n",
-    "homology_dimensions = [0, 1, 2]\n",
-    "num_shuffles = 100"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "noise level: 0.71%\n"
-     ]
-    }
-   ],
-   "source": [
-    "circle_task_points = synthetic.hypersphere(1, num_points)\n",
-    "circle_noisy_points, circle_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=circle_task_points,\n",
-    "    encoding_dim=encoding_dim,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(encoding_dim),\n",
-    "    poisson_multiplier=poisson_multiplier,\n",
-    ")\n",
-    "\n",
-    "\n",
-    "circle_noisy_diagrams = compute_diagrams_shuffle(\n",
-    "    circle_noisy_points,\n",
-    "    num_shuffles=num_shuffles,\n",
-    "    homology_dimensions=homology_dimensions,\n",
-    ")\n",
-    "\n",
-    "circle_PE = PersistenceEntropy()\n",
-    "\n",
-    "circle_features = circle_PE.fit_transform(circle_noisy_diagrams)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "noise level: 0.71%\n"
-     ]
-    }
-   ],
-   "source": [
-    "sphere_task_points = synthetic.hypersphere(2, num_points)\n",
-    "sphere_noisy_points, sphere_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=sphere_task_points,\n",
-    "    encoding_dim=encoding_dim,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(encoding_dim),\n",
-    "    poisson_multiplier=poisson_multiplier,\n",
-    ")\n",
-    "\n",
-    "sphere_noisy_diagrams = compute_diagrams_shuffle(\n",
-    "    sphere_noisy_points,\n",
-    "    num_shuffles=num_shuffles,\n",
-    "    homology_dimensions=homology_dimensions,\n",
-    ")\n",
-    "\n",
-    "sphere_PE = PersistenceEntropy()\n",
-    "sphere_features = sphere_PE.fit_transform(sphere_noisy_diagrams)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "noise level: 0.71%\n"
-     ]
-    }
-   ],
-   "source": [
-    "torus_task_points = synthetic.hypertorus(2, num_points)\n",
-    "torus_noisy_points, torus_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=torus_task_points,\n",
-    "    encoding_dim=encoding_dim,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(encoding_dim),\n",
-    "    poisson_multiplier=poisson_multiplier,\n",
-    ")\n",
-    "\n",
-    "torus_noisy_diagrams = compute_diagrams_shuffle(\n",
-    "    torus_noisy_points,\n",
-    "    num_shuffles=num_shuffles,\n",
-    "    homology_dimensions=homology_dimensions,\n",
-    ")\n",
-    "\n",
-    "torus_PE = PersistenceEntropy()\n",
+    "intrinsic_coords = torch.tensor(intrinsic_coords, device=device)\n",
     "\n",
-    "torus_features = torus_PE.fit_transform(torus_noisy_diagrams)"
+    "recon_points = immersion(intrinsic_coords).detach().cpu().numpy().squeeze()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 270,
    "metadata": {},
    "outputs": [
     {
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Points\",\"x\":0.14444444444444446,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"Manifold Points\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"Reconstructed Points\",\"x\":0.8555555555555556,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"}]},                        {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('03175875-422d-41e7-9b4c-8536f45300c5');\n",
+       "var gd = document.getElementById('2366c316-ef43-4649-894b-466ba1279e8f');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -27796,92 +13764,198 @@
     }
    ],
    "source": [
-    "# 3d plot with plotly\n",
-    "fig = go.Figure()\n",
+    "import plotly.graph_objects as go\n",
+    "from plotly.subplots import make_subplots\n",
+    "\n",
+    "# plot manifold points in 3d and recon points in 3d in separate subplots\n",
+    "\n",
+    "colors = intrinsic_coords.detach().cpu().numpy().squeeze()\n",
+    "\n",
+    "fig = make_subplots(\n",
+    "    rows=1,\n",
+    "    cols=3,\n",
+    "    specs=[[{\"type\": \"scatter3d\"}, {\"type\": \"scatter3d\"}, {\"type\": \"scatter3d\"}]],\n",
+    "    subplot_titles=(\"Noisy Points\", \"Manifold Points\", \"Reconstructed Points\"),\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=noisy_points[:, 0],\n",
+    "        y=noisy_points[:, 1],\n",
+    "        z=noisy_points[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=colors),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=1,\n",
+    ")\n",
     "\n",
     "fig.add_trace(\n",
     "    go.Scatter3d(\n",
-    "        x=circle_features[1:, 0],\n",
-    "        y=circle_features[1:, 1],\n",
-    "        z=circle_features[1:, 2],\n",
+    "        x=manifold_points[:, 0],\n",
+    "        y=manifold_points[:, 1],\n",
+    "        z=manifold_points[:, 2],\n",
     "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"lightpink\"),\n",
-    "        name=\"Shuffled Circle\",\n",
-    "    )\n",
+    "        marker=dict(size=3, color=colors),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=2,\n",
     ")\n",
     "\n",
     "fig.add_trace(\n",
     "    go.Scatter3d(\n",
-    "        x=[circle_features[0, 0]],\n",
-    "        y=[circle_features[0, 1]],\n",
-    "        z=[circle_features[0, 2]],\n",
+    "        x=recon_points[:, 0],\n",
+    "        y=recon_points[:, 1],\n",
+    "        z=recon_points[:, 2],\n",
     "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"deeppink\"),\n",
-    "        name=\"Circle\",\n",
-    "    )\n",
+    "        marker=dict(size=3, color=colors),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=3,\n",
     ")\n",
     "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=sphere_features[1:, 0],\n",
-    "        y=sphere_features[1:, 1],\n",
-    "        z=sphere_features[1:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"lightgreen\"),\n",
-    "        name=\"Shuffled Sphere\",\n",
-    "    )\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 305,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from neurometry.estimators.geometry.metric_estimator import NeuralManifoldIntrinsic\n",
+    "\n",
+    "circle_neural_manifold = NeuralManifoldIntrinsic(\n",
+    "    dim=1, neural_embedding_dim=extrinsic_dim, neural_immersion=immersion, equip=True\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 306,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "RuntimeError",
+     "evalue": "The Tensor returned by the function given to hessian should contain a single element",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[306], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m point_a \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39marray([\u001b[38;5;241m0\u001b[39m])\u001b[38;5;241m.\u001b[39munsqueeze(\u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m      2\u001b[0m point_b \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39marray([\u001b[38;5;241m0.5\u001b[39m])\u001b[38;5;241m.\u001b[39munsqueeze(\u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m----> 3\u001b[0m \u001b[43mcircle_neural_manifold\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdist\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpoint_a\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpoint_b\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/riemannian_metric.py:369\u001b[0m, in \u001b[0;36mRiemannianMetric.dist\u001b[0;34m(self, point_a, point_b)\u001b[0m\n\u001b[1;32m    351\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdist\u001b[39m(\u001b[38;5;28mself\u001b[39m, point_a, point_b):\n\u001b[1;32m    352\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Geodesic distance between two points.\u001b[39;00m\n\u001b[1;32m    353\u001b[0m \n\u001b[1;32m    354\u001b[0m \u001b[38;5;124;03m    Note: It only works for positive definite\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    367\u001b[0m \u001b[38;5;124;03m        Distance.\u001b[39;00m\n\u001b[1;32m    368\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 369\u001b[0m     sq_dist \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msquared_dist\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpoint_a\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpoint_b\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    370\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m gs\u001b[38;5;241m.\u001b[39msqrt(sq_dist)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/riemannian_metric.py:347\u001b[0m, in \u001b[0;36mRiemannianMetric.squared_dist\u001b[0;34m(self, point_a, point_b)\u001b[0m\n\u001b[1;32m    332\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msquared_dist\u001b[39m(\u001b[38;5;28mself\u001b[39m, point_a, point_b):\n\u001b[1;32m    333\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Squared geodesic distance between two points.\u001b[39;00m\n\u001b[1;32m    334\u001b[0m \n\u001b[1;32m    335\u001b[0m \u001b[38;5;124;03m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    345\u001b[0m \u001b[38;5;124;03m        Squared distance.\u001b[39;00m\n\u001b[1;32m    346\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 347\u001b[0m     log \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpoint\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpoint_b\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbase_point\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpoint_a\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    349\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msquared_norm(vector\u001b[38;5;241m=\u001b[39mlog, base_point\u001b[38;5;241m=\u001b[39mpoint_a)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/connection.py:135\u001b[0m, in \u001b[0;36mConnection.log\u001b[0;34m(self, point, base_point)\u001b[0m\n\u001b[1;32m    108\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Compute logarithm map associated to the affine connection.\u001b[39;00m\n\u001b[1;32m    109\u001b[0m \n\u001b[1;32m    110\u001b[0m \u001b[38;5;124;03mSolve the boundary value problem associated to the geodesic equation\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    132\u001b[0m \u001b[38;5;124;03m    Tangent vector at the base point.\u001b[39;00m\n\u001b[1;32m    133\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    134\u001b[0m _check_log_solver(\u001b[38;5;28mself\u001b[39m)\n\u001b[0;32m--> 135\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_solver\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpoint\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/geodesic.py:418\u001b[0m, in \u001b[0;36m_LogShootingSolverFlatten.log\u001b[0;34m(self, point, base_point)\u001b[0m\n\u001b[1;32m    413\u001b[0m objective \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m velocity: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_objective(\n\u001b[1;32m    414\u001b[0m     velocity, point, base_point, batch_shape\n\u001b[1;32m    415\u001b[0m )\n\u001b[1;32m    416\u001b[0m init_tangent_vec \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minitialization(point, base_point)\n\u001b[0;32m--> 418\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptimizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mminimize\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobjective\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minit_tangent_vec\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    420\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m gs\u001b[38;5;241m.\u001b[39mreshape(res\u001b[38;5;241m.\u001b[39mx, batch_shape \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_space\u001b[38;5;241m.\u001b[39mshape)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/optimizers.py:93\u001b[0m, in \u001b[0;36mScipyMinimize.minimize\u001b[0;34m(self, fun, x0, fun_jac, fun_hess, hessp)\u001b[0m\n\u001b[1;32m     90\u001b[0m fun_, jac \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handle_jac(fun, fun_jac)\n\u001b[1;32m     91\u001b[0m hess \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handle_hess(fun_hess)\n\u001b[0;32m---> 93\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mscipy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptimize\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mminimize\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     94\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfun_\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     95\u001b[0m \u001b[43m    \u001b[49m\u001b[43mx0\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     96\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     97\u001b[0m \u001b[43m    \u001b[49m\u001b[43mjac\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjac\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     98\u001b[0m \u001b[43m    \u001b[49m\u001b[43mhess\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhess\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     99\u001b[0m \u001b[43m    \u001b[49m\u001b[43mhessp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhessp\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    100\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbounds\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbounds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    101\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtol\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtol\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    102\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconstraints\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconstraints\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    103\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    104\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    105\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    107\u001b[0m result \u001b[38;5;241m=\u001b[39m result_to_backend_type(result)\n\u001b[1;32m    109\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m result\u001b[38;5;241m.\u001b[39mstatus \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_minimize.py:713\u001b[0m, in \u001b[0;36mminimize\u001b[0;34m(fun, x0, args, method, jac, hess, hessp, bounds, constraints, tol, callback, options)\u001b[0m\n\u001b[1;32m    710\u001b[0m     res \u001b[38;5;241m=\u001b[39m _minimize_newtoncg(fun, x0, args, jac, hess, hessp, callback,\n\u001b[1;32m    711\u001b[0m                              \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions)\n\u001b[1;32m    712\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m meth \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124ml-bfgs-b\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[0;32m--> 713\u001b[0m     res \u001b[38;5;241m=\u001b[39m \u001b[43m_minimize_lbfgsb\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjac\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbounds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    714\u001b[0m \u001b[43m                           \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    715\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m meth \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtnc\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m    716\u001b[0m     res \u001b[38;5;241m=\u001b[39m _minimize_tnc(fun, x0, args, jac, bounds, callback\u001b[38;5;241m=\u001b[39mcallback,\n\u001b[1;32m    717\u001b[0m                         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_lbfgsb_py.py:347\u001b[0m, in \u001b[0;36m_minimize_lbfgsb\u001b[0;34m(fun, x0, args, jac, bounds, disp, maxcor, ftol, gtol, eps, maxfun, maxiter, iprint, callback, maxls, finite_diff_rel_step, **unknown_options)\u001b[0m\n\u001b[1;32m    344\u001b[0m         iprint \u001b[38;5;241m=\u001b[39m disp\n\u001b[1;32m    346\u001b[0m \u001b[38;5;66;03m# _prepare_scalar_function can use bounds=None to represent no bounds\u001b[39;00m\n\u001b[0;32m--> 347\u001b[0m sf \u001b[38;5;241m=\u001b[39m \u001b[43m_prepare_scalar_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjac\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjac\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepsilon\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43meps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    348\u001b[0m \u001b[43m                              \u001b[49m\u001b[43mbounds\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbounds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    349\u001b[0m \u001b[43m                              \u001b[49m\u001b[43mfinite_diff_rel_step\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfinite_diff_rel_step\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    351\u001b[0m func_and_grad \u001b[38;5;241m=\u001b[39m sf\u001b[38;5;241m.\u001b[39mfun_and_grad\n\u001b[1;32m    353\u001b[0m fortran_int \u001b[38;5;241m=\u001b[39m _lbfgsb\u001b[38;5;241m.\u001b[39mtypes\u001b[38;5;241m.\u001b[39mintvar\u001b[38;5;241m.\u001b[39mdtype\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_optimize.py:288\u001b[0m, in \u001b[0;36m_prepare_scalar_function\u001b[0;34m(fun, x0, jac, args, bounds, epsilon, finite_diff_rel_step, hess)\u001b[0m\n\u001b[1;32m    284\u001b[0m     bounds \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39minf, np\u001b[38;5;241m.\u001b[39minf)\n\u001b[1;32m    286\u001b[0m \u001b[38;5;66;03m# ScalarFunction caches. Reuse of fun(x) during grad\u001b[39;00m\n\u001b[1;32m    287\u001b[0m \u001b[38;5;66;03m# calculation reduces overall function evaluations.\u001b[39;00m\n\u001b[0;32m--> 288\u001b[0m sf \u001b[38;5;241m=\u001b[39m \u001b[43mScalarFunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgrad\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhess\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    289\u001b[0m \u001b[43m                    \u001b[49m\u001b[43mfinite_diff_rel_step\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbounds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepsilon\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mepsilon\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    291\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m sf\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_differentiable_functions.py:166\u001b[0m, in \u001b[0;36mScalarFunction.__init__\u001b[0;34m(self, fun, x0, args, grad, hess, finite_diff_rel_step, finite_diff_bounds, epsilon)\u001b[0m\n\u001b[1;32m    163\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mf \u001b[38;5;241m=\u001b[39m fun_wrapped(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mx)\n\u001b[1;32m    165\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_update_fun_impl \u001b[38;5;241m=\u001b[39m update_fun\n\u001b[0;32m--> 166\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_update_fun\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    168\u001b[0m \u001b[38;5;66;03m# Gradient evaluation\u001b[39;00m\n\u001b[1;32m    169\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcallable\u001b[39m(grad):\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_differentiable_functions.py:262\u001b[0m, in \u001b[0;36mScalarFunction._update_fun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    260\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_update_fun\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m    261\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mf_updated:\n\u001b[0;32m--> 262\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_update_fun_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    263\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mf_updated \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_differentiable_functions.py:163\u001b[0m, in \u001b[0;36mScalarFunction.__init__.<locals>.update_fun\u001b[0;34m()\u001b[0m\n\u001b[1;32m    162\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mupdate_fun\u001b[39m():\n\u001b[0;32m--> 163\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mf \u001b[38;5;241m=\u001b[39m \u001b[43mfun_wrapped\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_differentiable_functions.py:145\u001b[0m, in \u001b[0;36mScalarFunction.__init__.<locals>.fun_wrapped\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m    141\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnfev \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m    142\u001b[0m \u001b[38;5;66;03m# Send a copy because the user may overwrite it.\u001b[39;00m\n\u001b[1;32m    143\u001b[0m \u001b[38;5;66;03m# Overwriting results in undefined behaviour because\u001b[39;00m\n\u001b[1;32m    144\u001b[0m \u001b[38;5;66;03m# fun(self.x) will change self.x, with the two no longer linked.\u001b[39;00m\n\u001b[0;32m--> 145\u001b[0m fx \u001b[38;5;241m=\u001b[39m \u001b[43mfun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    146\u001b[0m \u001b[38;5;66;03m# Make sure the function returns a true scalar\u001b[39;00m\n\u001b[1;32m    147\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m np\u001b[38;5;241m.\u001b[39misscalar(fx):\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_optimize.py:79\u001b[0m, in \u001b[0;36mMemoizeJac.__call__\u001b[0;34m(self, x, *args)\u001b[0m\n\u001b[1;32m     77\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, x, \u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m     78\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\" returns the function value \"\"\"\u001b[39;00m\n\u001b[0;32m---> 79\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_compute_if_needed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     80\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_value\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/scipy/optimize/_optimize.py:73\u001b[0m, in \u001b[0;36mMemoizeJac._compute_if_needed\u001b[0;34m(self, x, *args)\u001b[0m\n\u001b[1;32m     71\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m np\u001b[38;5;241m.\u001b[39mall(x \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mx) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_value \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mjac \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m     72\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mx \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39masarray(x)\u001b[38;5;241m.\u001b[39mcopy()\n\u001b[0;32m---> 73\u001b[0m     fg \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mjac \u001b[38;5;241m=\u001b[39m fg[\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m     75\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_value \u001b[38;5;241m=\u001b[39m fg[\u001b[38;5;241m0\u001b[39m]\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/optimizers.py:59\u001b[0m, in \u001b[0;36mScipyMinimize._handle_jac.<locals>.fun_\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m     58\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfun_\u001b[39m(x):\n\u001b[0;32m---> 59\u001b[0m     value, grad \u001b[38;5;241m=\u001b[39m \u001b[43mgs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mautodiff\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue_and_grad\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_numpy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     60\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m value, grad\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/_backend/pytorch/autodiff.py:363\u001b[0m, in \u001b[0;36mvalue_and_grad.<locals>.func_with_grad\u001b[0;34m(*inputs, **kwargs)\u001b[0m\n\u001b[1;32m    361\u001b[0m     inputs_\u001b[38;5;241m.\u001b[39mappend(point)\n\u001b[1;32m    362\u001b[0m inputs \u001b[38;5;241m=\u001b[39m inputs_\n\u001b[0;32m--> 363\u001b[0m value \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mrequires_grad_(\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m    365\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m value\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m    366\u001b[0m     sum_value \u001b[38;5;241m=\u001b[39m value\u001b[38;5;241m.\u001b[39msum(axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/geodesic.py:413\u001b[0m, in \u001b[0;36m_LogShootingSolverFlatten.log.<locals>.<lambda>\u001b[0;34m(velocity)\u001b[0m\n\u001b[1;32m    397\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Logarithm map.\u001b[39;00m\n\u001b[1;32m    398\u001b[0m \n\u001b[1;32m    399\u001b[0m \u001b[38;5;124;03mParameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    409\u001b[0m \u001b[38;5;124;03m    Tangent vector at the base point.\u001b[39;00m\n\u001b[1;32m    410\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    411\u001b[0m batch_shape \u001b[38;5;241m=\u001b[39m get_batch_shape(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_space\u001b[38;5;241m.\u001b[39mpoint_ndim, point, base_point)\n\u001b[0;32m--> 413\u001b[0m objective \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m velocity: \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_objective\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    414\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvelocity\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpoint\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_shape\u001b[49m\n\u001b[1;32m    415\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    416\u001b[0m init_tangent_vec \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minitialization(point, base_point)\n\u001b[1;32m    418\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptimizer\u001b[38;5;241m.\u001b[39mminimize(objective, init_tangent_vec)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/geodesic.py:373\u001b[0m, in \u001b[0;36m_LogShootingSolver._objective\u001b[0;34m(self, flat_tangent_vec, point, base_point, batch_shape)\u001b[0m\n\u001b[1;32m    357\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Objective function.\u001b[39;00m\n\u001b[1;32m    358\u001b[0m \n\u001b[1;32m    359\u001b[0m \u001b[38;5;124;03mMinimizes Euclidean distance to shooted point.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    370\u001b[0m \u001b[38;5;124;03m    Batch shape.\u001b[39;00m\n\u001b[1;32m    371\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    372\u001b[0m tangent_vec \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39mreshape(flat_tangent_vec, batch_shape \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_space\u001b[38;5;241m.\u001b[39mshape)\n\u001b[0;32m--> 373\u001b[0m delta \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_space\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexp\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtangent_vec\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m-\u001b[39m point\n\u001b[1;32m    374\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m gs\u001b[38;5;241m.\u001b[39msum(delta\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m2\u001b[39m)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/connection.py:105\u001b[0m, in \u001b[0;36mConnection.exp\u001b[0;34m(self, tangent_vec, base_point)\u001b[0m\n\u001b[1;32m     90\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Exponential map associated to the affine connection.\u001b[39;00m\n\u001b[1;32m     91\u001b[0m \n\u001b[1;32m     92\u001b[0m \u001b[38;5;124;03mParameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    102\u001b[0m \u001b[38;5;124;03m    Point on the manifold.\u001b[39;00m\n\u001b[1;32m    103\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    104\u001b[0m _check_exp_solver(\u001b[38;5;28mself\u001b[39m)\n\u001b[0;32m--> 105\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexp_solver\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexp\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtangent_vec\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/geodesic.py:125\u001b[0m, in \u001b[0;36mExpODESolver.exp\u001b[0;34m(self, tangent_vec, base_point)\u001b[0m\n\u001b[1;32m    110\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mexp\u001b[39m(\u001b[38;5;28mself\u001b[39m, tangent_vec, base_point):\n\u001b[1;32m    111\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Exponential map.\u001b[39;00m\n\u001b[1;32m    112\u001b[0m \n\u001b[1;32m    113\u001b[0m \u001b[38;5;124;03m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    123\u001b[0m \u001b[38;5;124;03m        Point on the manifold.\u001b[39;00m\n\u001b[1;32m    124\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 125\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_solve\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtangent_vec\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    126\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_simplify_exp_result(result)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/geodesic.py:106\u001b[0m, in \u001b[0;36mExpODESolver._solve\u001b[0;34m(self, tangent_vec, base_point, t_eval)\u001b[0m\n\u001b[1;32m    104\u001b[0m force \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m state, _: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_space\u001b[38;5;241m.\u001b[39mmetric\u001b[38;5;241m.\u001b[39mgeodesic_equation(state)\n\u001b[1;32m    105\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m t_eval \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 106\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mintegrator\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mintegrate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mforce\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minitial_state\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    108\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mintegrator\u001b[38;5;241m.\u001b[39mintegrate_t(force, initial_state, t_eval)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/ivp.py:177\u001b[0m, in \u001b[0;36mGSIVPIntegrator.integrate\u001b[0;34m(self, force, initial_state, end_time)\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mintegrate\u001b[39m(\u001b[38;5;28mself\u001b[39m, force, initial_state, end_time\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1.0\u001b[39m):\n\u001b[1;32m    162\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Integrate force.\u001b[39;00m\n\u001b[1;32m    163\u001b[0m \n\u001b[1;32m    164\u001b[0m \u001b[38;5;124;03m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    175\u001b[0m \u001b[38;5;124;03m    result : OdeResult\u001b[39;00m\n\u001b[1;32m    176\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 177\u001b[0m     states \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_integrate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mforce\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minitial_state\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mend_time\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mend_time\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    179\u001b[0m     ts \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0.0\u001b[39m, end_time, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_steps \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m    180\u001b[0m     nfev \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_n_fevals(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_steps)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/ivp.py:154\u001b[0m, in \u001b[0;36mGSIVPIntegrator._integrate\u001b[0;34m(self, force, initial_state, end_time)\u001b[0m\n\u001b[1;32m    151\u001b[0m current_state \u001b[38;5;241m=\u001b[39m initial_state\n\u001b[1;32m    153\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_steps):\n\u001b[0;32m--> 154\u001b[0m     current_state \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    155\u001b[0m \u001b[43m        \u001b[49m\u001b[43mforce\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcurrent_state\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtime\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mdt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdt\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdt\u001b[49m\n\u001b[1;32m    156\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    157\u001b[0m     states\u001b[38;5;241m.\u001b[39mappend(current_state)\n\u001b[1;32m    159\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m states\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/ivp.py:142\u001b[0m, in \u001b[0;36mGSIVPIntegrator._step\u001b[0;34m(self, force, state, time, dt)\u001b[0m\n\u001b[1;32m    141\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_step\u001b[39m(\u001b[38;5;28mself\u001b[39m, force, state, time, dt):\n\u001b[0;32m--> 142\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_step_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43mforce\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtime\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdt\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/integrator.py:56\u001b[0m, in \u001b[0;36meuler_step\u001b[0;34m(force, state, time, dt)\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21meuler_step\u001b[39m(force, state, time, dt):\n\u001b[1;32m     37\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Compute one step of the euler approximation.\u001b[39;00m\n\u001b[1;32m     38\u001b[0m \n\u001b[1;32m     39\u001b[0m \u001b[38;5;124;03m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     54\u001b[0m \u001b[38;5;124;03m        Variables at time t + dt.\u001b[39;00m\n\u001b[1;32m     55\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m---> 56\u001b[0m     derivatives \u001b[38;5;241m=\u001b[39m \u001b[43mforce\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtime\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     57\u001b[0m     new_state \u001b[38;5;241m=\u001b[39m state \u001b[38;5;241m+\u001b[39m derivatives \u001b[38;5;241m*\u001b[39m dt\n\u001b[1;32m     58\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m new_state\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/numerics/geodesic.py:104\u001b[0m, in \u001b[0;36mExpODESolver._solve.<locals>.<lambda>\u001b[0;34m(state, _)\u001b[0m\n\u001b[1;32m    101\u001b[0m state_axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m-\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_space\u001b[38;5;241m.\u001b[39mpoint_ndim \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m    102\u001b[0m initial_state \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39mstack([base_point, tangent_vec], axis\u001b[38;5;241m=\u001b[39mstate_axis)\n\u001b[0;32m--> 104\u001b[0m force \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m state, _: \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_space\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgeodesic_equation\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    105\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m t_eval \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    106\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mintegrator\u001b[38;5;241m.\u001b[39mintegrate(force, initial_state)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/connection.py:84\u001b[0m, in \u001b[0;36mConnection.geodesic_equation\u001b[0;34m(self, state)\u001b[0m\n\u001b[1;32m     82\u001b[0m position \u001b[38;5;241m=\u001b[39m state[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m0\u001b[39m, :]\n\u001b[1;32m     83\u001b[0m velocity \u001b[38;5;241m=\u001b[39m state[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m1\u001b[39m, :]\n\u001b[0;32m---> 84\u001b[0m gamma \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchristoffels\u001b[49m\u001b[43m(\u001b[49m\u001b[43mposition\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     85\u001b[0m equation \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39meinsum(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m...kij,...i->...kj\u001b[39m\u001b[38;5;124m\"\u001b[39m, gamma, velocity)\n\u001b[1;32m     86\u001b[0m equation \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m-\u001b[39mgs\u001b[38;5;241m.\u001b[39meinsum(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m...kj,...j->...k\u001b[39m\u001b[38;5;124m\"\u001b[39m, equation, velocity)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/riemannian_metric.py:158\u001b[0m, in \u001b[0;36mRiemannianMetric.christoffels\u001b[0;34m(self, base_point)\u001b[0m\n\u001b[1;32m    133\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Compute Christoffel symbols of the Levi-Civita connection.\u001b[39;00m\n\u001b[1;32m    134\u001b[0m \n\u001b[1;32m    135\u001b[0m \u001b[38;5;124;03mThe Koszul formula defining the Levi-Civita connection gives the\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    155\u001b[0m \u001b[38;5;124;03m    Christoffel symbols, where the contravariant index is first.\u001b[39;00m\n\u001b[1;32m    156\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    157\u001b[0m cometric_mat_at_point \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcometric_matrix(base_point)\n\u001b[0;32m--> 158\u001b[0m metric_derivative_at_point \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minner_product_derivative_matrix\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    160\u001b[0m term_1 \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39meinsum(\n\u001b[1;32m    161\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m...lk,...jli->...kij\u001b[39m\u001b[38;5;124m\"\u001b[39m, cometric_mat_at_point, metric_derivative_at_point\n\u001b[1;32m    162\u001b[0m )\n\u001b[1;32m    163\u001b[0m term_2 \u001b[38;5;241m=\u001b[39m gs\u001b[38;5;241m.\u001b[39meinsum(\n\u001b[1;32m    164\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m...lk,...lij->...kij\u001b[39m\u001b[38;5;124m\"\u001b[39m, cometric_mat_at_point, metric_derivative_at_point\n\u001b[1;32m    165\u001b[0m )\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/pullback_metric.py:129\u001b[0m, in \u001b[0;36mPullbackMetric.inner_product_derivative_matrix\u001b[0;34m(self, base_point)\u001b[0m\n\u001b[1;32m    108\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Compute the inner-product derivative matrix.\u001b[39;00m\n\u001b[1;32m    109\u001b[0m \n\u001b[1;32m    110\u001b[0m \u001b[38;5;124;03mThe derivative of the metrix matrix is given by\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    126\u001b[0m \u001b[38;5;124;03m    is last: :math:`mat_{ijk} = \\partial_k g_{ij}`.\u001b[39;00m\n\u001b[1;32m    127\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    128\u001b[0m jacobian_ai \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_space\u001b[38;5;241m.\u001b[39mjacobian_immersion(base_point)\n\u001b[0;32m--> 129\u001b[0m hessian_aij \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_space\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhessian_immersion\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    130\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m gs\u001b[38;5;241m.\u001b[39meinsum(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m...aki,...aj->...ijk\u001b[39m\u001b[38;5;124m\"\u001b[39m, hessian_aij, jacobian_ai) \u001b[38;5;241m+\u001b[39m gs\u001b[38;5;241m.\u001b[39meinsum(\n\u001b[1;32m    131\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m...akj,...ai->...ijk\u001b[39m\u001b[38;5;124m\"\u001b[39m, hessian_aij, jacobian_ai\n\u001b[1;32m    132\u001b[0m )\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/geometry/base.py:822\u001b[0m, in \u001b[0;36mImmersedSet.hessian_immersion\u001b[0;34m(self, base_point)\u001b[0m\n\u001b[1;32m    809\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhessian_immersion\u001b[39m(\u001b[38;5;28mself\u001b[39m, base_point):\n\u001b[1;32m    810\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Compute the Hessian of the immersion.\u001b[39;00m\n\u001b[1;32m    811\u001b[0m \n\u001b[1;32m    812\u001b[0m \u001b[38;5;124;03m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    820\u001b[0m \u001b[38;5;124;03m        Hessian at the base point\u001b[39;00m\n\u001b[1;32m    821\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 822\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mgs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mautodiff\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhessian_vec\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    823\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimmersion\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc_out_ndim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43membedding_space\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdim\u001b[49m\n\u001b[1;32m    824\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbase_point\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/_backend/pytorch/autodiff.py:256\u001b[0m, in \u001b[0;36mhessian_vec.<locals>._hessian\u001b[0;34m(point)\u001b[0m\n\u001b[1;32m    253\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m point\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m point_ndim:\n\u001b[1;32m    254\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m hessian_func(point)\n\u001b[1;32m    255\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _torch\u001b[38;5;241m.\u001b[39mstack(\n\u001b[0;32m--> 256\u001b[0m     \u001b[43m[\u001b[49m\u001b[43mhessian_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mone_point\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mone_point\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpoint\u001b[49m\u001b[43m]\u001b[49m,\n\u001b[1;32m    257\u001b[0m     axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m,\n\u001b[1;32m    258\u001b[0m )\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/_backend/pytorch/autodiff.py:256\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    253\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m point\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m point_ndim:\n\u001b[1;32m    254\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m hessian_func(point)\n\u001b[1;32m    255\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _torch\u001b[38;5;241m.\u001b[39mstack(\n\u001b[0;32m--> 256\u001b[0m     [\u001b[43mhessian_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mone_point\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m one_point \u001b[38;5;129;01min\u001b[39;00m point],\n\u001b[1;32m    257\u001b[0m     axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m,\n\u001b[1;32m    258\u001b[0m )\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/_backend/pytorch/autodiff.py:218\u001b[0m, in \u001b[0;36mhessian.<locals>._hessian_vector_valued\u001b[0;34m(point)\u001b[0m\n\u001b[1;32m    214\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mscalar_func\u001b[39m(point, a):\n\u001b[1;32m    215\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m func(point)[a]\n\u001b[1;32m    217\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _torch\u001b[38;5;241m.\u001b[39mstack(\n\u001b[0;32m--> 218\u001b[0m     \u001b[43m[\u001b[49m\n\u001b[1;32m    219\u001b[0m \u001b[43m        \u001b[49m\u001b[43mhessian\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunctools\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpartial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mscalar_func\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43ma\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43ma\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpoint\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    220\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ma\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mfunc_out_ndim\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    221\u001b[0m \u001b[43m    \u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m    222\u001b[0m )\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/_backend/pytorch/autodiff.py:219\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    214\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mscalar_func\u001b[39m(point, a):\n\u001b[1;32m    215\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m func(point)[a]\n\u001b[1;32m    217\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _torch\u001b[38;5;241m.\u001b[39mstack(\n\u001b[1;32m    218\u001b[0m     [\n\u001b[0;32m--> 219\u001b[0m         \u001b[43mhessian\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunctools\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpartial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mscalar_func\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43ma\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43ma\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpoint\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    220\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(func_out_ndim)\n\u001b[1;32m    221\u001b[0m     ]\n\u001b[1;32m    222\u001b[0m )\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/geomstats/_backend/pytorch/autodiff.py:211\u001b[0m, in \u001b[0;36mhessian.<locals>._hessian\u001b[0;34m(point)\u001b[0m\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_hessian\u001b[39m(point):\n\u001b[0;32m--> 211\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_torch_hessian\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpoint\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/torch/autograd/functional.py:956\u001b[0m, in \u001b[0;36mhessian\u001b[0;34m(func, inputs, create_graph, strict, vectorize, outer_jacobian_strategy)\u001b[0m\n\u001b[1;32m    953\u001b[0m     _check_requires_grad(jac, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mjacobian\u001b[39m\u001b[38;5;124m\"\u001b[39m, strict\u001b[38;5;241m=\u001b[39mstrict)\n\u001b[1;32m    954\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m jac\n\u001b[0;32m--> 956\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mjacobian\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    957\u001b[0m \u001b[43m    \u001b[49m\u001b[43mjac_func\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    958\u001b[0m \u001b[43m    \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    959\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcreate_graph\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcreate_graph\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    960\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstrict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstrict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    961\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvectorize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvectorize\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    962\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstrategy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mouter_jacobian_strategy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    963\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    964\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _tuple_postprocess(res, (is_inputs_tuple, is_inputs_tuple))\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/torch/autograd/functional.py:674\u001b[0m, in \u001b[0;36mjacobian\u001b[0;34m(func, inputs, create_graph, strict, vectorize, strategy)\u001b[0m\n\u001b[1;32m    671\u001b[0m is_inputs_tuple, inputs \u001b[38;5;241m=\u001b[39m _as_tuple(inputs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minputs\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mjacobian\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    672\u001b[0m inputs \u001b[38;5;241m=\u001b[39m _grad_preprocess(inputs, create_graph\u001b[38;5;241m=\u001b[39mcreate_graph, need_graph\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m--> 674\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    675\u001b[0m is_outputs_tuple, outputs \u001b[38;5;241m=\u001b[39m _as_tuple(\n\u001b[1;32m    676\u001b[0m     outputs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutputs of the user-provided function\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mjacobian\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    677\u001b[0m )\n\u001b[1;32m    678\u001b[0m _check_requires_grad(outputs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m\"\u001b[39m, strict\u001b[38;5;241m=\u001b[39mstrict)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/torch/autograd/functional.py:952\u001b[0m, in \u001b[0;36mhessian.<locals>.jac_func\u001b[0;34m(*inp)\u001b[0m\n\u001b[1;32m    948\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m outer_jacobian_strategy \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mforward-mode\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    949\u001b[0m     \u001b[38;5;66;03m# _grad_preprocess requires create_graph=True and input to require_grad\u001b[39;00m\n\u001b[1;32m    950\u001b[0m     \u001b[38;5;66;03m# or else the input will be detached\u001b[39;00m\n\u001b[1;32m    951\u001b[0m     inp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(t\u001b[38;5;241m.\u001b[39mrequires_grad_(\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m inp)\n\u001b[0;32m--> 952\u001b[0m jac \u001b[38;5;241m=\u001b[39m \u001b[43mjacobian\u001b[49m\u001b[43m(\u001b[49m\u001b[43mensure_single_output_function\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_graph\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    953\u001b[0m _check_requires_grad(jac, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mjacobian\u001b[39m\u001b[38;5;124m\"\u001b[39m, strict\u001b[38;5;241m=\u001b[39mstrict)\n\u001b[1;32m    954\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m jac\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/torch/autograd/functional.py:674\u001b[0m, in \u001b[0;36mjacobian\u001b[0;34m(func, inputs, create_graph, strict, vectorize, strategy)\u001b[0m\n\u001b[1;32m    671\u001b[0m is_inputs_tuple, inputs \u001b[38;5;241m=\u001b[39m _as_tuple(inputs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minputs\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mjacobian\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    672\u001b[0m inputs \u001b[38;5;241m=\u001b[39m _grad_preprocess(inputs, create_graph\u001b[38;5;241m=\u001b[39mcreate_graph, need_graph\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m--> 674\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    675\u001b[0m is_outputs_tuple, outputs \u001b[38;5;241m=\u001b[39m _as_tuple(\n\u001b[1;32m    676\u001b[0m     outputs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutputs of the user-provided function\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mjacobian\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    677\u001b[0m )\n\u001b[1;32m    678\u001b[0m _check_requires_grad(outputs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m\"\u001b[39m, strict\u001b[38;5;241m=\u001b[39mstrict)\n",
+      "File \u001b[0;32m~/miniconda3/envs/neurometry/lib/python3.11/site-packages/torch/autograd/functional.py:941\u001b[0m, in \u001b[0;36mhessian.<locals>.ensure_single_output_function\u001b[0;34m(*inp)\u001b[0m\n\u001b[1;32m    936\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m    937\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe function given to hessian should return a single Tensor\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    938\u001b[0m     )\n\u001b[1;32m    940\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m out\u001b[38;5;241m.\u001b[39mnelement() \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m--> 941\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m    942\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe Tensor returned by the function given to hessian should contain a single element\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    943\u001b[0m     )\n\u001b[1;32m    945\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\u001b[38;5;241m.\u001b[39msqueeze()\n",
+      "\u001b[0;31mRuntimeError\u001b[0m: The Tensor returned by the function given to hessian should contain a single element"
+     ]
+    }
+   ],
+   "source": [
+    "point_a = gs.array([0]).unsqueeze(0)\n",
+    "point_b = gs.array([0.5]).unsqueeze(0)\n",
+    "circle_neural_manifold.metric.dist(point_a, point_b)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 307,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from geomstats.geometry.pullback_metric import PullbackMetric\n",
+    "\n",
+    "circle_neural_manifold = NeuralManifoldIntrinsic(\n",
+    "    dim=1, neural_embedding_dim=extrinsic_dim, neural_immersion=immersion, equip=False\n",
     ")\n",
+    "circle_neural_manifold.equip_with_metric(PullbackMetric);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Synthetic Torus analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 315,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "task_points, intrinsic_coords = synthetic.hypertorus(2, 1000)\n",
+    "noisy_points, manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=task_points,\n",
+    "    encoding_dim=4,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.array([5, 3, 1, 3]),\n",
+    "    fano_factor=1,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 317,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from neurometry.estimators.geometry.immersion_estimator import ImmersionEstimator\n",
     "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=[sphere_features[0, 0]],\n",
-    "        y=[sphere_features[0, 1]],\n",
-    "        z=[sphere_features[0, 2]],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"darkgreen\"),\n",
-    "        name=\"Sphere\",\n",
-    "    )\n",
-    ")\n",
+    "extrinsic_dim = 4\n",
+    "topology = \"torus\"\n",
+    "device = \"cuda\"\n",
     "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=torus_features[1:, 0],\n",
-    "        y=torus_features[1:, 1],\n",
-    "        z=torus_features[1:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"lightblue\"),\n",
-    "        name=\"Shuffled Torus\",\n",
-    "    )\n",
-    ")\n",
+    "immersion_estimator = ImmersionEstimator(extrinsic_dim, topology, device=device)\n",
     "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=[torus_features[0, 0]],\n",
-    "        y=[torus_features[0, 1]],\n",
-    "        z=[torus_features[0, 2]],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=\"darkblue\"),\n",
-    "        name=\"Torus\",\n",
-    "    )\n",
-    ")"
+    "latents = immersion_estimator.intrinsic_to_extrinsic(intrinsic_coords).squeeze()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 318,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Classifier score: 1.0\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
-       "<style>#sk-container-id-3 {\n",
+       "<style>#sk-container-id-16 {\n",
        "  /* Definition of color scheme common for light and dark mode */\n",
        "  --sklearn-color-text: black;\n",
        "  --sklearn-color-line: gray;\n",
@@ -27911,15 +13985,15 @@
        "  }\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 {\n",
+       "#sk-container-id-16 {\n",
        "  color: var(--sklearn-color-text);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 pre {\n",
+       "#sk-container-id-16 pre {\n",
        "  padding: 0;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "#sk-container-id-16 input.sk-hidden--visually {\n",
        "  border: 0;\n",
        "  clip: rect(1px 1px 1px 1px);\n",
        "  clip: rect(1px, 1px, 1px, 1px);\n",
@@ -27931,7 +14005,7 @@
        "  width: 1px;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "#sk-container-id-16 div.sk-dashed-wrapped {\n",
        "  border: 1px dashed var(--sklearn-color-line);\n",
        "  margin: 0 0.4em 0.5em 0.4em;\n",
        "  box-sizing: border-box;\n",
@@ -27939,7 +14013,7 @@
        "  background-color: var(--sklearn-color-background);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-container {\n",
+       "#sk-container-id-16 div.sk-container {\n",
        "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
        "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
        "     so we also need the `!important` here to be able to override the\n",
@@ -27949,7 +14023,7 @@
        "  position: relative;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "#sk-container-id-16 div.sk-text-repr-fallback {\n",
        "  display: none;\n",
        "}\n",
        "\n",
@@ -27965,14 +14039,14 @@
        "\n",
        "/* Parallel-specific style estimator block */\n",
        "\n",
-       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "#sk-container-id-16 div.sk-parallel-item::after {\n",
        "  content: \"\";\n",
        "  width: 100%;\n",
        "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
        "  flex-grow: 1;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-parallel {\n",
+       "#sk-container-id-16 div.sk-parallel {\n",
        "  display: flex;\n",
        "  align-items: stretch;\n",
        "  justify-content: center;\n",
@@ -27980,28 +14054,28 @@
        "  position: relative;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "#sk-container-id-16 div.sk-parallel-item {\n",
        "  display: flex;\n",
        "  flex-direction: column;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "#sk-container-id-16 div.sk-parallel-item:first-child::after {\n",
        "  align-self: flex-end;\n",
        "  width: 50%;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "#sk-container-id-16 div.sk-parallel-item:last-child::after {\n",
        "  align-self: flex-start;\n",
        "  width: 50%;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "#sk-container-id-16 div.sk-parallel-item:only-child::after {\n",
        "  width: 0;\n",
        "}\n",
        "\n",
        "/* Serial-specific style estimator block */\n",
        "\n",
-       "#sk-container-id-3 div.sk-serial {\n",
+       "#sk-container-id-16 div.sk-serial {\n",
        "  display: flex;\n",
        "  flex-direction: column;\n",
        "  align-items: center;\n",
@@ -28019,14 +14093,14 @@
        "\n",
        "/* Pipeline and ColumnTransformer style (default) */\n",
        "\n",
-       "#sk-container-id-3 div.sk-toggleable {\n",
+       "#sk-container-id-16 div.sk-toggleable {\n",
        "  /* Default theme specific background. It is overwritten whether we have a\n",
        "  specific estimator or a Pipeline/ColumnTransformer */\n",
        "  background-color: var(--sklearn-color-background);\n",
        "}\n",
        "\n",
        "/* Toggleable label */\n",
-       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "#sk-container-id-16 label.sk-toggleable__label {\n",
        "  cursor: pointer;\n",
        "  display: block;\n",
        "  width: 100%;\n",
@@ -28036,7 +14110,7 @@
        "  text-align: center;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "#sk-container-id-16 label.sk-toggleable__label-arrow:before {\n",
        "  /* Arrow on the left of the label */\n",
        "  content: \"▸\";\n",
        "  float: left;\n",
@@ -28044,13 +14118,13 @@
        "  color: var(--sklearn-color-icon);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "#sk-container-id-16 label.sk-toggleable__label-arrow:hover:before {\n",
        "  color: var(--sklearn-color-text);\n",
        "}\n",
        "\n",
        "/* Toggleable content - dropdown */\n",
        "\n",
-       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "#sk-container-id-16 div.sk-toggleable__content {\n",
        "  max-height: 0;\n",
        "  max-width: 0;\n",
        "  overflow: hidden;\n",
@@ -28059,12 +14133,12 @@
        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "#sk-container-id-16 div.sk-toggleable__content.fitted {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "#sk-container-id-16 div.sk-toggleable__content pre {\n",
        "  margin: 0.2em;\n",
        "  border-radius: 0.25em;\n",
        "  color: var(--sklearn-color-text);\n",
@@ -28072,79 +14146,79 @@
        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "#sk-container-id-16 div.sk-toggleable__content.fitted pre {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "#sk-container-id-16 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
        "  /* Expand drop-down */\n",
        "  max-height: 200px;\n",
        "  max-width: 100%;\n",
        "  overflow: auto;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "#sk-container-id-16 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
        "  content: \"▾\";\n",
        "}\n",
        "\n",
        "/* Pipeline/ColumnTransformer-specific style */\n",
        "\n",
-       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-16 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  color: var(--sklearn-color-text);\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-16 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
        "\n",
        "/* Estimator-specific style */\n",
        "\n",
        "/* Colorize estimator box */\n",
-       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-16 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-16 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
-       "#sk-container-id-3 div.sk-label label {\n",
+       "#sk-container-id-16 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-16 div.sk-label label {\n",
        "  /* The background is the default theme color */\n",
        "  color: var(--sklearn-color-text-on-default-background);\n",
        "}\n",
        "\n",
        "/* On hover, darken the color of the background */\n",
-       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "#sk-container-id-16 div.sk-label:hover label.sk-toggleable__label {\n",
        "  color: var(--sklearn-color-text);\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
        "/* Label box, darken color on hover, fitted */\n",
-       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "#sk-container-id-16 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
        "  color: var(--sklearn-color-text);\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
        "\n",
        "/* Estimator label */\n",
        "\n",
-       "#sk-container-id-3 div.sk-label label {\n",
+       "#sk-container-id-16 div.sk-label label {\n",
        "  font-family: monospace;\n",
        "  font-weight: bold;\n",
        "  display: inline-block;\n",
        "  line-height: 1.2em;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-label-container {\n",
+       "#sk-container-id-16 div.sk-label-container {\n",
        "  text-align: center;\n",
        "}\n",
        "\n",
        "/* Estimator-specific */\n",
-       "#sk-container-id-3 div.sk-estimator {\n",
+       "#sk-container-id-16 div.sk-estimator {\n",
        "  font-family: monospace;\n",
        "  border: 1px dotted var(--sklearn-color-border-box);\n",
        "  border-radius: 0.25em;\n",
@@ -28154,18 +14228,18 @@
        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "#sk-container-id-16 div.sk-estimator.fitted {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-0);\n",
        "}\n",
        "\n",
        "/* on hover */\n",
-       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "#sk-container-id-16 div.sk-estimator:hover {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "#sk-container-id-16 div.sk-estimator.fitted:hover {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
@@ -28252,7 +14326,7 @@
        "\n",
        "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
        "\n",
-       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "#sk-container-id-16 a.estimator_doc_link {\n",
        "  float: right;\n",
        "  font-size: 1rem;\n",
        "  line-height: 1em;\n",
@@ -28267,234 +14341,55 @@
        "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "#sk-container-id-16 a.estimator_doc_link.fitted {\n",
        "  /* fitted */\n",
        "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
        "  color: var(--sklearn-color-fitted-level-1);\n",
        "}\n",
        "\n",
        "/* On hover */\n",
-       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "#sk-container-id-16 a.estimator_doc_link:hover {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-unfitted-level-3);\n",
        "  color: var(--sklearn-color-background);\n",
        "  text-decoration: none;\n",
        "}\n",
        "\n",
-       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "#sk-container-id-16 a.estimator_doc_link.fitted:hover {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-3);\n",
        "}\n",
-       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;TopologicalClassifier<span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)</pre></div> </div></div></div></div>"
+       "</style><div id=\"sk-container-id-16\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=4, topology=&#x27;torus&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" checked><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ImmersionEstimator<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=4, topology=&#x27;torus&#x27;)</pre></div> </div></div></div></div>"
       ],
       "text/plain": [
-       "TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "num_points = 500\n",
-    "encoding_dim = 10\n",
-    "poisson_multiplier = 100\n",
-    "\n",
-    "\n",
-    "test_task_points = synthetic.hypertorus(2, 400)\n",
-    "test_noisy_points, test_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=test_task_points,\n",
-    "    encoding_dim=encoding_dim,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(encoding_dim),\n",
-    "    poisson_multiplier=poisson_multiplier,\n",
-    ")\n",
-    "\n",
-    "from neurometry.estimators.topology.persistent_homology import TopologicalClassifier\n",
-    "\n",
-    "num_samples = 10\n",
-    "\n",
-    "TC = TopologicalClassifier(\n",
-    "    num_samples=num_samples, poisson_multiplier=poisson_multiplier, reduce_dim=True\n",
-    ")\n",
-    "TC.fit(test_noisy_points)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([2.])"
+       "ImmersionEstimator(device='cuda', extrinsic_dim=4, topology='torus')"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 318,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "TC.predict(test_noisy_points)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.ensemble import RandomForestClassifier\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn.base import BaseEstimator, ClassifierMixin\n",
-    "\n",
-    "\n",
-    "class TopologicalClassifier(ClassifierMixin, BaseEstimator):\n",
-    "    def __init__(\n",
-    "        self,\n",
-    "        num_samples,\n",
-    "        poisson_multiplier,\n",
-    "        homology_dimensions=[0, 1, 2],\n",
-    "        reduce_dim=False,\n",
-    "    ):\n",
-    "        self.num_samples = num_samples\n",
-    "        self.poisson_multiplier = poisson_multiplier\n",
-    "        self.homology_dimensions = homology_dimensions\n",
-    "        self.reduce_dim = reduce_dim\n",
-    "        self.classifier = RandomForestClassifier()\n",
-    "\n",
-    "    def _generate_ref_data(self, input_data):\n",
-    "        num_points = input_data.shape[0]\n",
-    "        encoding_dim = input_data.shape[1]\n",
-    "        circle_task_points = synthetic.hypersphere(1, num_points)\n",
-    "        circle_point_clouds = []\n",
-    "        for i in range(self.num_samples):\n",
-    "            circle_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
-    "                points=circle_task_points,\n",
-    "                encoding_dim=encoding_dim,\n",
-    "                nonlinearity=\"sigmoid\",\n",
-    "                scales=gs.ones(encoding_dim),\n",
-    "                poisson_multiplier=self.poisson_multiplier,\n",
-    "            )\n",
-    "            circle_point_clouds.append(circle_noisy_points)\n",
-    "\n",
-    "        sphere_task_points = synthetic.hypersphere(2, num_points)\n",
-    "        sphere_point_clouds = []\n",
-    "        for i in range(num_samples):\n",
-    "            sphere_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
-    "                points=sphere_task_points,\n",
-    "                encoding_dim=encoding_dim,\n",
-    "                nonlinearity=\"sigmoid\",\n",
-    "                scales=gs.ones(encoding_dim),\n",
-    "                poisson_multiplier=self.poisson_multiplier,\n",
-    "            )\n",
-    "            sphere_point_clouds.append(sphere_noisy_points)\n",
-    "\n",
-    "        torus_task_points = synthetic.hypertorus(2, num_points)\n",
-    "        torus_point_clouds = []\n",
-    "        for i in range(num_samples):\n",
-    "            torus_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
-    "                points=torus_task_points,\n",
-    "                encoding_dim=encoding_dim,\n",
-    "                nonlinearity=\"sigmoid\",\n",
-    "                scales=gs.ones(encoding_dim),\n",
-    "                poisson_multiplier=self.poisson_multiplier,\n",
-    "            )\n",
-    "            torus_point_clouds.append(torus_noisy_points)\n",
-    "\n",
-    "        klein_bottle_task_points = synthetic.klein_bottle(num_points)\n",
-    "        klein_bottle_point_clouds = []\n",
-    "        for i in range(num_samples):\n",
-    "            klein_bottle_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
-    "                points=klein_bottle_task_points,\n",
-    "                encoding_dim=encoding_dim,\n",
-    "                nonlinearity=\"sigmoid\",\n",
-    "                scales=gs.ones(encoding_dim),\n",
-    "                poisson_multiplier=self.poisson_multiplier,\n",
-    "            )\n",
-    "            klein_bottle_point_clouds.append(klein_bottle_noisy_points)\n",
-    "\n",
-    "        circle_labels = np.zeros(num_samples)\n",
-    "        sphere_labels = np.ones(num_samples)\n",
-    "        torus_labels = 2 * np.ones(num_samples)\n",
-    "        klein_bottle_labels = 3 * np.ones(num_samples)\n",
-    "        ref_labels = np.concatenate(\n",
-    "            [\n",
-    "                circle_labels,\n",
-    "                sphere_labels,\n",
-    "                torus_labels,\n",
-    "                klein_bottle_labels,\n",
-    "            ]\n",
-    "        )\n",
-    "\n",
-    "        ref_point_clouds = [\n",
-    "            *circle_point_clouds,\n",
-    "            *sphere_point_clouds,\n",
-    "            *torus_point_clouds,\n",
-    "            *klein_bottle_point_clouds,\n",
-    "        ]\n",
-    "\n",
-    "        return ref_point_clouds, ref_labels\n",
-    "\n",
-    "    def _compute_topo_features(self, diagrams):\n",
-    "        PE = PersistenceEntropy()\n",
-    "        features = PE.fit_transform(diagrams)\n",
-    "        return features\n",
-    "\n",
-    "    def fit(self, X, y=None):\n",
-    "        ref_point_clouds, ref_labels = self._generate_ref_data(X)\n",
-    "        if self.reduce_dim:\n",
-    "            pca = PCA(n_components=10)\n",
-    "            ref_point_clouds = [\n",
-    "                pca.fit_transform(point_cloud) for point_cloud in ref_point_clouds\n",
-    "            ]\n",
-    "        ref_diagrams = compute_persistence_diagrams(\n",
-    "            ref_point_clouds, homology_dimensions=self.homology_dimensions\n",
-    "        )\n",
-    "        ref_features = self._compute_topo_features(ref_diagrams)\n",
-    "        X_ref_train, X_ref_valid, y_ref_train, y_ref_valid = train_test_split(\n",
-    "            ref_features, ref_labels\n",
-    "        )\n",
-    "        self.classifier.fit(X_ref_train, y_ref_train)\n",
-    "        print(f\"Classifier score: {self.classifier.score(X_ref_valid, y_ref_valid)}\")\n",
-    "        return self\n",
-    "\n",
-    "    def predict(self, X):\n",
-    "        if self.reduce_dim:\n",
-    "            pca = PCA(n_components=10)\n",
-    "            X = pca.fit_transform(X)\n",
-    "        diagram = compute_persistence_diagrams(\n",
-    "            [X], homology_dimensions=self.homology_dimensions\n",
-    "        )\n",
-    "        features = self._compute_topo_features(diagram)\n",
-    "        return self.classifier.predict(features)"
+    "immersion_estimator.fit(X=latents, y=noisy_points)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 320,
    "metadata": {},
    "outputs": [],
    "source": [
-    "test_task_points = synthetic.hypertorus(2, 400)\n",
-    "test_noisy_points, test_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=test_task_points,\n",
-    "    encoding_dim=5,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(10),\n",
-    "    poisson_multiplier=100,\n",
-    ")\n",
+    "immersion = immersion_estimator.estimate_\n",
     "\n",
-    "TC = TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)\n",
-    "TC.fit(test_noisy_points)"
+    "intrinsic_coords = torch.tensor(intrinsic_coords, device=device)\n",
+    "colors = intrinsic_coords.detach().cpu().numpy().squeeze()\n",
+    "recon_points = immersion(intrinsic_coords).detach().cpu().numpy().squeeze()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
+   "execution_count": 321,
    "metadata": {},
    "outputs": [
     {
@@ -28507,257 +14402,12089 @@
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                       {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('da1f5fb7-2f3f-4223-8f41-25598146d0c4');\n",
+       "var gd = document.getElementById('139ee10c-a741-4f7f-a761-bfbd6e6c20f5');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -29609,210 +27336,63 @@
     }
    ],
    "source": [
-    "# Example color mapping\n",
-    "color_map = {0: \"darkblue\", 1: \"deeppink\", 2: \"limegreen\", 3: \"orange\"}\n",
-    "colors = [color_map[label] for label in labels]\n",
-    "\n",
-    "names = {0: \"Circle\", 1: \"Sphere\", 2: \"Torus\", 3: \"Klein Bottle\"}\n",
+    "import plotly.graph_objects as go\n",
+    "from plotly.subplots import make_subplots\n",
+    "from sklearn.decomposition import PCA\n",
     "\n",
-    "# Create a figure\n",
-    "fig = go.Figure()\n",
+    "pca = PCA(n_components=3)\n",
+    "noisy_points_pca = pca.fit_transform(noisy_points)\n",
     "\n",
-    "# Add the trace with colored markers based on labels\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=features[:, 0],\n",
-    "        y=features[:, 1],\n",
-    "        z=features[:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3, color=colors),\n",
-    "        showlegend=False,\n",
-    "    )\n",
-    ")\n",
+    "manifold_points_pca = pca.transform(manifold_points)\n",
     "\n",
-    "# Manually add the legend entries\n",
-    "for label, color in color_map.items():\n",
-    "    fig.add_trace(\n",
-    "        go.Scatter3d(\n",
-    "            x=[None],\n",
-    "            y=[None],\n",
-    "            z=[None],\n",
-    "            mode=\"markers\",\n",
-    "            marker=dict(size=3, color=color),\n",
-    "            showlegend=True,\n",
-    "            name=f\"{names[label]}\",\n",
-    "        )\n",
-    "    )\n",
+    "recon_points_pca = pca.transform(recon_points)\n",
     "\n",
-    "fig.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 110,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.8"
-      ]
-     },
-     "execution_count": 110,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from sklearn.ensemble import RandomForestClassifier\n",
-    "from sklearn.model_selection import train_test_split\n",
+    "colors = colors[:, 1]\n",
     "\n",
-    "X_train, X_valid, y_train, y_valid = train_test_split(features, labels)\n",
-    "model = RandomForestClassifier()\n",
-    "model.fit(X_train, y_train)\n",
-    "model.score(X_valid, y_valid)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "AssertionError",
-     "evalue": "scales must have same shape as tensor",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[9], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m test_task_points \u001b[38;5;241m=\u001b[39m synthetic\u001b[38;5;241m.\u001b[39mhypertorus(\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m400\u001b[39m)\n\u001b[0;32m----> 2\u001b[0m test_noisy_points, test_manifold_points \u001b[38;5;241m=\u001b[39m \u001b[43msynthetic\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msynthetic_neural_manifold\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpoints\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtest_task_points\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoding_dim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnonlinearity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msigmoid\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43mscales\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mones\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpoisson_multiplier\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m     10\u001b[0m TC\u001b[38;5;241m.\u001b[39mfit(test_noisy_points)\n",
-      "File \u001b[0;32m~/neurometry/neurometry/datasets/synthetic.py:42\u001b[0m, in \u001b[0;36msynthetic_neural_manifold\u001b[0;34m(points, encoding_dim, nonlinearity, poisson_multiplier, ref_frequency, **kwargs)\u001b[0m\n\u001b[1;32m     40\u001b[0m encoding_matrix \u001b[38;5;241m=\u001b[39m random_encoding_matrix(manifold_extrinsic_dim, encoding_dim)\n\u001b[1;32m     41\u001b[0m encoded_points \u001b[38;5;241m=\u001b[39m encode_points(points, encoding_matrix)\n\u001b[0;32m---> 42\u001b[0m manifold_points \u001b[38;5;241m=\u001b[39m ref_frequency \u001b[38;5;241m*\u001b[39m \u001b[43mapply_nonlinearity\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     43\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoded_points\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnonlinearity\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m     44\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     45\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m     46\u001b[0m     noisy_points \u001b[38;5;241m=\u001b[39m poisson_spikes(manifold_points, poisson_multiplier)\n",
-      "File \u001b[0;32m~/neurometry/neurometry/datasets/synthetic.py:218\u001b[0m, in \u001b[0;36mapply_nonlinearity\u001b[0;34m(encoded_points, nonlinearity, **kwargs)\u001b[0m\n\u001b[1;32m    216\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m relu(encoded_points, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    217\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m nonlinearity \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msigmoid\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m--> 218\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mscaled_sigmoid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mencoded_points\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    219\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m nonlinearity \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtanh\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    220\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m scaled_tanh(encoded_points, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
-      "File \u001b[0;32m~/neurometry/neurometry/datasets/synthetic.py:231\u001b[0m, in \u001b[0;36mscaled_sigmoid\u001b[0;34m(tensor, scales)\u001b[0m\n\u001b[1;32m    230\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mscaled_sigmoid\u001b[39m(tensor, scales):\n\u001b[0;32m--> 231\u001b[0m     \u001b[38;5;28;01massert\u001b[39;00m tensor\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m==\u001b[39m scales\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mscales must have same shape as tensor\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    232\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m1\u001b[39m \u001b[38;5;241m/\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m+\u001b[39m gs\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mscales \u001b[38;5;241m*\u001b[39m tensor))\n",
-      "\u001b[0;31mAssertionError\u001b[0m: scales must have same shape as tensor"
-     ]
-    }
-   ],
-   "source": [
-    "test_task_points = synthetic.hypertorus(2, 400)\n",
-    "test_noisy_points, test_manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=test_task_points,\n",
-    "    encoding_dim=5,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.ones(10),\n",
-    "    poisson_multiplier=100,\n",
+    "fig = make_subplots(\n",
+    "    rows=1,\n",
+    "    cols=3,\n",
+    "    specs=[[{\"type\": \"scatter3d\"}, {\"type\": \"scatter3d\"}, {\"type\": \"scatter3d\"}]],\n",
     ")\n",
     "\n",
-    "TC.fit(test_noisy_points)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### NOTE: Try different coefficients to distinguish between torus and klein bottle?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 105,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: (19.814, 0.7066852198822331), 1: (13.214, 2.555817677378416)}\n"
-     ]
-    }
-   ],
-   "source": [
-    "betti_numbers = estimate_betti_numbers(\n",
-    "    manifold_points, num_shuffles=500, homology_dimensions=(0, 1)\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=noisy_points_pca[:, 0],\n",
+    "        y=noisy_points_pca[:, 1],\n",
+    "        z=noisy_points_pca[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=colors),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=1,\n",
     ")\n",
-    "print(betti_numbers)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2000x1500 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "num_shuffles = 10\n",
     "\n",
-    "noisy_diagrams = compute_diagrams_shuffle(\n",
-    "    noisy_points, num_shuffles=num_shuffles, homology_dimensions=(0, 1, 2)\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=manifold_points_pca[:, 0],\n",
+    "        y=manifold_points_pca[:, 1],\n",
+    "        z=manifold_points_pca[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=colors),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=2,\n",
     ")\n",
     "\n",
-    "manifold_diagrams = compute_diagrams_shuffle(\n",
-    "    manifold_points, num_shuffles=num_shuffles, homology_dimensions=(0, 1, 2)\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=recon_points_pca[:, 0],\n",
+    "        y=recon_points_pca[:, 1],\n",
+    "        z=recon_points_pca[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=colors),\n",
+    "    ),\n",
+    "    row=1,\n",
+    "    col=3,\n",
     ")\n",
     "\n",
-    "plot_all_barcodes_with_null(\n",
-    "    noisy_diagrams, \"noisy\", diagrams_2=manifold_diagrams, dataset_name_2=\"manifold\"\n",
-    ");"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: 0, 1: 5, 2: 2}\n"
-     ]
-    }
-   ],
-   "source": [
-    "betti = get_betti_numbers(noisy_diagrams)\n",
-    "print(betti)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### TODO: FIX get_betti_numbers FUNCTION!!!!\n",
-    "\n",
-    "Also: how to deal with betti 0 ? There should be a single \"significant\" feature?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sphere_1_betti = {0: 1, 1: 1, 2: 0}\n",
-    "torus_2_betti = {0: 1, 1: 2, 2: 1}\n",
-    "sphere_2_betti = {0: 1, 1: 0, 2: 1}\n",
-    "\n",
-    "# if betti == sphere_1_betti:\n",
-    "#     print(\"The manifold is a ring\") ----> use ring VAE\n",
-    "\n",
-    "\n",
-    "# elif betti == torus_2_betti:"
+    "fig.show()"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": []
   }
  ],
  "metadata": {
diff --git a/tutorials/04_methods_estimate_manifold_immersion.ipynb b/tutorials/04_methods_estimate_manifold_immersion.ipynb
deleted file mode 100644
index 7f24cec..0000000
--- a/tutorials/04_methods_estimate_manifold_immersion.ipynb
+++ /dev/null
@@ -1,9026 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 64,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Working directory:  /home/facosta/neurometry/neurometry\n",
-      "Directory added to path:  /home/facosta/neurometry\n",
-      "Directory added to path:  /home/facosta/neurometry/neurometry\n",
-      "The autoreload extension is already loaded. To reload it, use:\n",
-      "  %reload_ext autoreload\n",
-      "The jupyter_black extension is already loaded. To reload it, use:\n",
-      "  %reload_ext jupyter_black\n"
-     ]
-    }
-   ],
-   "source": [
-    "import setup\n",
-    "\n",
-    "setup.main()\n",
-    "%load_ext autoreload\n",
-    "%autoreload 2\n",
-    "%load_ext jupyter_black\n",
-    "\n",
-    "import neurometry.datasets.synthetic as synthetic\n",
-    "import numpy as np\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "\n",
-    "import os\n",
-    "\n",
-    "os.environ[\"GEOMSTATS_BACKEND\"] = \"pytorch\"\n",
-    "import geomstats.backend as gs"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "task_points, intrinsic_coords = synthetic.hypersphere(1, 1000)\n",
-    "noisy_points, manifold_points = synthetic.synthetic_neural_manifold(\n",
-    "    points=task_points,\n",
-    "    encoding_dim=3,\n",
-    "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.array([5, 3, 1]),\n",
-    ")\n",
-    "\n",
-    "X = manifold_points\n",
-    "labels = intrinsic_coords"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 66,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from neurometry.estimators.geometry.immersion_estimator import ImmersionEstimator"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 67,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "extrinsic_dim = 3\n",
-    "topology = \"circle\"\n",
-    "device = \"cuda\"\n",
-    "\n",
-    "immersion_estimator = ImmersionEstimator(extrinsic_dim, topology, device=device)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 68,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Train Epoch: 1 [0/800 (0%)]\tLoss: 202.562974\n",
-      "====> Train Epoch: 1 Average loss: 188.1801\n",
-      "====> Test Epoch: 1 Average loss: 165.0614\n",
-      "Train Epoch: 2 [0/800 (0%)]\tLoss: 134.526717\n",
-      "====> Train Epoch: 2 Average loss: 74.1690\n",
-      "====> Test Epoch: 2 Average loss: 70.4762\n",
-      "Train Epoch: 3 [0/800 (0%)]\tLoss: 56.325479\n",
-      "====> Train Epoch: 3 Average loss: 47.7297\n",
-      "====> Test Epoch: 3 Average loss: 57.2686\n",
-      "Train Epoch: 4 [0/800 (0%)]\tLoss: 42.957465\n",
-      "====> Train Epoch: 4 Average loss: 44.2286\n",
-      "====> Test Epoch: 4 Average loss: 54.5528\n",
-      "Train Epoch: 5 [0/800 (0%)]\tLoss: 42.971686\n",
-      "====> Train Epoch: 5 Average loss: 44.1926\n",
-      "====> Test Epoch: 5 Average loss: 53.0346\n",
-      "Train Epoch: 6 [0/800 (0%)]\tLoss: 45.222545\n",
-      "====> Train Epoch: 6 Average loss: 43.8985\n",
-      "====> Test Epoch: 6 Average loss: 53.7503\n",
-      "Train Epoch: 7 [0/800 (0%)]\tLoss: 42.859619\n",
-      "====> Train Epoch: 7 Average loss: 43.8415\n",
-      "====> Test Epoch: 7 Average loss: 55.3904\n",
-      "Train Epoch: 8 [0/800 (0%)]\tLoss: 43.091515\n",
-      "====> Train Epoch: 8 Average loss: 43.9621\n",
-      "====> Test Epoch: 8 Average loss: 57.2641\n",
-      "Train Epoch: 9 [0/800 (0%)]\tLoss: 44.604582\n",
-      "====> Train Epoch: 9 Average loss: 43.0592\n",
-      "====> Test Epoch: 9 Average loss: 56.2048\n",
-      "Train Epoch: 10 [0/800 (0%)]\tLoss: 43.722002\n",
-      "====> Train Epoch: 10 Average loss: 41.9819\n",
-      "====> Test Epoch: 10 Average loss: 47.0864\n",
-      "Train Epoch: 11 [0/800 (0%)]\tLoss: 40.527655\n",
-      "====> Train Epoch: 11 Average loss: 32.4589\n",
-      "====> Test Epoch: 11 Average loss: 24.6105\n",
-      "Train Epoch: 12 [0/800 (0%)]\tLoss: 20.672960\n",
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-      "====> Test Epoch: 459 Average loss: 0.4435\n",
-      "Train Epoch: 460 [0/800 (0%)]\tLoss: 0.357999\n",
-      "====> Train Epoch: 460 Average loss: 0.3325\n",
-      "====> Test Epoch: 460 Average loss: 0.3893\n",
-      "Train Epoch: 461 [0/800 (0%)]\tLoss: 0.306467\n",
-      "====> Train Epoch: 461 Average loss: 0.3340\n",
-      "====> Test Epoch: 461 Average loss: 0.4215\n",
-      "Train Epoch: 462 [0/800 (0%)]\tLoss: 0.323375\n",
-      "====> Train Epoch: 462 Average loss: 0.3350\n",
-      "====> Test Epoch: 462 Average loss: 0.4246\n",
-      "Train Epoch: 463 [0/800 (0%)]\tLoss: 0.326692\n",
-      "====> Train Epoch: 463 Average loss: 0.3262\n",
-      "====> Test Epoch: 463 Average loss: 0.4005\n",
-      "Train Epoch: 464 [0/800 (0%)]\tLoss: 0.354387\n",
-      "====> Train Epoch: 464 Average loss: 0.3280\n",
-      "====> Test Epoch: 464 Average loss: 0.4259\n",
-      "Train Epoch: 465 [0/800 (0%)]\tLoss: 0.354573\n",
-      "====> Train Epoch: 465 Average loss: 0.3393\n",
-      "====> Test Epoch: 465 Average loss: 0.4147\n",
-      "Train Epoch: 466 [0/800 (0%)]\tLoss: 0.303800\n",
-      "====> Train Epoch: 466 Average loss: 0.3412\n",
-      "====> Test Epoch: 466 Average loss: 0.4573\n",
-      "Train Epoch: 467 [0/800 (0%)]\tLoss: 0.382437\n",
-      "====> Train Epoch: 467 Average loss: 0.3368\n",
-      "====> Test Epoch: 467 Average loss: 0.4339\n",
-      "Train Epoch: 468 [0/800 (0%)]\tLoss: 0.307622\n",
-      "====> Train Epoch: 468 Average loss: 0.3284\n",
-      "====> Test Epoch: 468 Average loss: 0.4097\n",
-      "Train Epoch: 469 [0/800 (0%)]\tLoss: 0.293374\n",
-      "====> Train Epoch: 469 Average loss: 0.3305\n",
-      "====> Test Epoch: 469 Average loss: 0.4191\n",
-      "Train Epoch: 470 [0/800 (0%)]\tLoss: 0.306203\n",
-      "====> Train Epoch: 470 Average loss: 0.3338\n",
-      "====> Test Epoch: 470 Average loss: 0.4223\n",
-      "Train Epoch: 471 [0/800 (0%)]\tLoss: 0.337388\n",
-      "====> Train Epoch: 471 Average loss: 0.3326\n",
-      "====> Test Epoch: 471 Average loss: 0.3999\n",
-      "Train Epoch: 472 [0/800 (0%)]\tLoss: 0.314001\n",
-      "====> Train Epoch: 472 Average loss: 0.3311\n",
-      "====> Test Epoch: 472 Average loss: 0.4319\n",
-      "Train Epoch: 473 [0/800 (0%)]\tLoss: 0.339449\n",
-      "====> Train Epoch: 473 Average loss: 0.3259\n",
-      "====> Test Epoch: 473 Average loss: 0.4413\n",
-      "Train Epoch: 474 [0/800 (0%)]\tLoss: 0.370001\n",
-      "====> Train Epoch: 474 Average loss: 0.3315\n",
-      "====> Test Epoch: 474 Average loss: 0.4141\n",
-      "Train Epoch: 475 [0/800 (0%)]\tLoss: 0.354314\n",
-      "====> Train Epoch: 475 Average loss: 0.3328\n",
-      "====> Test Epoch: 475 Average loss: 0.4293\n",
-      "Train Epoch: 476 [0/800 (0%)]\tLoss: 0.308028\n",
-      "====> Train Epoch: 476 Average loss: 0.3351\n",
-      "====> Test Epoch: 476 Average loss: 0.4333\n",
-      "Train Epoch: 477 [0/800 (0%)]\tLoss: 0.309831\n",
-      "====> Train Epoch: 477 Average loss: 0.3370\n",
-      "====> Test Epoch: 477 Average loss: 0.4018\n",
-      "Train Epoch: 478 [0/800 (0%)]\tLoss: 0.314408\n",
-      "====> Train Epoch: 478 Average loss: 0.3291\n",
-      "====> Test Epoch: 478 Average loss: 0.4390\n",
-      "Train Epoch: 479 [0/800 (0%)]\tLoss: 0.308332\n",
-      "====> Train Epoch: 479 Average loss: 0.3267\n",
-      "====> Test Epoch: 479 Average loss: 0.3957\n",
-      "Train Epoch: 480 [0/800 (0%)]\tLoss: 0.322499\n",
-      "====> Train Epoch: 480 Average loss: 0.3300\n",
-      "====> Test Epoch: 480 Average loss: 0.3739\n",
-      "Train Epoch: 481 [0/800 (0%)]\tLoss: 0.288729\n",
-      "====> Train Epoch: 481 Average loss: 0.3260\n",
-      "====> Test Epoch: 481 Average loss: 0.4330\n",
-      "Train Epoch: 482 [0/800 (0%)]\tLoss: 0.329343\n",
-      "====> Train Epoch: 482 Average loss: 0.3327\n",
-      "====> Test Epoch: 482 Average loss: 0.4121\n",
-      "Train Epoch: 483 [0/800 (0%)]\tLoss: 0.306637\n",
-      "====> Train Epoch: 483 Average loss: 0.3350\n",
-      "====> Test Epoch: 483 Average loss: 0.4438\n",
-      "Train Epoch: 484 [0/800 (0%)]\tLoss: 0.286781\n",
-      "====> Train Epoch: 484 Average loss: 0.3323\n",
-      "====> Test Epoch: 484 Average loss: 0.4280\n",
-      "Train Epoch: 485 [0/800 (0%)]\tLoss: 0.304832\n",
-      "====> Train Epoch: 485 Average loss: 0.3328\n",
-      "====> Test Epoch: 485 Average loss: 0.4156\n",
-      "Train Epoch: 486 [0/800 (0%)]\tLoss: 0.308274\n",
-      "====> Train Epoch: 486 Average loss: 0.3336\n",
-      "====> Test Epoch: 486 Average loss: 0.4549\n",
-      "Train Epoch: 487 [0/800 (0%)]\tLoss: 0.320666\n",
-      "====> Train Epoch: 487 Average loss: 0.3406\n",
-      "====> Test Epoch: 487 Average loss: 0.4086\n",
-      "Train Epoch: 488 [0/800 (0%)]\tLoss: 0.295135\n",
-      "====> Train Epoch: 488 Average loss: 0.3407\n",
-      "====> Test Epoch: 488 Average loss: 0.4365\n",
-      "Train Epoch: 489 [0/800 (0%)]\tLoss: 0.331129\n",
-      "====> Train Epoch: 489 Average loss: 0.3370\n",
-      "====> Test Epoch: 489 Average loss: 0.3875\n",
-      "Train Epoch: 490 [0/800 (0%)]\tLoss: 0.319115\n",
-      "====> Train Epoch: 490 Average loss: 0.3298\n",
-      "====> Test Epoch: 490 Average loss: 0.4059\n",
-      "Train Epoch: 491 [0/800 (0%)]\tLoss: 0.333036\n",
-      "====> Train Epoch: 491 Average loss: 0.3308\n",
-      "====> Test Epoch: 491 Average loss: 0.4339\n",
-      "Train Epoch: 492 [0/800 (0%)]\tLoss: 0.320206\n",
-      "====> Train Epoch: 492 Average loss: 0.3290\n",
-      "====> Test Epoch: 492 Average loss: 0.4417\n",
-      "Train Epoch: 493 [0/800 (0%)]\tLoss: 0.292040\n",
-      "====> Train Epoch: 493 Average loss: 0.3346\n",
-      "====> Test Epoch: 493 Average loss: 0.4089\n",
-      "Train Epoch: 494 [0/800 (0%)]\tLoss: 0.298197\n",
-      "====> Train Epoch: 494 Average loss: 0.3320\n",
-      "====> Test Epoch: 494 Average loss: 0.4325\n",
-      "Train Epoch: 495 [0/800 (0%)]\tLoss: 0.325547\n",
-      "====> Train Epoch: 495 Average loss: 0.3355\n",
-      "====> Test Epoch: 495 Average loss: 0.4352\n",
-      "Train Epoch: 496 [0/800 (0%)]\tLoss: 0.310787\n",
-      "====> Train Epoch: 496 Average loss: 0.3273\n",
-      "====> Test Epoch: 496 Average loss: 0.4133\n",
-      "Train Epoch: 497 [0/800 (0%)]\tLoss: 0.292689\n",
-      "====> Train Epoch: 497 Average loss: 0.3272\n",
-      "====> Test Epoch: 497 Average loss: 0.4040\n",
-      "Train Epoch: 498 [0/800 (0%)]\tLoss: 0.305203\n",
-      "====> Train Epoch: 498 Average loss: 0.3256\n",
-      "====> Test Epoch: 498 Average loss: 0.4090\n",
-      "Train Epoch: 499 [0/800 (0%)]\tLoss: 0.302636\n",
-      "====> Train Epoch: 499 Average loss: 0.3276\n",
-      "====> Test Epoch: 499 Average loss: 0.4244\n",
-      "Train Epoch: 500 [0/800 (0%)]\tLoss: 0.308832\n",
-      "====> Train Epoch: 500 Average loss: 0.3286\n",
-      "====> Test Epoch: 500 Average loss: 0.3816\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<style>#sk-container-id-4 {\n",
-       "  /* Definition of color scheme common for light and dark mode */\n",
-       "  --sklearn-color-text: black;\n",
-       "  --sklearn-color-line: gray;\n",
-       "  /* Definition of color scheme for unfitted estimators */\n",
-       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
-       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
-       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
-       "  --sklearn-color-unfitted-level-3: chocolate;\n",
-       "  /* Definition of color scheme for fitted estimators */\n",
-       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
-       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
-       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
-       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
-       "\n",
-       "  /* Specific color for light theme */\n",
-       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
-       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
-       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
-       "  --sklearn-color-icon: #696969;\n",
-       "\n",
-       "  @media (prefers-color-scheme: dark) {\n",
-       "    /* Redefinition of color scheme for dark theme */\n",
-       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
-       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
-       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
-       "    --sklearn-color-icon: #878787;\n",
-       "  }\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 {\n",
-       "  color: var(--sklearn-color-text);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 pre {\n",
-       "  padding: 0;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 input.sk-hidden--visually {\n",
-       "  border: 0;\n",
-       "  clip: rect(1px 1px 1px 1px);\n",
-       "  clip: rect(1px, 1px, 1px, 1px);\n",
-       "  height: 1px;\n",
-       "  margin: -1px;\n",
-       "  overflow: hidden;\n",
-       "  padding: 0;\n",
-       "  position: absolute;\n",
-       "  width: 1px;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
-       "  border: 1px dashed var(--sklearn-color-line);\n",
-       "  margin: 0 0.4em 0.5em 0.4em;\n",
-       "  box-sizing: border-box;\n",
-       "  padding-bottom: 0.4em;\n",
-       "  background-color: var(--sklearn-color-background);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-container {\n",
-       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
-       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
-       "     so we also need the `!important` here to be able to override the\n",
-       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
-       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
-       "  display: inline-block !important;\n",
-       "  position: relative;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       "div.sk-parallel-item,\n",
-       "div.sk-serial,\n",
-       "div.sk-item {\n",
-       "  /* draw centered vertical line to link estimators */\n",
-       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
-       "  background-size: 2px 100%;\n",
-       "  background-repeat: no-repeat;\n",
-       "  background-position: center center;\n",
-       "}\n",
-       "\n",
-       "/* Parallel-specific style estimator block */\n",
-       "\n",
-       "#sk-container-id-4 div.sk-parallel-item::after {\n",
-       "  content: \"\";\n",
-       "  width: 100%;\n",
-       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
-       "  flex-grow: 1;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-parallel {\n",
-       "  display: flex;\n",
-       "  align-items: stretch;\n",
-       "  justify-content: center;\n",
-       "  background-color: var(--sklearn-color-background);\n",
-       "  position: relative;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-parallel-item {\n",
-       "  display: flex;\n",
-       "  flex-direction: column;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
-       "  align-self: flex-end;\n",
-       "  width: 50%;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
-       "  align-self: flex-start;\n",
-       "  width: 50%;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
-       "  width: 0;\n",
-       "}\n",
-       "\n",
-       "/* Serial-specific style estimator block */\n",
-       "\n",
-       "#sk-container-id-4 div.sk-serial {\n",
-       "  display: flex;\n",
-       "  flex-direction: column;\n",
-       "  align-items: center;\n",
-       "  background-color: var(--sklearn-color-background);\n",
-       "  padding-right: 1em;\n",
-       "  padding-left: 1em;\n",
-       "}\n",
-       "\n",
-       "\n",
-       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
-       "clickable and can be expanded/collapsed.\n",
-       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
-       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
-       "*/\n",
-       "\n",
-       "/* Pipeline and ColumnTransformer style (default) */\n",
-       "\n",
-       "#sk-container-id-4 div.sk-toggleable {\n",
-       "  /* Default theme specific background. It is overwritten whether we have a\n",
-       "  specific estimator or a Pipeline/ColumnTransformer */\n",
-       "  background-color: var(--sklearn-color-background);\n",
-       "}\n",
-       "\n",
-       "/* Toggleable label */\n",
-       "#sk-container-id-4 label.sk-toggleable__label {\n",
-       "  cursor: pointer;\n",
-       "  display: block;\n",
-       "  width: 100%;\n",
-       "  margin-bottom: 0;\n",
-       "  padding: 0.5em;\n",
-       "  box-sizing: border-box;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
-       "  /* Arrow on the left of the label */\n",
-       "  content: \"▸\";\n",
-       "  float: left;\n",
-       "  margin-right: 0.25em;\n",
-       "  color: var(--sklearn-color-icon);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
-       "  color: var(--sklearn-color-text);\n",
-       "}\n",
-       "\n",
-       "/* Toggleable content - dropdown */\n",
-       "\n",
-       "#sk-container-id-4 div.sk-toggleable__content {\n",
-       "  max-height: 0;\n",
-       "  max-width: 0;\n",
-       "  overflow: hidden;\n",
-       "  text-align: left;\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
-       "  /* fitted */\n",
-       "  background-color: var(--sklearn-color-fitted-level-0);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
-       "  margin: 0.2em;\n",
-       "  border-radius: 0.25em;\n",
-       "  color: var(--sklearn-color-text);\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-fitted-level-0);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
-       "  /* Expand drop-down */\n",
-       "  max-height: 200px;\n",
-       "  max-width: 100%;\n",
-       "  overflow: auto;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
-       "  content: \"▾\";\n",
-       "}\n",
-       "\n",
-       "/* Pipeline/ColumnTransformer-specific style */\n",
-       "\n",
-       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
-       "  color: var(--sklearn-color-text);\n",
-       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
-       "  background-color: var(--sklearn-color-fitted-level-2);\n",
-       "}\n",
-       "\n",
-       "/* Estimator-specific style */\n",
-       "\n",
-       "/* Colorize estimator box */\n",
-       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
-       "  /* fitted */\n",
-       "  background-color: var(--sklearn-color-fitted-level-2);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
-       "#sk-container-id-4 div.sk-label label {\n",
-       "  /* The background is the default theme color */\n",
-       "  color: var(--sklearn-color-text-on-default-background);\n",
-       "}\n",
-       "\n",
-       "/* On hover, darken the color of the background */\n",
-       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
-       "  color: var(--sklearn-color-text);\n",
-       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
-       "}\n",
-       "\n",
-       "/* Label box, darken color on hover, fitted */\n",
-       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
-       "  color: var(--sklearn-color-text);\n",
-       "  background-color: var(--sklearn-color-fitted-level-2);\n",
-       "}\n",
-       "\n",
-       "/* Estimator label */\n",
-       "\n",
-       "#sk-container-id-4 div.sk-label label {\n",
-       "  font-family: monospace;\n",
-       "  font-weight: bold;\n",
-       "  display: inline-block;\n",
-       "  line-height: 1.2em;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-label-container {\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       "/* Estimator-specific */\n",
-       "#sk-container-id-4 div.sk-estimator {\n",
-       "  font-family: monospace;\n",
-       "  border: 1px dotted var(--sklearn-color-border-box);\n",
-       "  border-radius: 0.25em;\n",
-       "  box-sizing: border-box;\n",
-       "  margin-bottom: 0.5em;\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-estimator.fitted {\n",
-       "  /* fitted */\n",
-       "  background-color: var(--sklearn-color-fitted-level-0);\n",
-       "}\n",
-       "\n",
-       "/* on hover */\n",
-       "#sk-container-id-4 div.sk-estimator:hover {\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
-       "  /* fitted */\n",
-       "  background-color: var(--sklearn-color-fitted-level-2);\n",
-       "}\n",
-       "\n",
-       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
-       "\n",
-       "/* Common style for \"i\" and \"?\" */\n",
-       "\n",
-       ".sk-estimator-doc-link,\n",
-       "a:link.sk-estimator-doc-link,\n",
-       "a:visited.sk-estimator-doc-link {\n",
-       "  float: right;\n",
-       "  font-size: smaller;\n",
-       "  line-height: 1em;\n",
-       "  font-family: monospace;\n",
-       "  background-color: var(--sklearn-color-background);\n",
-       "  border-radius: 1em;\n",
-       "  height: 1em;\n",
-       "  width: 1em;\n",
-       "  text-decoration: none !important;\n",
-       "  margin-left: 1ex;\n",
-       "  /* unfitted */\n",
-       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
-       "  color: var(--sklearn-color-unfitted-level-1);\n",
-       "}\n",
-       "\n",
-       ".sk-estimator-doc-link.fitted,\n",
-       "a:link.sk-estimator-doc-link.fitted,\n",
-       "a:visited.sk-estimator-doc-link.fitted {\n",
-       "  /* fitted */\n",
-       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
-       "  color: var(--sklearn-color-fitted-level-1);\n",
-       "}\n",
-       "\n",
-       "/* On hover */\n",
-       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
-       ".sk-estimator-doc-link:hover,\n",
-       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
-       ".sk-estimator-doc-link:hover {\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
-       "  color: var(--sklearn-color-background);\n",
-       "  text-decoration: none;\n",
-       "}\n",
-       "\n",
-       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
-       ".sk-estimator-doc-link.fitted:hover,\n",
-       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
-       ".sk-estimator-doc-link.fitted:hover {\n",
-       "  /* fitted */\n",
-       "  background-color: var(--sklearn-color-fitted-level-3);\n",
-       "  color: var(--sklearn-color-background);\n",
-       "  text-decoration: none;\n",
-       "}\n",
-       "\n",
-       "/* Span, style for the box shown on hovering the info icon */\n",
-       ".sk-estimator-doc-link span {\n",
-       "  display: none;\n",
-       "  z-index: 9999;\n",
-       "  position: relative;\n",
-       "  font-weight: normal;\n",
-       "  right: .2ex;\n",
-       "  padding: .5ex;\n",
-       "  margin: .5ex;\n",
-       "  width: min-content;\n",
-       "  min-width: 20ex;\n",
-       "  max-width: 50ex;\n",
-       "  color: var(--sklearn-color-text);\n",
-       "  box-shadow: 2pt 2pt 4pt #999;\n",
-       "  /* unfitted */\n",
-       "  background: var(--sklearn-color-unfitted-level-0);\n",
-       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
-       "}\n",
-       "\n",
-       ".sk-estimator-doc-link.fitted span {\n",
-       "  /* fitted */\n",
-       "  background: var(--sklearn-color-fitted-level-0);\n",
-       "  border: var(--sklearn-color-fitted-level-3);\n",
-       "}\n",
-       "\n",
-       ".sk-estimator-doc-link:hover span {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
-       "\n",
-       "#sk-container-id-4 a.estimator_doc_link {\n",
-       "  float: right;\n",
-       "  font-size: 1rem;\n",
-       "  line-height: 1em;\n",
-       "  font-family: monospace;\n",
-       "  background-color: var(--sklearn-color-background);\n",
-       "  border-radius: 1rem;\n",
-       "  height: 1rem;\n",
-       "  width: 1rem;\n",
-       "  text-decoration: none;\n",
-       "  /* unfitted */\n",
-       "  color: var(--sklearn-color-unfitted-level-1);\n",
-       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
-       "  /* fitted */\n",
-       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
-       "  color: var(--sklearn-color-fitted-level-1);\n",
-       "}\n",
-       "\n",
-       "/* On hover */\n",
-       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
-       "  /* unfitted */\n",
-       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
-       "  color: var(--sklearn-color-background);\n",
-       "  text-decoration: none;\n",
-       "}\n",
-       "\n",
-       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
-       "  /* fitted */\n",
-       "  background-color: var(--sklearn-color-fitted-level-3);\n",
-       "}\n",
-       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=3, topology=&#x27;circle&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ImmersionEstimator<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>ImmersionEstimator(device=&#x27;cuda&#x27;, extrinsic_dim=3, topology=&#x27;circle&#x27;)</pre></div> </div></div></div></div>"
-      ],
-      "text/plain": [
-       "ImmersionEstimator(device='cuda', extrinsic_dim=3, topology='circle')"
-      ]
-     },
-     "execution_count": 68,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "immersion_estimator.fit(X, labels)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "immersion = immersion_estimator.estimate_"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import torch\n",
-    "\n",
-    "intrinsic_coords = torch.tensor(intrinsic_coords, device=device)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "recon_points = immersion(intrinsic_coords).detach().cpu().numpy().squeeze()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 72,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "config": {
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-         "marker": {
-          "size": 3
-         },
-         "mode": "markers",
-         "scene": "scene",
-         "type": "scatter3d",
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-       "                            \n",
-       "var gd = document.getElementById('a4cb67c1-7f83-4b74-aa21-f5cc03275aec');\n",
-       "var x = new MutationObserver(function (mutations, observer) {{\n",
-       "        var display = window.getComputedStyle(gd).display;\n",
-       "        if (!display || display === 'none') {{\n",
-       "            console.log([gd, 'removed!']);\n",
-       "            Plotly.purge(gd);\n",
-       "            observer.disconnect();\n",
-       "        }}\n",
-       "}});\n",
-       "\n",
-       "// Listen for the removal of the full notebook cells\n",
-       "var notebookContainer = gd.closest('#notebook-container');\n",
-       "if (notebookContainer) {{\n",
-       "    x.observe(notebookContainer, {childList: true});\n",
-       "}}\n",
-       "\n",
-       "// Listen for the clearing of the current output cell\n",
-       "var outputEl = gd.closest('.output');\n",
-       "if (outputEl) {{\n",
-       "    x.observe(outputEl, {childList: true});\n",
-       "}}\n",
-       "\n",
-       "                        })                };                });            </script>        </div>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import plotly.graph_objects as go\n",
-    "from plotly.subplots import make_subplots\n",
-    "\n",
-    "# plot manifold points in 3d and recon points in 3d in separate subplots\n",
-    "\n",
-    "fig = make_subplots(\n",
-    "    rows=1, cols=2, specs=[[{\"type\": \"scatter3d\"}, {\"type\": \"scatter3d\"}]]\n",
-    ")\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=manifold_points[:, 0],\n",
-    "        y=manifold_points[:, 1],\n",
-    "        z=manifold_points[:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3),\n",
-    "    ),\n",
-    "    row=1,\n",
-    "    col=1,\n",
-    ")\n",
-    "\n",
-    "fig.add_trace(\n",
-    "    go.Scatter3d(\n",
-    "        x=recon_points[:, 0],\n",
-    "        y=recon_points[:, 1],\n",
-    "        z=recon_points[:, 2],\n",
-    "        mode=\"markers\",\n",
-    "        marker=dict(size=3),\n",
-    "    ),\n",
-    "    row=1,\n",
-    "    col=2,\n",
-    ")\n",
-    "\n",
-    "fig.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "neurometry",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/tutorials/09_application_rnns_grid_cells_xu.ipynb b/tutorials/05_analyze_task_optimized_rnn.ipynb
similarity index 99%
rename from tutorials/09_application_rnns_grid_cells_xu.ipynb
rename to tutorials/05_analyze_task_optimized_rnn.ipynb
index 1a052b5..a6bac84 100644
--- a/tutorials/09_application_rnns_grid_cells_xu.ipynb
+++ b/tutorials/05_analyze_task_optimized_rnn.ipynb
@@ -4,9 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Analyze Representations in Path-Integrating RNN\n",
+    "# Analyze a Task-Optimized RNN model of Medial Entorhinal Cortex\n",
     "\n",
-    "Model from \"Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells\" Xu, et al. 2022. (https://arxiv.org/abs/2210.02684)"
+    "Model from \"Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems\" (Acosta, et al. 2024)"
    ]
   },
   {
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diff --git a/tutorials/12_application_digitaltwin_v4.ipynb b/tutorials/06_analyze_digital_twin_V4.ipynb
similarity index 99%
rename from tutorials/12_application_digitaltwin_v4.ipynb
rename to tutorials/06_analyze_digital_twin_V4.ipynb
index 165e90f..d54d60c 100644
--- a/tutorials/12_application_digitaltwin_v4.ipynb
+++ b/tutorials/06_analyze_digital_twin_V4.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# V4 Digital Twins"
+    "# Analyze a Digital Twin model of Macaque Visual Cortex area V4"
    ]
   },
   {
diff --git a/tutorials/07_analyze_electrophys_hippocampus.ipynb b/tutorials/07_analyze_electrophys_hippocampus.ipynb
new file mode 100644
index 0000000..1b08c3b
--- /dev/null
+++ b/tutorials/07_analyze_electrophys_hippocampus.ipynb
@@ -0,0 +1,25 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analyze Electrophysiological Recordings of Rodent Hippocampus\n",
+    "\n",
+    "We would like to thank James Knierim, Noah Cowan and Ravikrishnan Jayakumar at Johns Hopkins University for providing experimental data. The rodent place cell data analyzed in this tutorial was collected in the Knierim and Cowan labs by R. Jayakumar and M. Madhav."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tutorials/04_explore_hyperbolic_geometry.ipynb b/tutorials/move/04_explore_hyperbolic_geometry.ipynb
similarity index 100%
rename from tutorials/04_explore_hyperbolic_geometry.ipynb
rename to tutorials/move/04_explore_hyperbolic_geometry.ipynb
diff --git a/tutorials/move/04_methods_estimate_manifold_geometry.ipynb b/tutorials/move/04_methods_estimate_manifold_geometry.ipynb
new file mode 100644
index 0000000..88a2ee8
--- /dev/null
+++ b/tutorials/move/04_methods_estimate_manifold_geometry.ipynb
@@ -0,0 +1,29839 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Classify Neural Manifold Topology"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Set-up + Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Working directory:  /home/facosta/neurometry/neurometry\n",
+      "Directory added to path:  /home/facosta/neurometry\n",
+      "Directory added to path:  /home/facosta/neurometry/neurometry\n",
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n",
+      "The jupyter_black extension is already loaded. To reload it, use:\n",
+      "  %reload_ext jupyter_black\n"
+     ]
+    }
+   ],
+   "source": [
+    "import setup\n",
+    "\n",
+    "setup.main()\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "%load_ext jupyter_black\n",
+    "\n",
+    "import os\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import torch\n",
+    "\n",
+    "os.environ[\"GEOMSTATS_BACKEND\"] = \"pytorch\"\n",
+    "import geomstats.backend as gs\n",
+    "import neurometry.datasets.synthetic as synthetic"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "noise level: 0.71%\n"
+     ]
+    }
+   ],
+   "source": [
+    "import neurometry.datasets.synthetic as synthetic\n",
+    "\n",
+    "circle_task_points = synthetic.hypersphere(1, 1000)\n",
+    "circle_noisy_points, circle_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=circle_task_points,\n",
+    "    encoding_dim=10,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(10),\n",
+    "    poisson_multiplier=100,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('4b9dbb5e-16e9-4704-a149-be226c7ca480');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot noisy_points and manifold_points in 3D with plotly\n",
+    "\n",
+    "import plotly.graph_objects as go\n",
+    "\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=circle_noisy_points[:, 0],\n",
+    "        y=circle_noisy_points[:, 1],\n",
+    "        z=circle_noisy_points[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3),\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=circle_manifold_points[:, 0],\n",
+    "        y=circle_manifold_points[:, 1],\n",
+    "        z=circle_manifold_points[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3),\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from neurometry.estimators.topology.persistent_homology import compute_diagrams_shuffle\n",
+    "\n",
+    "\n",
+    "import neurometry.datasets.synthetic as synthetic\n",
+    "\n",
+    "circle_task_points = synthetic.hypersphere(1, 1000)\n",
+    "circle_noisy_points, circle_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=circle_task_points,\n",
+    "    encoding_dim=10,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(10),\n",
+    "    poisson_multiplier=100,\n",
+    ")\n",
+    "\n",
+    "num_shuffles = 100\n",
+    "\n",
+    "circle_noisy_diagrams = compute_diagrams_shuffle(\n",
+    "    circle_noisy_points, num_shuffles=num_shuffles, homology_dimensions=[0, 1, 2]\n",
+    ")\n",
+    "\n",
+    "\n",
+    "from gtda.diagrams import PersistenceEntropy\n",
+    "\n",
+    "circle_PE = PersistenceEntropy()\n",
+    "\n",
+    "circle_features = circle_PE.fit_transform(circle_noisy_diagrams)\n",
+    "\n",
+    "# manifold_diagrams = compute_diagrams_shuffle(manifold_points, num_shuffles=num_shuffles)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = noisy_points\n",
+    "\n",
+    "\n",
+    "def _shuffle_entries(data, rng):\n",
+    "    return np.array([rng.permutation(row) for row in data])\n",
+    "\n",
+    "\n",
+    "seed = 0\n",
+    "rng = np.random.default_rng(seed)\n",
+    "shuffled_Xs = [_shuffle_entries(X, rng) for _ in range(num_shuffles)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('b002dd44-9735-4463-91a0-ef7f7a400613');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.graph_objects as go\n",
+    "\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=X[:, 0],\n",
+    "        y=X[:, 1],\n",
+    "        z=X[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3),\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "i = 5\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=shuffled_Xs[i][:, 0],\n",
+    "        y=shuffled_Xs[i][:, 1],\n",
+    "        z=shuffled_Xs[i][:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3),\n",
+    "    )\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hoverinfo": "none",
+         "line": {
+          "color": "black",
+          "dash": "dash",
+          "width": 1
+         },
+         "mode": "lines",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          -13.17488525390625,
+          122.965595703125
+         ],
+         "y": [
+          -13.17488525390625,
+          122.965595703125
+         ]
+        },
+        {
+         "hoverinfo": "text",
+         "hovertext": [
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('f6812aac-2dae-4cc9-82b5-75180cb2aa10');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from gtda.plotting import plot_diagram\n",
+    "\n",
+    "plot_diagram(noisy_diagrams[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
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+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_diagram(noisy_diagrams[70])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from gtda.diagrams import PersistenceEntropy\n",
+    "\n",
+    "circle_PE = PersistenceEntropy()\n",
+    "\n",
+    "circle_features = circle_PE.fit_transform(circle_noisy_diagrams)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('67cc471e-7990-40ff-9cbc-e3c385c2a0e1');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 3d plot with plotly\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=features[1:, 0],\n",
+    "        y=features[1:, 1],\n",
+    "        z=features[1:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"blue\"),\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=[features[0, 0]],\n",
+    "        y=[features[0, 1]],\n",
+    "        z=[features[0, 2]],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"red\"),\n",
+    "    )\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Wt74VI0aMiPLy8gIlBQAAGht1s7p5Q+pmALZlGuMAFJ0TTjgh9t5775g6dWpMmzYtIiJ69+4dBx100EZjv/SlL212njlz5sTQoUNj6dKl0aZNmzj88MOjqqoqPvroo3jqqadqja2pqckU93vssUd07949dtxxx2jevHksWbIkXn755fjXv/4VERFPPPFEHHXUUfHcc89FRUVFrXmOOuqoaN26dbz++usxYcKEiIjo1q1bHHnkkRvl69q1az3+Vv7ttddei759+8aHH36YuW2fffaJ/fffP1KpVMycOTNefvnliIiYPn16HHLIIfHUU0/VKoI355VXXonLLrssVqxYETvttFN8+ctfjh122CHmz58fTzzxRHzyySexbt26OP/882Offfb53L//uigvL4+BAwfGbbfdFhGfFe5bKvA/+eSTePDBBzPXN/z0fMRnRzCsL+532WWX6NGjR3To0CFatmwZK1asiNdeey1mzJgRSZLEiy++GIcffni88MILBX3D5vMMHTo0br755sz1ysrKOPjgg6NDhw7x6aefxsyZM+OVV16JJEnirrvuipqamnj44YejrMyJhQAAoFipmz+fulndrG4GKFIJAORQ3759k4hIIiK54oortmqO9dt/3svUho8zceLETY654oor6p1l0KBBmW2aNm2aREQyZMiQZPny5bXGrV69Olm3bl3m+p133pnccsstybvvvrvZuV988cWkV69emfl//vOfb3bsqFGjMuMGDRpUp+x12WbVqlXJfvvtlxm30047JY899thG4/7+978nlZWVmXE9e/ZMVq9evck5N1yLioqKpEmTJskNN9yQrFmzpta4efPmJXvvvXdmbL9+/er0vLZk6tSptX5nXnrppc8dP2bMmFp5P/roo1r3jx8/Phk+fHgye/bszc7x5ptvJkcffXRmnrPPPnuzYydOnJgZ17dv360e85/q8u/kzjvvzIxp27Ztcscdd2xyHZ944omkU6dOmbHXXXddnTIAAAD1p25WN6uba1M3A9BQHDEOQN488sgjsXDhwi2Ou+yyy6JTp04NkKh+1q5dG+ecc07ceuutG93XrFmzWtfPOuusLc637777xuOPPx7dunWLBQsWxK9//eu47LLLokmTJjnLvCVjxoyJF198MSI+ew6PPvpoHHDAARuNGzBgQDzyyCNxyCGHxNq1a2PGjBkxduzYjb5T7D+tWrUqfvvb38a555670X277rprjB07Nvbdd99IkiQmTZoU7733XnTs2DGr59S7d+/o3r17vPbaaxHx2affr7/++s2O3/B0cF/72teiffv2te4/7rjj4rjjjvvcx9x9993joYceil69esVLL70UY8aMieuvvz622267rX8iObZ8+fL43//934j47AiBf/zjH9GnT59Nju3Xr1889thj0bNnz/j000/jF7/4RXz3u9+Nli1bNmRkAAAoOerm2tTN6uaGpG4GKD3O9QFA3kybNi1uu+22Lf5seGqybUnz5s3jF7/4RU7nbNeuXZxwwgkREfHee+/Fq6++mtP5t+S3v/1t5vIFF1ywyeJ+vd69e9f6PrMRI0Zscf599tlnk8X9envvvXf07t07IiKSJInnn3++LrG3aMPTut17772b/M66iM/+zh9//PFNbldfzZo1i9NPPz0iIj799NOYPHnyVs+VD3fddVcsWbIkIiK+853vbLa4X6979+6Zv49FixbFo48+mu+IAABQ8tTNG1M3q5sbiroZoPQ4YhwANmPAgAFb9UnmDz74IJ577rl47bXX4qOPPoqVK1dGkiSZ+zcsal944YXYZ599cpJ3S5YvX17rsevyaf1zzjknU9hPmzYtVq5cGa1atdrs+JNPPnmLcx5wwAExderUiIh46623tji+Lr75zW/GsGHDIp1OR01NTTz++ONx9NFHbzRuzJgxmeK/Q4cOmxyzoSVLlsRzzz0X//rXv2LRokWxYsWKSKfTmftff/31zOUXXnhhi5+Yb0iPPPJI5vJpp51Wp2369++feRNo8uTJceKJJ+YlGwAAUBzUzepmdbO6GaAx0RgHIG+uuOKKuPLKKwsdY6sdeOCB9Rr/6quvxqWXXhp/+9vfNvvJ6/9Ul1Pm5cpLL72UydW6devYd999t7jN/vvvH61atYqVK1fGunXr4sUXX4xDDjlks+Pr8mbFDjvskLm8bNmyOiTfsk6dOsVRRx0V//jHPyIi4ne/+90mi/cNTwd3+umnb/Z0fO+++2786Ec/igcffDBWrVpVpwwNuZZ18eyzz2Yu33777XH33XdvcZt33303c/mdd97JSy4AAODf1M1bpm5WN+eLuhmg9GiMA8Bm7LjjjnUe+/e//z2+9rWv1bkYXG/58uX1jbXVNjz13q677hqpVGqL25SVlcWuu+6a+YT3lorYdu3abXHODb9nbs2aNVscX1eDBg3KFPjjxo2LFStWROvWrTP3z5w5M15++eVa4zdl5syZceSRR8ZHH31Ur8dvyLXckhUrVtTKM3LkyHrPUd/nDwAAlB51s7q5PtTNABSa7xgHgM1o0aJFncZ9+OGHccopp2SK+9122y2GDx8ekydPjpqamvj4448jnU5HkiSRJElcccUVmW03PL1Yvq1YsSJz+fNO6/afNhy7pSK2Lm8a5MsJJ5wQbdu2jYiIjz/+OB588MFa92/4qfcDDjhgk5/SX7VqVZx00kmZ4nbHHXeMn/zkJzFx4sR45513YuXKlbXWctSoUZltG3Itt2Tp0qVZz7F27docJAEAAIqZunnjsepmdTMA2y5HjANAlu64445MQbXffvvFU089lSk0N6VQn5De8FPgK1eurPN2G45t06ZNTjPlUosWLeLkk0+OO++8MyI+Oy3c4MGDI+KzYnXs2LGZsZv71Psf//jHmDt3bkR8dpq5adOmRceOHTf7mIVayy29mfCfb+AsXrx4q773DwAAIBfUzdsGdfO/qZsBSpMjxgEgSxMmTMhc/slPfvK5xX1ExNtvv53vSJu04Snu3n333UiSZIvbpNPpWt+ZVVlZmZdsubJh4T5p0qRM9r///e/x/vvvR8Rnp6Q77bTTNrn9hms5dOjQzy3uI3K3lhueJq8unzjf0ifb27dvHxUVFZnrCxYs2PpwAAAAWVI3bzvUzZ9RNwOUJo1xAIpWQ52erKamJnN5U6cZ29C6devi6aef3uKc+ci+7777RpMmTSLis09sb/i9YZvz4osvZj753qRJk9hvv/1yniuXDjvssNhjjz0i4rM3J37/+99HRO3TwR1zzDGb/R68+qxlRMRTTz2VTdyMDd8UWrRo0RbH12XtDjrooMzluvzOAQAApUfdXJu6+TPqZgCKlcY4AEWrefPmmctr1qzJ2+OUlf375fTjjz/+3LF//vOf6/Qp5Hxkb9OmTfTq1StzffTo0VvcZv3p1SI+Kxjr8x1rhZBKpeLMM8/MXP/d734XS5cujfHjx2du29zp4CLqt5bTp0+PadOmZZH233bbbbfMmzpz5syp9b12m3L//fdvcc6vfvWrmcsjRoyo05EOAABAaVE316Zu/oy6GYBipTEOQNHaYYcdMpfnz5+ft8dZ/0nriKhVSP6nDz/8MC666KI6zZmv7Oedd17m8m233RYvvfTSZsdOnz49fvvb32aun3/++TnLkU9nnnlmplh+7bXX4oc//GF8+umnERGx/fbb1yp8/1Nd1/Ljjz+Oc889N0eJP/vke7du3SLis1PCjRkzZrNjZ86cGXfccccW5zzvvPOiffv2ERExY8aMuOqqq+qcZ+HChbFu3bo6jwcAABondfPG1M3q5rpQNwM0ThrjABStvffeO3P5H//4xxa/X2prHXfccZnLw4cPz5yGbEMzZsyIvn37xjvvvFOnT49vmH3KlCkxb968nGQ9/fTTM6d1W716dRx99NExceLEjcY9/vjjccwxx2S+t6tnz54xcODAnGTIt9133z2+/OUvZ67ffvvtmcsDBw6M8vLyzW674VrefffdccMNN2xU6M6ZMycGDBgQM2bMyOmRABt+f9uPfvSjmDx58kZj/va3v8WAAQPqdMrAdu3axY033pi5ftVVV8WgQYM2+7uUJEk8/fTT8Z3vfCeqq6vjk08+2YpnAQAANCbq5o2pm9XN6maA4tW00AEAIF8OOuig2HXXXeOdd96J9957L7p16xYDBgyIysrKTIHUu3fvOOWUU7J6nEGDBsUNN9wQs2bNilWrVsUZZ5wR11xzTey3337RvHnzeOWVV+L555+PiIj99tsvjj766PjFL37xuXN26NAhDjnkkHjmmWfi008/jf322y++8pWvRMeOHTOnLevSpUtccMEF9cpaXl4eY8eOjb59+8aHH34YCxYsiP79+8d+++0X+++/f0REvPDCC/Hiiy9mttlpp51i7Nix0axZs3o9ViENGjRok99j9nmng4uIGDBgQBx++OHx1FNPRZIkcckll8Rtt90WPXv2jHbt2sXs2bPjmWeeiXXr1kWnTp3iwgsvjB/+8Ic5yfy9730vRowYETU1NbFkyZI4/PDD49BDD41u3brFp59+Gs8//3y8/vrrEfHZ6fwGDx68xTkHDx4cb775Zvz85z+PiM++M27MmDGx//77R7du3aJ169axYsWKePfdd+OFF17I25tgAADAtkndvDF1s7pZ3QxQvDTGAShaZWVl8etf/zpOOumkWL16dSxYsCDuueeeWmMGDRqUdYFfUVERDz30UBxzzDHx5ptvRsRnpyJ77bXXao079NBD4w9/+EOdTucVEXHzzTdH//79Y/ny5bFkyZK47777at3ft2/fehf4ERHdu3ePyZMnx6mnnhozZ86MiIgXX3yxVlG/Xs+ePeP++++PLl261PtxCunkk0+O733ve7W+76x79+7Ru3fvLW57//33x3//93/HjBkzIiJi7ty5MXfu3FpjevToEQ888EBMnTo1Z5nbtWsXDz30UBx99NGxcOHCSJIkJk+eXOsT8OXl5XHjjTfGoEG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+      "text/plain": [
+       "<Figure size 2000x1000 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from neurometry.estimators.topology.plotting import plot_all_barcodes_with_null\n",
+    "\n",
+    "plot_all_barcodes_with_null(\n",
+    "    noisy_diagrams, \"noisy\", diagrams_2=manifold_diagrams, dataset_name_2=\"manifold\"\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def _get_lifespan_from_diagram(diagram):\n",
+    "    birth = diagram[:, 0]\n",
+    "    death = diagram[:, 1]\n",
+    "    if np.isfinite(death).any():\n",
+    "        inf_value = 3 * np.max(death[death != np.inf])\n",
+    "    else:\n",
+    "        inf_value = 1000\n",
+    "    death[death == np.inf] = inf_value\n",
+    "    lifespan = death - birth\n",
+    "    indices = np.argsort(-lifespan)[:20]\n",
+    "\n",
+    "    return lifespan[indices]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def estimate_betti_numbers(points, num_shuffles, homology_dimensions=(0, 1, 2)):\n",
+    "    all_diagrams = compute_diagrams_shuffle(\n",
+    "        points, num_shuffles=num_shuffles, homology_dimensions=homology_dimensions\n",
+    "    )\n",
+    "    diagram = all_diagrams[0]\n",
+    "    shuffled_diagrams = all_diagrams[1:]\n",
+    "\n",
+    "    betti_numbers = {dim: None for dim in homology_dimensions}\n",
+    "\n",
+    "    for dim in homology_dimensions:\n",
+    "        filtered_diagram = diagram[diagram[:, 2] == dim]\n",
+    "        lifespan = _get_lifespan_from_diagram(filtered_diagram)\n",
+    "        filtered_shuffled_diagrams = np.array(\n",
+    "            [\n",
+    "                shuffled_diagrams[i, shuffled_diagrams[i, :, 2] == 1]\n",
+    "                for i in range(shuffled_diagrams.shape[0])\n",
+    "            ]\n",
+    "        )\n",
+    "        betti_number = []\n",
+    "        for diag in filtered_shuffled_diagrams:\n",
+    "            shuffled_lifespan = _get_lifespan_from_diagram(diag)\n",
+    "            significant_features = (lifespan > shuffled_lifespan).astype(int)\n",
+    "            betti_number.append(sum(significant_features))\n",
+    "        betti_numbers[dim] = (np.mean(betti_number), np.std(betti_number))\n",
+    "\n",
+    "    return betti_numbers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{0: (1.28, 2.209434316742636), 1: (1.0, 0.0), 2: (0.0, 0.0)}\n"
+     ]
+    }
+   ],
+   "source": [
+    "betti_numbers = estimate_betti_numbers(\n",
+    "    manifold_points, num_shuffles=100, homology_dimensions=(0, 1, 2)\n",
+    ")\n",
+    "print(betti_numbers)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "homology_dimensions = (0, 1)\n",
+    "points = manifold_points\n",
+    "num_shuffles = 100\n",
+    "\n",
+    "all_diagrams = compute_diagrams_shuffle(\n",
+    "    points, num_shuffles=num_shuffles, homology_dimensions=homology_dimensions\n",
+    ")\n",
+    "\n",
+    "plot_all_barcodes_with_null(all_diagrams, \"manifold\")\n",
+    "\n",
+    "\n",
+    "diagram = all_diagrams[0]\n",
+    "lifespan = _get_lifespan_from_diagram(diagram)\n",
+    "shuffled_diagrams = all_diagrams[1:]\n",
+    "\n",
+    "betti_numbers = {dim: None for dim in homology_dimensions}\n",
+    "\n",
+    "for dim in homology_dimensions:\n",
+    "    betti_number = []\n",
+    "    for shuffled_diagram in shuffled_diagrams:\n",
+    "        shuffled_lifespan = _get_lifespan_from_diagram(shuffled_diagram)\n",
+    "        significant_features = (lifespan > shuffled_lifespan).astype(int)\n",
+    "        betti_number.append(sum(significant_features))\n",
+    "    betti_numbers[dim] = np.mean(betti_number)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_betti_numbers(diagrams):\n",
+    "    original_diagram = diagrams[0]\n",
+    "    shuffled_diagrams = diagrams[1:]\n",
+    "\n",
+    "    dims = np.unique(original_diagram[:, 2]).astype(int)\n",
+    "\n",
+    "    betti_numbers = {dim: None for dim in dims}\n",
+    "    for i, dim in enumerate(dims):\n",
+    "        diagram_dim = original_diagram[original_diagram[:, 2] == dim]\n",
+    "        null_diagram_dim = shuffled_diagrams[:, :, 2] == dim\n",
+    "        null_diagram = shuffled_diagrams[null_diagram_dim]\n",
+    "\n",
+    "        null_lifespans_dim = _get_lifespan_from_diagram(null_diagram)\n",
+    "        lifespans_dim = _get_lifespan_from_diagram(diagram_dim)\n",
+    "\n",
+    "        comparison = (lifespans_dim > null_lifespans_dim).astype(int)\n",
+    "\n",
+    "        betti_numbers[dim] = sum(comparison)\n",
+    "\n",
+    "    return betti_numbers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "betti = get_betti_numbers(noisy_diagrams)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{0: 0, 1: 5, 2: 2}"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "betti"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Classify circle, sphere, torus point clouds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import neurometry.datasets.synthetic as synthetic\n",
+    "from neurometry.estimators.topology.persistent_homology import compute_diagrams_shuffle\n",
+    "from gtda.diagrams import PersistenceEntropy\n",
+    "\n",
+    "num_points = 1000\n",
+    "encoding_dim = 10\n",
+    "poisson_multiplier = 100\n",
+    "homology_dimensions = [0, 1, 2]\n",
+    "num_shuffles = 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "noise level: 0.71%\n"
+     ]
+    }
+   ],
+   "source": [
+    "circle_task_points = synthetic.hypersphere(1, num_points)\n",
+    "circle_noisy_points, circle_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=circle_task_points,\n",
+    "    encoding_dim=encoding_dim,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(encoding_dim),\n",
+    "    poisson_multiplier=poisson_multiplier,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "circle_noisy_diagrams = compute_diagrams_shuffle(\n",
+    "    circle_noisy_points,\n",
+    "    num_shuffles=num_shuffles,\n",
+    "    homology_dimensions=homology_dimensions,\n",
+    ")\n",
+    "\n",
+    "circle_PE = PersistenceEntropy()\n",
+    "\n",
+    "circle_features = circle_PE.fit_transform(circle_noisy_diagrams)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "noise level: 0.71%\n"
+     ]
+    }
+   ],
+   "source": [
+    "sphere_task_points = synthetic.hypersphere(2, num_points)\n",
+    "sphere_noisy_points, sphere_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=sphere_task_points,\n",
+    "    encoding_dim=encoding_dim,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(encoding_dim),\n",
+    "    poisson_multiplier=poisson_multiplier,\n",
+    ")\n",
+    "\n",
+    "sphere_noisy_diagrams = compute_diagrams_shuffle(\n",
+    "    sphere_noisy_points,\n",
+    "    num_shuffles=num_shuffles,\n",
+    "    homology_dimensions=homology_dimensions,\n",
+    ")\n",
+    "\n",
+    "sphere_PE = PersistenceEntropy()\n",
+    "sphere_features = sphere_PE.fit_transform(sphere_noisy_diagrams)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "noise level: 0.71%\n"
+     ]
+    }
+   ],
+   "source": [
+    "torus_task_points = synthetic.hypertorus(2, num_points)\n",
+    "torus_noisy_points, torus_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=torus_task_points,\n",
+    "    encoding_dim=encoding_dim,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(encoding_dim),\n",
+    "    poisson_multiplier=poisson_multiplier,\n",
+    ")\n",
+    "\n",
+    "torus_noisy_diagrams = compute_diagrams_shuffle(\n",
+    "    torus_noisy_points,\n",
+    "    num_shuffles=num_shuffles,\n",
+    "    homology_dimensions=homology_dimensions,\n",
+    ")\n",
+    "\n",
+    "torus_PE = PersistenceEntropy()\n",
+    "\n",
+    "torus_features = torus_PE.fit_transform(torus_noisy_diagrams)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
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{\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenu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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('03175875-422d-41e7-9b4c-8536f45300c5');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 3d plot with plotly\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=circle_features[1:, 0],\n",
+    "        y=circle_features[1:, 1],\n",
+    "        z=circle_features[1:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"lightpink\"),\n",
+    "        name=\"Shuffled Circle\",\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=[circle_features[0, 0]],\n",
+    "        y=[circle_features[0, 1]],\n",
+    "        z=[circle_features[0, 2]],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"deeppink\"),\n",
+    "        name=\"Circle\",\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=sphere_features[1:, 0],\n",
+    "        y=sphere_features[1:, 1],\n",
+    "        z=sphere_features[1:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"lightgreen\"),\n",
+    "        name=\"Shuffled Sphere\",\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=[sphere_features[0, 0]],\n",
+    "        y=[sphere_features[0, 1]],\n",
+    "        z=[sphere_features[0, 2]],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"darkgreen\"),\n",
+    "        name=\"Sphere\",\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=torus_features[1:, 0],\n",
+    "        y=torus_features[1:, 1],\n",
+    "        z=torus_features[1:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"lightblue\"),\n",
+    "        name=\"Shuffled Torus\",\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=[torus_features[0, 0]],\n",
+    "        y=[torus_features[0, 1]],\n",
+    "        z=[torus_features[0, 2]],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=\"darkblue\"),\n",
+    "        name=\"Torus\",\n",
+    "    )\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Classifier score: 1.0\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;TopologicalClassifier<span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_points = 500\n",
+    "encoding_dim = 10\n",
+    "poisson_multiplier = 100\n",
+    "\n",
+    "\n",
+    "test_task_points = synthetic.hypertorus(2, 400)\n",
+    "test_noisy_points, test_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=test_task_points,\n",
+    "    encoding_dim=encoding_dim,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(encoding_dim),\n",
+    "    poisson_multiplier=poisson_multiplier,\n",
+    ")\n",
+    "\n",
+    "from neurometry.estimators.topology.persistent_homology import TopologicalClassifier\n",
+    "\n",
+    "num_samples = 10\n",
+    "\n",
+    "TC = TopologicalClassifier(\n",
+    "    num_samples=num_samples, poisson_multiplier=poisson_multiplier, reduce_dim=True\n",
+    ")\n",
+    "TC.fit(test_noisy_points)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([2.])"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "TC.predict(test_noisy_points)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.base import BaseEstimator, ClassifierMixin\n",
+    "\n",
+    "\n",
+    "class TopologicalClassifier(ClassifierMixin, BaseEstimator):\n",
+    "    def __init__(\n",
+    "        self,\n",
+    "        num_samples,\n",
+    "        poisson_multiplier,\n",
+    "        homology_dimensions=[0, 1, 2],\n",
+    "        reduce_dim=False,\n",
+    "    ):\n",
+    "        self.num_samples = num_samples\n",
+    "        self.poisson_multiplier = poisson_multiplier\n",
+    "        self.homology_dimensions = homology_dimensions\n",
+    "        self.reduce_dim = reduce_dim\n",
+    "        self.classifier = RandomForestClassifier()\n",
+    "\n",
+    "    def _generate_ref_data(self, input_data):\n",
+    "        num_points = input_data.shape[0]\n",
+    "        encoding_dim = input_data.shape[1]\n",
+    "        circle_task_points = synthetic.hypersphere(1, num_points)\n",
+    "        circle_point_clouds = []\n",
+    "        for i in range(self.num_samples):\n",
+    "            circle_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
+    "                points=circle_task_points,\n",
+    "                encoding_dim=encoding_dim,\n",
+    "                nonlinearity=\"sigmoid\",\n",
+    "                scales=gs.ones(encoding_dim),\n",
+    "                poisson_multiplier=self.poisson_multiplier,\n",
+    "            )\n",
+    "            circle_point_clouds.append(circle_noisy_points)\n",
+    "\n",
+    "        sphere_task_points = synthetic.hypersphere(2, num_points)\n",
+    "        sphere_point_clouds = []\n",
+    "        for i in range(num_samples):\n",
+    "            sphere_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
+    "                points=sphere_task_points,\n",
+    "                encoding_dim=encoding_dim,\n",
+    "                nonlinearity=\"sigmoid\",\n",
+    "                scales=gs.ones(encoding_dim),\n",
+    "                poisson_multiplier=self.poisson_multiplier,\n",
+    "            )\n",
+    "            sphere_point_clouds.append(sphere_noisy_points)\n",
+    "\n",
+    "        torus_task_points = synthetic.hypertorus(2, num_points)\n",
+    "        torus_point_clouds = []\n",
+    "        for i in range(num_samples):\n",
+    "            torus_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
+    "                points=torus_task_points,\n",
+    "                encoding_dim=encoding_dim,\n",
+    "                nonlinearity=\"sigmoid\",\n",
+    "                scales=gs.ones(encoding_dim),\n",
+    "                poisson_multiplier=self.poisson_multiplier,\n",
+    "            )\n",
+    "            torus_point_clouds.append(torus_noisy_points)\n",
+    "\n",
+    "        klein_bottle_task_points = synthetic.klein_bottle(num_points)\n",
+    "        klein_bottle_point_clouds = []\n",
+    "        for i in range(num_samples):\n",
+    "            klein_bottle_noisy_points, _ = synthetic.synthetic_neural_manifold(\n",
+    "                points=klein_bottle_task_points,\n",
+    "                encoding_dim=encoding_dim,\n",
+    "                nonlinearity=\"sigmoid\",\n",
+    "                scales=gs.ones(encoding_dim),\n",
+    "                poisson_multiplier=self.poisson_multiplier,\n",
+    "            )\n",
+    "            klein_bottle_point_clouds.append(klein_bottle_noisy_points)\n",
+    "\n",
+    "        circle_labels = np.zeros(num_samples)\n",
+    "        sphere_labels = np.ones(num_samples)\n",
+    "        torus_labels = 2 * np.ones(num_samples)\n",
+    "        klein_bottle_labels = 3 * np.ones(num_samples)\n",
+    "        ref_labels = np.concatenate(\n",
+    "            [\n",
+    "                circle_labels,\n",
+    "                sphere_labels,\n",
+    "                torus_labels,\n",
+    "                klein_bottle_labels,\n",
+    "            ]\n",
+    "        )\n",
+    "\n",
+    "        ref_point_clouds = [\n",
+    "            *circle_point_clouds,\n",
+    "            *sphere_point_clouds,\n",
+    "            *torus_point_clouds,\n",
+    "            *klein_bottle_point_clouds,\n",
+    "        ]\n",
+    "\n",
+    "        return ref_point_clouds, ref_labels\n",
+    "\n",
+    "    def _compute_topo_features(self, diagrams):\n",
+    "        PE = PersistenceEntropy()\n",
+    "        features = PE.fit_transform(diagrams)\n",
+    "        return features\n",
+    "\n",
+    "    def fit(self, X, y=None):\n",
+    "        ref_point_clouds, ref_labels = self._generate_ref_data(X)\n",
+    "        if self.reduce_dim:\n",
+    "            pca = PCA(n_components=10)\n",
+    "            ref_point_clouds = [\n",
+    "                pca.fit_transform(point_cloud) for point_cloud in ref_point_clouds\n",
+    "            ]\n",
+    "        ref_diagrams = compute_persistence_diagrams(\n",
+    "            ref_point_clouds, homology_dimensions=self.homology_dimensions\n",
+    "        )\n",
+    "        ref_features = self._compute_topo_features(ref_diagrams)\n",
+    "        X_ref_train, X_ref_valid, y_ref_train, y_ref_valid = train_test_split(\n",
+    "            ref_features, ref_labels\n",
+    "        )\n",
+    "        self.classifier.fit(X_ref_train, y_ref_train)\n",
+    "        print(f\"Classifier score: {self.classifier.score(X_ref_valid, y_ref_valid)}\")\n",
+    "        return self\n",
+    "\n",
+    "    def predict(self, X):\n",
+    "        if self.reduce_dim:\n",
+    "            pca = PCA(n_components=10)\n",
+    "            X = pca.fit_transform(X)\n",
+    "        diagram = compute_persistence_diagrams(\n",
+    "            [X], homology_dimensions=self.homology_dimensions\n",
+    "        )\n",
+    "        features = self._compute_topo_features(diagram)\n",
+    "        return self.classifier.predict(features)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_task_points = synthetic.hypertorus(2, 400)\n",
+    "test_noisy_points, test_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=test_task_points,\n",
+    "    encoding_dim=5,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(10),\n",
+    "    poisson_multiplier=100,\n",
+    ")\n",
+    "\n",
+    "TC = TopologicalClassifier(num_samples=10, poisson_multiplier=100, reduce_dim=True)\n",
+    "TC.fit(test_noisy_points)"
+   ]
+  },
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('da1f5fb7-2f3f-4223-8f41-25598146d0c4');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Example color mapping\n",
+    "color_map = {0: \"darkblue\", 1: \"deeppink\", 2: \"limegreen\", 3: \"orange\"}\n",
+    "colors = [color_map[label] for label in labels]\n",
+    "\n",
+    "names = {0: \"Circle\", 1: \"Sphere\", 2: \"Torus\", 3: \"Klein Bottle\"}\n",
+    "\n",
+    "# Create a figure\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "# Add the trace with colored markers based on labels\n",
+    "fig.add_trace(\n",
+    "    go.Scatter3d(\n",
+    "        x=features[:, 0],\n",
+    "        y=features[:, 1],\n",
+    "        z=features[:, 2],\n",
+    "        mode=\"markers\",\n",
+    "        marker=dict(size=3, color=colors),\n",
+    "        showlegend=False,\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "# Manually add the legend entries\n",
+    "for label, color in color_map.items():\n",
+    "    fig.add_trace(\n",
+    "        go.Scatter3d(\n",
+    "            x=[None],\n",
+    "            y=[None],\n",
+    "            z=[None],\n",
+    "            mode=\"markers\",\n",
+    "            marker=dict(size=3, color=color),\n",
+    "            showlegend=True,\n",
+    "            name=f\"{names[label]}\",\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.8"
+      ]
+     },
+     "execution_count": 110,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "X_train, X_valid, y_train, y_valid = train_test_split(features, labels)\n",
+    "model = RandomForestClassifier()\n",
+    "model.fit(X_train, y_train)\n",
+    "model.score(X_valid, y_valid)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AssertionError",
+     "evalue": "scales must have same shape as tensor",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[9], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m test_task_points \u001b[38;5;241m=\u001b[39m synthetic\u001b[38;5;241m.\u001b[39mhypertorus(\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m400\u001b[39m)\n\u001b[0;32m----> 2\u001b[0m test_noisy_points, test_manifold_points \u001b[38;5;241m=\u001b[39m \u001b[43msynthetic\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msynthetic_neural_manifold\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpoints\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtest_task_points\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoding_dim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnonlinearity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msigmoid\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43mscales\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mones\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpoisson_multiplier\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m     10\u001b[0m TC\u001b[38;5;241m.\u001b[39mfit(test_noisy_points)\n",
+      "File \u001b[0;32m~/neurometry/neurometry/datasets/synthetic.py:42\u001b[0m, in \u001b[0;36msynthetic_neural_manifold\u001b[0;34m(points, encoding_dim, nonlinearity, poisson_multiplier, ref_frequency, **kwargs)\u001b[0m\n\u001b[1;32m     40\u001b[0m encoding_matrix \u001b[38;5;241m=\u001b[39m random_encoding_matrix(manifold_extrinsic_dim, encoding_dim)\n\u001b[1;32m     41\u001b[0m encoded_points \u001b[38;5;241m=\u001b[39m encode_points(points, encoding_matrix)\n\u001b[0;32m---> 42\u001b[0m manifold_points \u001b[38;5;241m=\u001b[39m ref_frequency \u001b[38;5;241m*\u001b[39m \u001b[43mapply_nonlinearity\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     43\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoded_points\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnonlinearity\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m     44\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     45\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m     46\u001b[0m     noisy_points \u001b[38;5;241m=\u001b[39m poisson_spikes(manifold_points, poisson_multiplier)\n",
+      "File \u001b[0;32m~/neurometry/neurometry/datasets/synthetic.py:218\u001b[0m, in \u001b[0;36mapply_nonlinearity\u001b[0;34m(encoded_points, nonlinearity, **kwargs)\u001b[0m\n\u001b[1;32m    216\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m relu(encoded_points, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    217\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m nonlinearity \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msigmoid\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m--> 218\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mscaled_sigmoid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mencoded_points\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    219\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m nonlinearity \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtanh\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    220\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m scaled_tanh(encoded_points, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
+      "File \u001b[0;32m~/neurometry/neurometry/datasets/synthetic.py:231\u001b[0m, in \u001b[0;36mscaled_sigmoid\u001b[0;34m(tensor, scales)\u001b[0m\n\u001b[1;32m    230\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mscaled_sigmoid\u001b[39m(tensor, scales):\n\u001b[0;32m--> 231\u001b[0m     \u001b[38;5;28;01massert\u001b[39;00m tensor\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m==\u001b[39m scales\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mscales must have same shape as tensor\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    232\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m1\u001b[39m \u001b[38;5;241m/\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m+\u001b[39m gs\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mscales \u001b[38;5;241m*\u001b[39m tensor))\n",
+      "\u001b[0;31mAssertionError\u001b[0m: scales must have same shape as tensor"
+     ]
+    }
+   ],
+   "source": [
+    "test_task_points = synthetic.hypertorus(2, 400)\n",
+    "test_noisy_points, test_manifold_points = synthetic.synthetic_neural_manifold(\n",
+    "    points=test_task_points,\n",
+    "    encoding_dim=5,\n",
+    "    nonlinearity=\"sigmoid\",\n",
+    "    scales=gs.ones(10),\n",
+    "    poisson_multiplier=100,\n",
+    ")\n",
+    "\n",
+    "TC.fit(test_noisy_points)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### NOTE: Try different coefficients to distinguish between torus and klein bottle?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{0: (19.814, 0.7066852198822331), 1: (13.214, 2.555817677378416)}\n"
+     ]
+    }
+   ],
+   "source": [
+    "betti_numbers = estimate_betti_numbers(\n",
+    "    manifold_points, num_shuffles=500, homology_dimensions=(0, 1)\n",
+    ")\n",
+    "print(betti_numbers)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2000x1500 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "num_shuffles = 10\n",
+    "\n",
+    "noisy_diagrams = compute_diagrams_shuffle(\n",
+    "    noisy_points, num_shuffles=num_shuffles, homology_dimensions=(0, 1, 2)\n",
+    ")\n",
+    "\n",
+    "manifold_diagrams = compute_diagrams_shuffle(\n",
+    "    manifold_points, num_shuffles=num_shuffles, homology_dimensions=(0, 1, 2)\n",
+    ")\n",
+    "\n",
+    "plot_all_barcodes_with_null(\n",
+    "    noisy_diagrams, \"noisy\", diagrams_2=manifold_diagrams, dataset_name_2=\"manifold\"\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{0: 0, 1: 5, 2: 2}\n"
+     ]
+    }
+   ],
+   "source": [
+    "betti = get_betti_numbers(noisy_diagrams)\n",
+    "print(betti)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### TODO: FIX get_betti_numbers FUNCTION!!!!\n",
+    "\n",
+    "Also: how to deal with betti 0 ? There should be a single \"significant\" feature?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sphere_1_betti = {0: 1, 1: 1, 2: 0}\n",
+    "torus_2_betti = {0: 1, 1: 2, 2: 1}\n",
+    "sphere_2_betti = {0: 1, 1: 0, 2: 1}\n",
+    "\n",
+    "# if betti == sphere_1_betti:\n",
+    "#     print(\"The manifold is a ring\") ----> use ring VAE\n",
+    "\n",
+    "\n",
+    "# elif betti == torus_2_betti:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "neurometry",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tutorials/05_explore_diffeomorphisms_of_space.ipynb b/tutorials/move/05_explore_diffeomorphisms_of_space.ipynb
similarity index 100%
rename from tutorials/05_explore_diffeomorphisms_of_space.ipynb
rename to tutorials/move/05_explore_diffeomorphisms_of_space.ipynb
diff --git a/tutorials/06_application_synthetic_v1.ipynb b/tutorials/move/06_application_synthetic_v1.ipynb
similarity index 100%
rename from tutorials/06_application_synthetic_v1.ipynb
rename to tutorials/move/06_application_synthetic_v1.ipynb
diff --git a/tutorials/071_application_dual_agent_rnns.ipynb b/tutorials/move/071_application_dual_agent_rnns.ipynb
similarity index 100%
rename from tutorials/071_application_dual_agent_rnns.ipynb
rename to tutorials/move/071_application_dual_agent_rnns.ipynb
diff --git a/tutorials/07_application_rnns_grid_cells.ipynb b/tutorials/move/07_application_rnns_grid_cells.ipynb
similarity index 100%
rename from tutorials/07_application_rnns_grid_cells.ipynb
rename to tutorials/move/07_application_rnns_grid_cells.ipynb
diff --git a/tutorials/08_applications_synthetic_grid_cells.ipynb b/tutorials/move/08_applications_synthetic_grid_cells.ipynb
similarity index 100%
rename from tutorials/08_applications_synthetic_grid_cells.ipynb
rename to tutorials/move/08_applications_synthetic_grid_cells.ipynb
diff --git a/tutorials/10_methods_estimate_manifold_curvature.ipynb b/tutorials/move/10_methods_estimate_manifold_curvature.ipynb
similarity index 100%
rename from tutorials/10_methods_estimate_manifold_curvature.ipynb
rename to tutorials/move/10_methods_estimate_manifold_curvature.ipynb
diff --git a/tutorials/11_visualize_rnn.ipynb b/tutorials/move/11_visualize_rnn.ipynb
similarity index 100%
rename from tutorials/11_visualize_rnn.ipynb
rename to tutorials/move/11_visualize_rnn.ipynb
diff --git a/tutorials/plot_klein_bottle.py b/tutorials/move/plot_klein_bottle.py
similarity index 100%
rename from tutorials/plot_klein_bottle.py
rename to tutorials/move/plot_klein_bottle.py
diff --git a/tutorials/load_runs.py b/tutorials/old_curvature/load_runs.py
similarity index 100%
rename from tutorials/load_runs.py
rename to tutorials/old_curvature/load_runs.py

From 554d0f3c5affd73a3b7f9095a9309cae3f4787ca Mon Sep 17 00:00:00 2001
From: franciscoeacosta <facosta@ucsb.edu>
Date: Tue, 24 Jun 2025 11:02:03 -0700
Subject: [PATCH 5/6] notebook changes

---
 .../01_methods_create_synthetic_data.ipynb    | 15956 ++++++++--------
 1 file changed, 7975 insertions(+), 7981 deletions(-)

diff --git a/tutorials/01_methods_create_synthetic_data.ipynb b/tutorials/01_methods_create_synthetic_data.ipynb
index 3df3e04..1ebba53 100644
--- a/tutorials/01_methods_create_synthetic_data.ipynb
+++ b/tutorials/01_methods_create_synthetic_data.ipynb
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -27,12 +27,34 @@
      "text": [
       "Working directory:  /home/facosta/neurometry/neurometry\n",
       "Directory added to path:  /home/facosta/neurometry\n",
-      "Directory added to path:  /home/facosta/neurometry/neurometry\n",
-      "The autoreload extension is already loaded. To reload it, use:\n",
-      "  %reload_ext autoreload\n",
-      "The jupyter_black extension is already loaded. To reload it, use:\n",
-      "  %reload_ext jupyter_black\n"
+      "Directory added to path:  /home/facosta/neurometry/neurometry\n"
      ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "                <script type=\"application/javascript\" id=\"jupyter_black\">\n",
+       "                (function() {\n",
+       "                    if (window.IPython === undefined) {\n",
+       "                        return\n",
+       "                    }\n",
+       "                    var msg = \"WARNING: it looks like you might have loaded \" +\n",
+       "                        \"jupyter_black in a non-lab notebook with \" +\n",
+       "                        \"`is_lab=True`. Please double check, and if \" +\n",
+       "                        \"loading with `%load_ext` please review the README!\"\n",
+       "                    console.log(msg)\n",
+       "                    alert(msg)\n",
+       "                })()\n",
+       "                </script>\n",
+       "                "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -68,7 +90,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -96,7 +118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -105,7 +127,8 @@
     "    points=task_points,\n",
     "    encoding_dim=3,\n",
     "    nonlinearity=\"sigmoid\",\n",
-    "    scales=gs.array([5, 3, 1]),\n",
+    "    scales=gs.array([1, 1, 1]),\n",
+    "    fano_factor=0.0,\n",
     ")"
    ]
   },
@@ -118,45 +141,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
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r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color,fontWeight:n.weight,fontStyle:n.style,fontVariant:n.variant},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(u.stroke,e.bordercolor).call(u.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var q=e.font,H=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(Y).on(\"edit\",(function(r){e.text=r,this.call(Y),S(\"text\",r),y&&y.autorange&&M(y._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(Y)}else n.selectAll(\"#\"+L).remove();function W(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function Y(r){return r.call(c.font,q).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),v=c.bBox((f?n:G).node()),b=v.width,_=v.height,A=e.width||b,D=e.height||_,B=Math.round(A+2*N),q=Math.round(D+2*N);function H(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var Y=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var K,J,$,Q,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:y,y:x}[et],at=(P+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=q*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ut=e[et+\"anchor\"],ct=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=C[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(Y=!0):Y=!0),K=it._offset+it.r2p(e[et]),Q=.5}else{var dt=\"domain\"===ht;\"x\"===et?($=e[et],K=dt?it._offset+it._length*$:K=T.l+T.w*$):($=1-e[et],K=dt?it._offset+it._length*$:K=T.t+T.h*$),Q=e.showarrow?.5:$}if(e.showarrow){ft.head=K;var vt=e[\"a\"+et];if(tt=ot*H(.5,e.xanchor)-st*H(.5,e.yanchor),nt===rt){var gt=l.getRefType(nt);\"domain\"===gt?(\"y\"===et&&(vt=1-vt),ft.tail=it._offset+it._length*vt):\"paper\"===gt?\"y\"===et?(vt=1-vt,ft.tail=T.t+T.h*vt):ft.tail=T.l+T.w*vt:ft.tail=it._offset+it.r2p(vt),J=tt}else ft.tail=K+vt,J=tt+vt;ft.text=ft.tail+tt;var yt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,yt-1)),\"pixel\"===nt){var mt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-yt;mt>0?(ft.tail+=mt,ft.text+=mt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ct,ft.head+=ct}else J=tt=lt*H(Q,ut),ft.text=K+tt;ft.text+=ct,tt+=ct,J+=ct,e[\"_\"+et+\"padplus\"]=lt/2+J,e[\"_\"+et+\"padminus\"]=lt/2-J,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(Y)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(A-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(c.setClipUrl,U?L:null,t);else{var wt=N+_t-v.top,Tt=N+bt-v.left;G.call(h.positionText,Tt,wt).call(c.setClipUrl,U?L:null,t)}V.select(\"rect\").call(c.setRect,N,N,A,D),j.call(c.setRect,F/2,F/2,B-F,q-F),R.call(c.setTranslate,Math.round(C.x.text-B/2),Math.round(C.y.text-q/2)),I.attr({transform:\"rotate(\"+P+\",\"+C.x.text+\",\"+C.y.text+\")\"});var kt,At=function(r,n){O.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,v=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,v,b),w=o.apply2DTransform(_),A=o.apply2DTransform2(_),L=+j.attr(\"width\"),z=+j.attr(\"height\"),D=v-.5*L,F=D+L,B=b-.5*z,N=B+z,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(A);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=O.append(\"g\").style({opacity:u.opacity(q)}).classed(\"annotation-arrow-g\",!0),W=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(u.stroke,u.rgb(q));if(g(W,H,e),k.annotationPosition&&W.node().parentNode&&!a){var Y=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));Y+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var K,J,$=G.append(\"path\").classed(\"annotation-arrow\",!0).classed(\"anndrag\",!0).classed(\"cursor-move\",!0).attr({d:\"M3,3H-3V-3H3ZM0,0L\"+(h-Y)+\",\"+(p-X),transform:s(Y,X)}).style(\"stroke-width\",V+6+\"px\").call(u.stroke,\"rgba(0,0,0,0)\").call(u.fill,\"rgba(0,0,0,0)\");d.init({element:$.node(),gd:t,prepFn:function(){var t=c.getTranslate(R);K=t.x,J=t.y,y&&y.autorange&&M(y._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0)},moveFn:function(t,r){var n=w(K,J),i=n[0]+t,a=n[1]+r;R.call(c.setTranslate,i,a),S(\"x\",m(y,t,\"x\",T,e)),S(\"y\",m(x,r,\"y\",T,e)),e.axref===e.xref&&S(\"ax\",m(y,t,\"ax\",T,e)),e.ayref===e.yref&&S(\"ay\",m(x,r,\"ay\",T,e)),G.attr(\"transform\",s(t,r)),I.attr({transform:\"rotate(\"+P+\",\"+i+\",\"+a+\")\"})},doneFn:function(){i.call(\"_guiRelayout\",t,E());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}};e.showarrow&&At(0,0),z&&d.init({element:R.node(),gd:t,prepFn:function(){kt=I.attr(\"transform\")},moveFn:function(t,r){var n=\"pointer\";if(e.showarrow)e.axref===e.xref?S(\"ax\",m(y,t,\"ax\",T,e)):S(\"ax\",e.ax+t),e.ayref===e.yref?S(\"ay\",m(x,r,\"ay\",T.w,e)):S(\"ay\",e.ay+r),At(t,r);else{if(a)return;var i,o;if(y)i=m(y,t,\"x\",T,e);else{var l=e._xsize/T.w,u=e.x+(e._xshift-e.xshift)/T.w-l/2;i=d.align(u+t/T.w,l,0,1,e.xanchor)}if(x)o=m(x,r,\"y\",T,e);else{var c=e._ysize/T.h,f=e.y-(e._yshift+e.yshift)/T.h-c/2;o=d.align(f-r/T.h,c,0,1,e.yanchor)}S(\"x\",i),S(\"y\",o),y&&x||(n=d.getCursor(y?.5:i,x?.5:o,e.xanchor,e.yanchor))}I.attr({transform:s(t,r)+kt}),p(R,n)},clickFn:function(r,n){e.captureevents&&t.emit(\"plotly_clickannotation\",W(n))},doneFn:function(){p(R),i.call(\"_guiRelayout\",t,E());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}}t.exports={draw:function(t){var e=t._fullLayout;e._infolayer.selectAll(\".annotation\").remove();for(var r=0;r<e.annotations.length;r++)e.annotations[r].visible&&y(t,r);return a.previousPromises(t)},drawOne:y,drawRaw:x}},33652:function(t,e,r){\"use strict\";var n=r(33428),i=r(76308),a=r(72196),o=r(3400),s=o.strScale,l=o.strRotate,u=o.strTranslate;t.exports=function(t,e,r){var o,c,f,h,p=t.node(),d=a[r.arrowhead||0],v=a[r.startarrowhead||0],g=(r.arrowwidth||1)*(r.arrowsize||1),y=(r.arrowwidth||1)*(r.startarrowsize||1),m=e.indexOf(\"start\")>=0,x=e.indexOf(\"end\")>=0,b=d.backoff*g+r.standoff,_=v.backoff*y+r.startstandoff;if(\"line\"===p.nodeName){o={x:+t.attr(\"x1\"),y:+t.attr(\"y1\")},c={x:+t.attr(\"x2\"),y:+t.attr(\"y2\")};var w=o.x-c.x,T=o.y-c.y;if(h=(f=Math.atan2(T,w))+Math.PI,b&&_&&b+_>Math.sqrt(w*w+T*T))return void z();if(b){if(b*b>w*w+T*T)return void z();var k=b*Math.cos(f),A=b*Math.sin(f);c.x+=k,c.y+=A,t.attr({x2:c.x,y2:c.y})}if(_){if(_*_>w*w+T*T)return void z();var M=_*Math.cos(f),S=_*Math.sin(f);o.x-=M,o.y-=S,t.attr({x1:o.x,y1:o.y})}}else if(\"path\"===p.nodeName){var E=p.getTotalLength(),L=\"\";if(E<b+_)return void z();var C=p.getPointAtLength(0),P=p.getPointAtLength(.1);f=Math.atan2(C.y-P.y,C.x-P.x),o=p.getPointAtLength(Math.min(_,E)),L=\"0px,\"+_+\"px,\";var O=p.getPointAtLength(E),I=p.getPointAtLength(E-.1);h=Math.atan2(O.y-I.y,O.x-I.x),c=p.getPointAtLength(Math.max(0,E-b)),L+=E-(L?_+b:b)+\"px,\"+E+\"px\",t.style(\"stroke-dasharray\",L)}function z(){t.style(\"stroke-dasharray\",\"0px,100px\")}function D(e,a,o,c){e.path&&(e.noRotate&&(o=0),n.select(p.parentNode).append(\"path\").attr({class:t.attr(\"class\"),d:e.path,transform:u(a.x,a.y)+l(180*o/Math.PI)+s(c)}).style({fill:i.rgb(r.arrowcolor),\"stroke-width\":0}))}m&&D(v,o,f,y),x&&D(d,c,h,g)}},79180:function(t,e,r){\"use strict\";var n=r(23816),i=r(42300);t.exports={moduleType:\"component\",name:\"annotations\",layoutAttributes:r(13916),supplyLayoutDefaults:r(45216),includeBasePlot:r(36632)(\"annotations\"),calcAutorange:r(90272),draw:n.draw,drawOne:n.drawOne,drawRaw:n.drawRaw,hasClickToShow:i.hasClickToShow,onClick:i.onClick,convertCoords:r(26828)}},45899:function(t,e,r){\"use strict\";var n=r(13916),i=r(67824).overrideAll,a=r(31780).templatedArray;t.exports=i(a(\"annotation\",{visible:n.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),\"calc\",\"from-root\")},42456:function(t,e,r){\"use strict\";var n=r(3400),i=r(54460);function a(t,e){var r=e.fullSceneLayout.domain,a=e.fullLayout._size,o={pdata:null,type:\"linear\",autorange:!1,range:[-1/0,1/0]};t._xa={},n.extendFlat(t._xa,o),i.setConvert(t._xa),t._xa._offset=a.l+r.x[0]*a.w,t._xa.l2p=function(){return.5*(1+t._pdata[0]/t._pdata[3])*a.w*(r.x[1]-r.x[0])},t._ya={},n.extendFlat(t._ya,o),i.setConvert(t._ya),t._ya._offset=a.t+(1-r.y[1])*a.h,t._ya.l2p=function(){return.5*(1-t._pdata[1]/t._pdata[3])*a.h*(r.y[1]-r.y[0])}}t.exports=function(t){for(var e=t.fullSceneLayout.annotations,r=0;r<e.length;r++)a(e[r],t);t.fullLayout._infolayer.selectAll(\".annotation-\"+t.id).remove()}},52808:function(t,e,r){\"use strict\";var n=r(3400),i=r(54460),a=r(51272),o=r(87192),s=r(45899);function l(t,e,r,a){function l(r,i){return n.coerce(t,e,s,r,i)}function u(t){var n=t+\"axis\",a={_fullLayout:{}};return 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n=r(33428),i=r(38248),a=r(49760),o=r(3400),s=o.pushUnique,l=o.strTranslate,u=o.strRotate,c=r(95924),f=r(72736),h=r(72213),p=r(43616),d=r(76308),v=r(86476),g=r(54460),y=r(24040),m=r(10624),x=r(92456),b=r(77864),_=r(31140),w=x.YANGLE,T=Math.PI*w/180,k=1/Math.sin(T),A=Math.cos(T),M=Math.sin(T),S=x.HOVERARROWSIZE,E=x.HOVERTEXTPAD,L={box:!0,ohlc:!0,violin:!0,candlestick:!0},C={scatter:!0,scattergl:!0,splom:!0};function P(t,e){return t.distance-e.distance}function O(t){return[t.trace.index,t.index,t.x0,t.y0,t.name,t.attr,t.xa?t.xa._id:\"\",t.ya?t.ya._id:\"\"].join(\",\")}e.hover=function(t,e,r,a){t=o.getGraphDiv(t);var l=e.target;o.throttle(t._fullLayout._uid+x.HOVERID,x.HOVERMINTIME,(function(){!function(t,e,r,a,l){r||(r=\"xy\");var u,f,p,x=Array.isArray(r)?r:[r],b=t._fullLayout,_=b.hoversubplots,w=b._plots||[],T=w[r],A=b._has(\"cartesian\"),M=e.hovermode||b.hovermode,E=\"x\"===(M||\"\").charAt(0),I=\"y\"===(M||\"\").charAt(0);if(A&&(E||I)&&\"axis\"===_)for(var D=x.length,U=0;U<D;U++)if(w[u=x[U]]){f=g.getFromId(t,u,\"x\"),p=g.getFromId(t,u,\"y\");var G=(E?f:p)._subplotsWith;if(G&&G.length)for(var W=0;W<G.length;W++)s(x,G[W])}if(T&&\"single\"!==_){var Y=T.overlays.map((function(t){return t.id}));x=x.concat(Y)}for(var X=x.length,Z=new Array(X),K=new Array(X),J=!1,$=0;$<X;$++)if(w[u=x[$]])J=!0,Z[$]=w[u].xaxis,K[$]=w[u].yaxis;else{if(!b[u]||!b[u]._subplot)return void o.warn(\"Unrecognized subplot: \"+u);var Q=b[u]._subplot;Z[$]=Q.xaxis,K[$]=Q.yaxis}if(M&&!J&&(M=\"closest\"),-1===[\"x\",\"y\",\"closest\",\"x unified\",\"y unified\"].indexOf(M)||!t.calcdata||t.querySelector(\".zoombox\")||t._dragging)return v.unhoverRaw(t,e);var tt=b.hoverdistance;-1===tt&&(tt=1/0);var et=b.spikedistance;-1===et&&(et=1/0);var rt,nt,it,at,ot,st,lt,ut,ct,ft,ht,pt,dt,vt=[],gt=[],yt={hLinePoint:null,vLinePoint:null},mt=!1;if(Array.isArray(e))for(M=\"array\",it=0;it<e.length;it++)(ot=t.calcdata[e[it].curveNumber||0])&&(st=ot[0].trace,\"skip\"!==ot[0].trace.hoverinfo&&(gt.push(ot),\"h\"===st.orientation&&(mt=!0)));else{var xt,bt,_t=t.calcdata.slice();for(_t.sort((function(t,e){return(t[0].trace.zorder||0)-(e[0].trace.zorder||0)})),at=0;at<_t.length;at++)ot=_t[at],\"skip\"!==(st=ot[0].trace).hoverinfo&&m.isTraceInSubplots(st,x)&&(gt.push(ot),\"h\"===st.orientation&&(mt=!0));if(l){if(!1===c.triggerHandler(t,\"plotly_beforehover\",e))return;var wt=l.getBoundingClientRect();xt=e.clientX-wt.left,bt=e.clientY-wt.top,b._calcInverseTransform(t);var Tt=o.apply3DTransform(b._invTransform)(xt,bt);if(xt=Tt[0],bt=Tt[1],xt<0||xt>Z[0]._length||bt<0||bt>K[0]._length)return v.unhoverRaw(t,e)}else xt=\"xpx\"in e?e.xpx:Z[0]._length/2,bt=\"ypx\"in e?e.ypx:K[0]._length/2;if(e.pointerX=xt+Z[0]._offset,e.pointerY=bt+K[0]._offset,rt=\"xval\"in e?m.flat(x,e.xval):m.p2c(Z,xt),nt=\"yval\"in e?m.flat(x,e.yval):m.p2c(K,bt),!i(rt[0])||!i(nt[0]))return o.warn(\"Fx.hover failed\",e,t),v.unhoverRaw(t,e)}var kt=1/0;function At(r,n){for(at=0;at<gt.length;at++)if((ot=gt[at])&&ot[0]&&ot[0].trace&&!0===(st=ot[0].trace).visible&&0!==st._length&&-1===[\"carpet\",\"contourcarpet\"].indexOf(st._module.name)){if(ct=M,m.isUnifiedHover(ct)&&(ct=ct.charAt(0)),\"splom\"===st.type?lt=x[ut=0]:(lt=m.getSubplot(st),ut=x.indexOf(lt)),pt={cd:ot,trace:st,xa:Z[ut],ya:K[ut],maxHoverDistance:tt,maxSpikeDistance:et,index:!1,distance:Math.min(kt,tt),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:d.defaultLine,name:st.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},b[lt]&&(pt.subplot=b[lt]._subplot),b._splomScenes&&b._splomScenes[st.uid]&&(pt.scene=b._splomScenes[st.uid]),\"array\"===ct){var a=e[at];\"pointNumber\"in a?(pt.index=a.pointNumber,ct=\"closest\"):(ct=\"\",\"xval\"in a&&(ft=a.xval,ct=\"x\"),\"yval\"in a&&(ht=a.yval,ct=ct?\"closest\":\"y\"))}else void 0!==r&&void 0!==n?(ft=r,ht=n):(ft=rt[ut],ht=nt[ut]);if(dt=vt.length,0!==tt)if(st._module&&st._module.hoverPoints){var s=st._module.hoverPoints(pt,ft,ht,ct,{finiteRange:!0,hoverLayer:b._hoverlayer,hoversubplots:_,gd:t});if(s)for(var l,u=0;u<s.length;u++)l=s[u],i(l.x0)&&i(l.y0)&&vt.push(B(l,M))}else o.log(\"Unrecognized trace type in hover:\",st);if(\"closest\"===M&&vt.length>dt&&(vt.splice(0,dt),kt=vt[0].distance),A&&0!==et&&0===vt.length){pt.distance=et,pt.index=!1;var c=st._module.hoverPoints(pt,ft,ht,\"closest\",{hoverLayer:b._hoverlayer});if(c&&(c=c.filter((function(t){return t.spikeDistance<=et}))),c&&c.length){var f,h=c.filter((function(t){return t.xa.showspikes&&\"hovered data\"!==t.xa.spikesnap}));if(h.length){var p=h[0];i(p.x0)&&i(p.y0)&&(f=St(p),(!yt.vLinePoint||yt.vLinePoint.spikeDistance>f.spikeDistance)&&(yt.vLinePoint=f))}var v=c.filter((function(t){return t.ya.showspikes&&\"hovered data\"!==t.ya.spikesnap}));if(v.length){var g=v[0];i(g.x0)&&i(g.y0)&&(f=St(g),(!yt.hLinePoint||yt.hLinePoint.spikeDistance>f.spikeDistance)&&(yt.hLinePoint=f))}}}}}function Mt(t,e,r){for(var n,i=null,a=1/0,o=0;o<t.length;o++)f&&f._id!==t[o].xa._id||p&&p._id!==t[o].ya._id||(n=t[o].spikeDistance,r&&0===o&&(n=-1/0),n<=a&&n<=e&&(i=t[o],a=n));return i}function St(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}At();var Et={fullLayout:b,container:b._hoverlayer,event:e},Lt=t._spikepoints,Ct={vLinePoint:yt.vLinePoint,hLinePoint:yt.hLinePoint};t._spikepoints=Ct;var Pt=function(){var t=vt.filter((function(t){return f&&f._id===t.xa._id&&p&&p._id===t.ya._id})),e=vt.filter((function(t){return!(f&&f._id===t.xa._id&&p&&p._id===t.ya._id)}));t.sort(P),e.sort(P),vt=function(t,e){for(var r=e.charAt(0),n=[],i=[],a=[],o=0;o<t.length;o++){var s=t[o];y.traceIs(s.trace,\"bar-like\")||y.traceIs(s.trace,\"box-violin\")?a.push(s):s.trace[r+\"period\"]?i.push(s):n.push(s)}return n.concat(i).concat(a)}(vt=t.concat(e),M)};Pt();var Ot=M.charAt(0),It=(\"x\"===Ot||\"y\"===Ot)&&vt[0]&&C[vt[0].trace.type];if(A&&0!==et&&0!==vt.length){var zt=Mt(vt.filter((function(t){return t.ya.showspikes})),et,It);yt.hLinePoint=St(zt);var Dt=Mt(vt.filter((function(t){return t.xa.showspikes})),et,It);yt.vLinePoint=St(Dt)}if(0===vt.length){var Rt=v.unhoverRaw(t,e);return!A||null===yt.hLinePoint&&null===yt.vLinePoint||j(Lt)&&N(t,yt,Et),Rt}if(A&&j(Lt)&&N(t,yt,Et),m.isXYhover(ct)&&0!==vt[0].length&&\"splom\"!==vt[0].trace.type){var Ft=vt[0],Bt=(vt=L[Ft.trace.type]?vt.filter((function(t){return t.trace.index===Ft.trace.index})):[Ft]).length;At(V(\"x\",Ft,b),V(\"y\",Ft,b));var Nt,jt=[],Ut={},Vt=0,qt=function(t){var e=L[t.trace.type]?O(t):t.trace.index;if(Ut[e]){var r=Ut[e]-1,n=jt[r];r>0&&Math.abs(t.distance)<Math.abs(n.distance)&&(jt[r]=t)}else Vt++,Ut[e]=Vt,jt.push(t)};for(Nt=0;Nt<Bt;Nt++)qt(vt[Nt]);for(Nt=vt.length-1;Nt>Bt-1;Nt--)qt(vt[Nt]);vt=jt,Pt()}var Ht=t._hoverdata,Gt=[],Wt=q(t),Yt=H(t);for(it=0;it<vt.length;it++){var Xt=vt[it],Zt=m.makeEventData(Xt,Xt.trace,Xt.cd);if(!1!==Xt.hovertemplate){var Kt=!1;Xt.cd[Xt.index]&&Xt.cd[Xt.index].ht&&(Kt=Xt.cd[Xt.index].ht),Xt.hovertemplate=Kt||Xt.trace.hovertemplate||!1}if(Xt.xa&&Xt.ya){var Jt=Xt.x0+Xt.xa._offset,$t=Xt.x1+Xt.xa._offset,Qt=Xt.y0+Xt.ya._offset,te=Xt.y1+Xt.ya._offset,ee=Math.min(Jt,$t),re=Math.max(Jt,$t),ne=Math.min(Qt,te),ie=Math.max(Qt,te);Zt.bbox={x0:ee+Yt,x1:re+Yt,y0:ne+Wt,y1:ie+Wt}}Xt.eventData=[Zt],Gt.push(Zt)}t._hoverdata=Gt;var ae=\"y\"===M&&(gt.length>1||vt.length>1)||\"closest\"===M&&mt&&vt.length>1,oe=d.combine(b.plot_bgcolor||d.background,b.paper_bgcolor),se=z(vt,{gd:t,hovermode:M,rotateLabels:ae,bgColor:oe,container:b._hoverlayer,outerContainer:b._paper.node(),commonLabelOpts:b.hoverlabel,hoverdistance:b.hoverdistance}),le=se.hoverLabels;if(m.isUnifiedHover(M)||(function(t,e,r,n){var i,a,o,s,l,u,c,f=e?\"xa\":\"ya\",h=e?\"ya\":\"xa\",p=0,d=1,v=t.size(),g=new Array(v),y=0,m=n.minX,x=n.maxX,b=n.minY,_=n.maxY,w=function(t){return t*r._invScaleX},T=function(t){return t*r._invScaleY};function A(t){var e=t[0],r=t[t.length-1];if(a=e.pmin-e.pos-e.dp+e.size,o=r.pos+r.dp+r.size-e.pmax,a>.01){for(l=t.length-1;l>=0;l--)t[l].dp+=a;i=!1}if(!(o<.01)){if(a<-.01){for(l=t.length-1;l>=0;l--)t[l].dp-=o;i=!1}if(i){var n=0;for(s=0;s<t.length;s++)(u=t[s]).pos+u.dp+u.size>e.pmax&&n++;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos>e.pmax-1&&(u.del=!0,n--);for(s=0;s<t.length&&!(n<=0);s++)if((u=t[s]).pos<e.pmin+1)for(u.del=!0,n--,o=2*u.size,l=t.length-1;l>=0;l--)t[l].dp-=o;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos+u.dp+u.size>e.pmax&&(u.del=!0,n--)}}}for(t.each((function(t){var n=t[f],i=t[h],a=\"x\"===n._id.charAt(0),o=n.range;0===y&&o&&o[0]>o[1]!==a&&(d=-1);var s=0,l=a?r.width:r.height;if(\"x\"===r.hovermode||\"y\"===r.hovermode){var u,c,p=R(t,e),v=t.anchor,A=\"end\"===v?-1:1;if(\"middle\"===v)c=(u=t.crossPos+(a?T(p.y-t.by/2):w(t.bx/2+t.tx2width/2)))+(a?T(t.by):w(t.bx));else if(a)c=(u=t.crossPos+T(S+p.y)-T(t.by/2-S))+T(t.by);else{var M=w(A*S+p.x),E=M+w(A*t.bx);u=t.crossPos+Math.min(M,E),c=t.crossPos+Math.max(M,E)}a?void 0!==b&&void 0!==_&&Math.min(c,_)-Math.max(u,b)>1&&(\"left\"===i.side?(s=i._mainLinePosition,l=r.width):l=i._mainLinePosition):void 0!==m&&void 0!==x&&Math.min(c,x)-Math.max(u,m)>1&&(\"top\"===i.side?(s=i._mainLinePosition,l=r.height):l=i._mainLinePosition)}g[y++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(a?k:1)/2,pmin:s,pmax:l}]})),g.sort((function(t,e){return t[0].posref-e[0].posref||d*(e[0].traceIndex-t[0].traceIndex)}));!i&&p<=v;){for(p++,i=!0,s=0;s<g.length-1;){var M=g[s],E=g[s+1],L=M[M.length-1],C=E[0];if((a=L.pos+L.dp+L.size-C.pos-C.dp+C.size)>.01&&L.pmin===C.pmin&&L.pmax===C.pmax){for(l=E.length-1;l>=0;l--)E[l].dp+=a;for(M.push.apply(M,E),g.splice(s+1,1),c=0,l=M.length-1;l>=0;l--)c+=M[l].dp;for(o=c/M.length,l=M.length-1;l>=0;l--)M[l].dp-=o;i=!1}else s++}g.forEach(A)}for(s=g.length-1;s>=0;s--){var P=g[s];for(l=P.length-1;l>=0;l--){var O=P[l],I=O.datum;I.offset=O.dp,I.del=O.del}}}(le,ae,b,se.commonLabelBoundingBox),F(le,ae,b._invScaleX,b._invScaleY)),l&&l.tagName){var ue=y.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,Gt);h(n.select(l),ue?\"pointer\":\"\")}l&&!a&&function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Ht)&&(Ht&&t.emit(\"plotly_unhover\",{event:e,points:Ht}),t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:Z,yaxes:K,xvals:rt,yvals:nt}))}(t,e,r,a,l)}))},e.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=q(i),o=H(i),s=z(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,u=t.eventData;if(u){var c=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),p=Math.max(s,l),v=t.trace;if(y.traceIs(v,\"gl3d\")){var g=i._fullLayout[v.scene]._scene.container,m=g.offsetLeft,x=g.offsetTop;c+=m,f+=m,h+=x,p+=x}u.bbox={x0:c+o,x1:f+o,y0:h+a,y1:p+a},e.inOut_bbox&&e.inOut_bbox.push(u.bbox)}else u=!1;return{color:t.color||d.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,fontWeight:t.fontWeight,fontStyle:t.fontStyle,fontVariant:t.fontVariant,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:u}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||d.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}).hoverLabels,l=0,u=0;return s.sort((function(t,e){return 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0),-1===p.indexOf(\"name\")&&(t.name=void 0)),t}function N(t,e,r){var n,i,o=r.container,s=r.fullLayout,l=s._size,u=r.event,c=!!e.hLinePoint,f=!!e.vLinePoint;if(o.selectAll(\".spikeline\").remove(),f||c){var h=d.combine(s.plot_bgcolor,s.paper_bgcolor);if(c){var v,y,m=e.hLinePoint;n=m&&m.xa,\"cursor\"===(i=m&&m.ya).spikesnap?(v=u.pointerX,y=u.pointerY):(v=n._offset+m.x,y=i._offset+m.y);var x,b,_=a.readability(m.color,h)<1.5?d.contrast(h):m.color,w=i.spikemode,T=i.spikethickness,k=i.spikecolor||_,A=g.getPxPosition(t,i);if(-1!==w.indexOf(\"toaxis\")||-1!==w.indexOf(\"across\")){if(-1!==w.indexOf(\"toaxis\")&&(x=A,b=v),-1!==w.indexOf(\"across\")){var 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A=v._isShape;(v.showlegend||v._dfltShowLegend&&!(v._module&&v._module.attributes&&v._module.attributes.showlegend&&!1===v._module.attributes.showlegend.dflt))&&(x++,v.showlegend&&(b=!0,(!A&&n.traceIs(v,\"pie-like\")||!0===v._input.showlegend)&&x++),i.coerceFont(g,\"legendgrouptitle.font\",m)),(!A&&n.traceIs(v,\"bar\")&&\"stack\"===r.barmode||-1!==[\"tonextx\",\"tonexty\"].indexOf(v.fill))&&(_=u.isGrouped({traceorder:_})?\"grouped+reversed\":\"reversed\"),void 0!==v.legendgroup&&\"\"!==v.legendgroup&&(_=u.isReversed({traceorder:_})?\"reversed+grouped\":\"grouped\")}var M=i.coerce(e,r,l,\"showlegend\",b&&x>(\"legend\"===t?1:0));if(!1===M&&(r[t]=void 0),(!1!==M||f.uirevision)&&(p(\"uirevision\",r.uirevision),!1!==M)){p(\"borderwidth\");var S,E,L,C=\"h\"===p(\"orientation\"),P=\"paper\"===p(\"yref\"),O=\"paper\"===p(\"xref\"),I=\"left\";if(C?(S=0,n.getComponentMethod(\"rangeslider\",\"isVisible\")(e.xaxis)?P?(E=1.1,L=\"bottom\"):(E=1,L=\"top\"):P?(E=-.1,L=\"top\"):(E=0,L=\"bottom\")):(E=1,L=\"auto\",O?S=1.02:(S=1,I=\"right\")),i.coerce(f,h,{x:{valType:\"number\",editType:\"legend\",min:O?-2:0,max:O?3:1,dflt:S}},\"x\"),i.coerce(f,h,{y:{valType:\"number\",editType:\"legend\",min:P?-2:0,max:P?3:1,dflt:E}},\"y\"),p(\"traceorder\",_),u.isGrouped(r[t])&&p(\"tracegroupgap\"),p(\"entrywidth\"),p(\"entrywidthmode\"),p(\"indentation\"),p(\"itemsizing\"),p(\"itemwidth\"),p(\"itemclick\"),p(\"itemdoubleclick\"),p(\"groupclick\"),p(\"xanchor\",I),p(\"yanchor\",L),p(\"valign\"),i.noneOrAll(f,h,[\"x\",\"y\"]),p(\"title.text\")){p(\"title.side\",C?\"left\":\"top\");var z=i.extendFlat({},d,{size:i.bigFont(d.size)});i.coerceFont(p,\"title.font\",z)}}}}t.exports=function(t,e,r){var n,a=r.slice(),o=e.shapes;if(o)for(n=0;n<o.length;n++){var 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t=n.event.sourceEvent;\"touchstart\"===t.type&&(D=t.changedTouches[0].clientY,F=Z)})).on(\"drag\",(function(){var t=n.event.sourceEvent;\"touchmove\"===t.type&&(R=t.changedTouches[0].clientY,Z=function(t,e,r){var n=(e-r)/X+t;return i.constrain(n,0,Y)}(F,D,R),$(Z,B,X))}));q.call(J)}function $(e,r,n){h._scrollY=t._fullLayout[w]._scrollY=e,u.setTranslate(q,0,-e),u.setRect(G,h._width,p.scrollBarMargin+e*n,p.scrollBarWidth,r),j.select(\"rect\").attr(\"y\",_+e)}t._context.edits.legendPosition&&(N.classed(\"cursor-move\",!0),l.init({element:N.node(),gd:t,prepFn:function(){var t=u.getTranslate(N);m=t.x,x=t.y},moveFn:function(t,r){var n=m+t,i=x+r;u.setTranslate(N,n,i),e=l.align(n,h._width,b.l,b.l+b.w,h.xanchor),c=l.align(i+h._height,-h._height,b.t+b.h,b.t,h.yanchor)},doneFn:function(){if(void 0!==e&&void 0!==c){var r={};r[w+\".x\"]=e,r[w+\".y\"]=c,o.call(\"_guiRelayout\",t,r)}},clickFn:function(e,r){var n=s.selectAll(\"g.traces\").filter((function(){var t=this.getBoundingClientRect();return 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r=Math.max(4,e);if(t&&t.trim().length>=r/2)return t;for(var n=r-(t=t||\"\").length;n>0;n--)t+=\" \";return t}function E(t,e,r){var a,o=e._context.doubleClickDelay,s=1,l=i.ensureSingle(t,\"rect\",r+\"toggle\",(function(t){e._context.staticPlot||t.style(\"cursor\",\"pointer\").attr(\"pointer-events\",\"all\"),t.call(c.fill,\"rgba(0,0,0,0)\")}));e._context.staticPlot||(l.on(\"mousedown\",(function(){(a=(new Date).getTime())-e._legendMouseDownTime<o?s+=1:(s=1,e._legendMouseDownTime=a)})),l.on(\"mouseup\",(function(){if(!e._dragged&&!e._editing){var i=e._fullLayout[r];(new Date).getTime()-e._legendMouseDownTime>o&&(s=Math.max(s-1,1)),A(e,i,t,s,n.event)}})))}function L(t,e,r,n,i){n._inHover&&t.attr(\"data-notex\",!0),f.convertToTspans(t,r,(function(){!function(t,e,r,n){var i=t.data()[0][0];if(r._inHover||!i||i.trace.showlegend){var a=t.select(\"g[class*=math-group]\"),o=a.node(),s=O(r);r||(r=e._fullLayout[s]);var 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r=t._fullLayout,i=r._legends;r._infolayer.selectAll('[class^=\"legend\"]').each((function(){var t=n.select(this),e=t.attr(\"class\").split(\" \")[0];e.match(w)&&-1===i.indexOf(e)&&t.remove()}));for(var a=0;a<i.length;a++){var o=i[a];T(t,t._fullLayout[o])}}}},35456:function(t,e,r){\"use strict\";var n=r(24040),i=r(42451);t.exports=function(t,e,r){var a,o,s=e._inHover,l=i.isGrouped(e),u=i.isReversed(e),c={},f=[],h=!1,p={},d=0,v=0;function g(t,n,a){if(!1!==e.visible&&(!r||t===e._id))if(\"\"!==n&&i.isGrouped(e))-1===f.indexOf(n)?(f.push(n),h=!0,c[n]=[a]):c[n].push(a);else{var o=\"~~i\"+d;f.push(o),c[o]=[a],d++}}for(a=0;a<t.length;a++){var y=t[a],m=y[0],x=m.trace,b=x.legend,_=x.legendgroup;if(s||x.visible&&x.showlegend)if(n.traceIs(x,\"pie-like\"))for(p[_]||(p[_]={}),o=0;o<y.length;o++){var w=y[o].label;p[_][w]||(g(b,_,{label:w,color:y[o].color,i:y[o].i,trace:x,pts:y[o].pts}),p[_][w]=!0,v=Math.max(v,(w||\"\").length))}else 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t.showlegend})),y=v.concat(g),m=d.trace;m._isShape&&(m=m._fullInput);var x,b,_,w,T,k=m.legendgroup,A={},M=[],S=[],E=[],L=(s.shapes||[]).map((function(t){return t._input})),C=!1,P=m.legend,O=m._fullInput;if(O&&O._isShape||!n.traceIs(m,\"pie-like\")){var I,z=k&&k.length,D=[];if(z)for(x=0;x<y.length;x++)(I=y[x]).visible&&I.legendgroup===k&&D.push(x);if(\"toggle\"===l){var R;switch(m.visible){case!0:R=\"legendonly\";break;case!1:R=!1;break;case\"legendonly\":R=!0}if(z)if(h)for(x=0;x<y.length;x++){var F=y[x];!1!==F.visible&&F.legendgroup===k&&tt(F,R)}else tt(m,R);else tt(m,R)}else if(\"toggleothers\"===l){var 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e=t[0].trace,r=\"waterfall\"===e.type;if(t[0]._distinct&&r){var i=t[0].trace[t[0].dir].marker;return t[0].mc=i.color,t[0].mlw=i.line.width,t[0].mlc=i.line.color,T(t,this,\"waterfall\")}var a=[];e.visible&&r&&(a=t[0].hasTotals?[[\"increasing\",\"M-6,-6V6H0Z\"],[\"totals\",\"M6,6H0L-6,-6H-0Z\"],[\"decreasing\",\"M6,6V-6H0Z\"]]:[[\"increasing\",\"M-6,-6V6H6Z\"],[\"decreasing\",\"M6,6V-6H-6Z\"]]);var o=n.select(this).select(\"g.legendpoints\").selectAll(\"path.legendwaterfall\").data(a);o.enter().append(\"path\").classed(\"legendwaterfall\",!0).attr(\"transform\",_).style(\"stroke-miterlimit\",1),o.exit().remove(),o.each((function(t){var r=n.select(this),i=e[t[0]].marker,a=w(void 0,i.line,5,2);r.attr(\"d\",t[1]).style(\"stroke-width\",a+\"px\").call(l.fill,i.color),a&&r.call(l.stroke,i.line.color)}))})).each((function(t){T(t,this,\"funnel\")})).each((function(t){T(t,this)})).each((function(t){var 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r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},c.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return u(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},c.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return u(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},c.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return u(t,\"Zoom 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h,p=r.modeBarButtons;h=Array.isArray(p)&&p.length?function(t){for(var e=c([],t),r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++){var a=n[i];if(\"string\"==typeof a){if(void 0===l[a])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));e[r][i]=l[a]}}return e}(p):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function c(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(c(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(c(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),v=e._has(\"cartesian\"),g=e._has(\"gl3d\"),y=e._has(\"geo\"),m=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"smith\"),A=e._has(\"sankey\"),M=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),S=o(e.hovermode),E=[];function L(t){if(t.length){for(var e=[],r=0;r<t.length;r++){for(var n=t[r],i=l[n],a=i.name.toLowerCase(),o=(i._cat||i.name).toLowerCase(),s=!1,u=0;u<d.length;u++){var c=d[u].toLowerCase();if(c===a||c===o){s=!0;break}}s||e.push(l[n])}E.push(e)}}var C=[\"toImage\"];s.showEditInChartStudio?C.push(\"editInChartStudio\"):s.showSendToCloud&&C.push(\"sendDataToCloud\"),L(C);var P=[],O=[],I=[],z=[];(v||b||m||x||_)+y+g+w+T+k>1?(O=[\"toggleHover\"],I=[\"resetViews\"]):y?(P=[\"zoomInGeo\",\"zoomOutGeo\"],O=[\"hoverClosestGeo\"],I=[\"resetGeo\"]):g?(O=[\"hoverClosest3d\"],I=[\"resetCameraDefault3d\",\"resetCameraLastSave3d\"]):w?(P=[\"zoomInMapbox\",\"zoomOutMapbox\"],O=[\"toggleHover\"],I=[\"resetViewMapbox\"]):b?O=[\"hoverClosestGl2d\"]:m?O=[\"hoverClosestPie\"]:A?(O=[\"hoverClosestCartesian\",\"hoverCompareCartesian\"],I=[\"resetViewSankey\"]):O=[\"toggleHover\"],v&&(O=[\"toggleSpikelines\",\"hoverClosestCartesian\",\"hoverCompareCartesian\"]),(function(t){for(var e=0;e<t.length;e++)if(!a.traceIs(t[e],\"noHover\"))return!1;return!0}(r)||S)&&(O=[]),!v&&!b||M||(P=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],\"resetViews\"!==I[0]&&(I=[\"resetScale2d\"])),g?z=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:(v||b)&&!M||_?z=[\"zoom2d\",\"pan2d\"]:w||y?z=[\"pan2d\"]:T&&(z=[\"zoom2d\"]),function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var 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L(z),L(P.concat(I)),L(D),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(E,p)}(t),f?f.update(t,h):e._modeBar=s(t,h)}else f&&(f.destroy(),delete e._modeBar)}},66400:function(t,e,r){\"use strict\";var n=r(33428),i=r(38248),a=r(3400),o=r(9224),s=r(25788).version,l=new DOMParser;function u(t){this.container=t.container,this.element=document.createElement(\"div\"),this.update(t.graphInfo,t.buttons),this.container.appendChild(this.element)}var c=u.prototype;c.update=function(t,e){this.graphInfo=t;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i=\"modebar-\"+n._uid;this.element.setAttribute(\"id\",i),this._uid=i,this.element.className=\"modebar\",\"hover\"===r.displayModeBar&&(this.element.className+=\" modebar--hover ease-bg\"),\"v\"===n.modebar.orientation&&(this.element.className+=\" vertical\",e=e.reverse());var o=n.modebar,s=\"hover\"===r.displayModeBar?\".js-plotly-plot .plotly:hover \":\"\";a.deleteRelatedStyleRule(i),a.addRelatedStyleRule(i,s+\"#\"+i+\" .modebar-group\",\"background-color: \"+o.bgcolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn .icon path\",\"fill: \"+o.color),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn:hover .icon path\",\"fill: \"+o.activecolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn.active .icon path\",\"fill: \"+o.activecolor);var l=!this.hasButtons(e),u=this.hasLogo!==r.displaylogo,c=this.locale!==r.locale;if(this.locale=r.locale,(l||u||c)&&(this.removeAllButtons(),this.updateButtons(e),r.watermark||r.displaylogo)){var f=this.getLogo();r.watermark&&(f.className=f.className+\" watermark\"),\"v\"===n.modebar.orientation?this.element.insertBefore(f,this.element.childNodes[0]):this.element.appendChild(f),this.hasLogo=!0}this.updateActiveButton()},c.updateButtons=function(t){var e=this;this.buttons=t,this.buttonElements=[],this.buttonsNames=[],this.buttons.forEach((function(t){var r=e.createGroup();t.forEach((function(t){var n=t.name;if(!n)throw new Error(\"must provide button 'name' in button config\");if(-1!==e.buttonsNames.indexOf(n))throw new Error(\"button name '\"+n+\"' is taken\");e.buttonsNames.push(n);var i=e.createButton(t);e.buttonElements.push(i),r.appendChild(i)})),e.element.appendChild(r)}))},c.createGroup=function(){var t=document.createElement(\"div\");return t.className=\"modebar-group\",t},c.createButton=function(t){var e=this,r=document.createElement(\"a\");r.setAttribute(\"rel\",\"tooltip\"),r.className=\"modebar-btn\";var i=t.title;void 0===i?i=t.name:\"function\"==typeof i&&(i=i(this.graphInfo)),(i||0===i)&&r.setAttribute(\"data-title\",i),void 0!==t.attr&&r.setAttribute(\"data-attr\",t.attr);var a=t.val;if(void 0!==a&&(\"function\"==typeof a&&(a=a(this.graphInfo)),r.setAttribute(\"data-val\",a)),\"function\"!=typeof t.click)throw new Error(\"must provide button 'click' function in button config\");r.addEventListener(\"click\",(function(r){t.click(e.graphInfo,r),e.updateActiveButton(r.currentTarget)})),r.setAttribute(\"data-toggle\",t.toggle||!1),t.toggle&&n.select(r).classed(\"active\",!0);var s=t.icon;return\"function\"==typeof s?r.appendChild(s()):r.appendChild(this.createIcon(s||o.question)),r.setAttribute(\"data-gravity\",t.gravity||\"n\"),r},c.createIcon=function(t){var e,r=i(t.height)?Number(t.height):t.ascent-t.descent,n=\"http://www.w3.org/2000/svg\";if(t.path){(e=document.createElementNS(n,\"svg\")).setAttribute(\"viewBox\",[0,0,t.width,r].join(\" \")),e.setAttribute(\"class\",\"icon\");var a=document.createElementNS(n,\"path\");a.setAttribute(\"d\",t.path),t.transform?a.setAttribute(\"transform\",t.transform):void 0!==t.ascent&&a.setAttribute(\"transform\",\"matrix(1 0 0 -1 0 \"+t.ascent+\")\"),e.appendChild(a)}return t.svg&&(e=l.parseFromString(t.svg,\"application/xml\").childNodes[0]),e.setAttribute(\"height\",\"1em\"),e.setAttribute(\"width\",\"1em\"),e},c.updateActiveButton=function(t){var e=this.graphInfo._fullLayout,r=void 0!==t?t.getAttribute(\"data-attr\"):null;this.buttonElements.forEach((function(t){var i=t.getAttribute(\"data-val\")||!0,o=t.getAttribute(\"data-attr\"),s=\"true\"===t.getAttribute(\"data-toggle\"),l=n.select(t);if(s)o===r&&l.classed(\"active\",!l.classed(\"active\"));else{var u=null===o?o:a.nestedProperty(e,o).get();l.classed(\"active\",u===i)}}))},c.hasButtons=function(t){var e=this.buttons;if(!e)return!1;if(t.length!==e.length)return!1;for(var r=0;r<t.length;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;n++)if(t[r][n].name!==e[r][n].name)return!1}return!0},c.getLogo=function(){var t=this.createGroup(),e=document.createElement(\"a\");return e.href=\"https://plotly.com/\",e.target=\"_blank\",e.setAttribute(\"data-title\",a._(this.graphInfo,\"Produced with Plotly.js\")+\" (v\"+s+\")\"),e.className=\"modebar-btn plotlyjsicon modebar-btn--logo\",e.appendChild(this.createIcon(o.newplotlylogo)),t.appendChild(e),t},c.removeAllButtons=function(){for(;this.element.firstChild;)this.element.removeChild(this.element.firstChild);this.hasLogo=!1},c.destroy=function(){a.removeElement(this.container.querySelector(\".modebar\")),a.deleteRelatedStyleRule(this._uid)},t.exports=function(t,e){var r=t._fullLayout,i=new u({graphInfo:t,container:r._modebardiv.node(),buttons:e});return r._privateplot&&n.select(i.element).append(\"span\").classed(\"badge-private float--left\",!0).text(\"PRIVATE\"),i}},26680:function(t,e,r){\"use strict\";var n=r(25376),i=r(22548),a=(0,r(31780).templatedArray)(\"button\",{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},step:{valType:\"enumerated\",values:[\"month\",\"year\",\"day\",\"hour\",\"minute\",\"second\",\"all\"],dflt:\"month\",editType:\"plot\"},stepmode:{valType:\"enumerated\",values:[\"backward\",\"todate\"],dflt:\"backward\",editType:\"plot\"},count:{valType:\"number\",min:0,dflt:1,editType:\"plot\"},label:{valType:\"string\",editType:\"plot\"},editType:\"plot\"});t.exports={visible:{valType:\"boolean\",editType:\"plot\"},buttons:a,x:{valType:\"number\",min:-2,max:3,editType:\"plot\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"plot\"},y:{valType:\"number\",min:-2,max:3,editType:\"plot\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"bottom\",editType:\"plot\"},font:n({editType:\"plot\"}),bgcolor:{valType:\"color\",dflt:i.lightLine,editType:\"plot\"},activecolor:{valType:\"color\",editType:\"plot\"},bordercolor:{valType:\"color\",dflt:i.defaultLine,editType:\"plot\"},borderwidth:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"}},85984:function(t){\"use 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g=d(\"bgcolor\");d(\"activecolor\",i.contrast(g,l.lightAmount,l.darkAmount)),d(\"bordercolor\"),d(\"borderwidth\")}}},50216:function(t,e,r){\"use strict\";var n=r(33428),i=r(24040),a=r(7316),o=r(76308),s=r(43616),l=r(3400),u=l.strTranslate,c=r(72736),f=r(79811),h=r(84284),p=h.LINE_SPACING,d=h.FROM_TL,v=h.FROM_BR,g=r(85984),y=r(48040);function m(t){return t._id}function x(t,e,r){var n=l.ensureSingle(t,\"rect\",\"selector-rect\",(function(t){t.attr(\"shape-rendering\",\"crispEdges\")}));n.attr({rx:g.rx,ry:g.ry}),n.call(o.stroke,e.bordercolor).call(o.fill,function(t,e){return e._isActive||e._isHovered?t.activecolor:t.bgcolor}(e,r)).style(\"stroke-width\",e.borderwidth+\"px\")}function b(t,e,r,n){var i,a;l.ensureSingle(t,\"text\",\"selector-text\",(function(t){t.attr(\"text-anchor\",\"middle\")})).call(s.font,e.font).text((i=r,a=n._fullLayout._meta,i.label?a?l.templateString(i.label,a):i.label:\"all\"===i.step?\"all\":i.count+i.step.charAt(0))).call((function(t){c.convertToTspans(t,n)}))}t.exports=function(t){var e=t._fullLayout._infolayer.selectAll(\".rangeselector\").data(function(t){for(var e=f.list(t,\"x\",!0),r=[],n=0;n<e.length;n++){var i=e[n];i.rangeselector&&i.rangeselector.visible&&r.push(i)}return r}(t),m);e.enter().append(\"g\").classed(\"rangeselector\",!0),e.exit().remove(),e.style({cursor:\"pointer\",\"pointer-events\":\"all\"}),e.each((function(e){var r=n.select(this),o=e,f=o.rangeselector,h=r.selectAll(\"g.button\").data(l.filterVisible(f.buttons));h.enter().append(\"g\").classed(\"button\",!0),h.exit().remove(),h.each((function(e){var r=n.select(this),a=y(o,e);e._isActive=function(t,e,r){if(\"all\"===e.step)return!0===t.autorange;var n=Object.keys(r);return t.range[0]===r[n[0]]&&t.range[1]===r[n[1]]}(o,e,a),r.call(x,f,e),r.call(b,f,e,t),r.on(\"click\",(function(){t._dragged||i.call(\"_guiRelayout\",t,a)})),r.on(\"mouseover\",(function(){e._isHovered=!0,r.call(x,f,e)})),r.on(\"mouseout\",(function(){e._isHovered=!1,r.call(x,f,e)}))})),function(t,e,r,i,o){var f=0,h=0,y=r.borderwidth;e.each((function(){var t=n.select(this).select(\".selector-text\"),e=r.font.size*p,i=Math.max(e*c.lineCount(t),16)+3;h=Math.max(h,i)})),e.each((function(){var t=n.select(this),e=t.select(\".selector-rect\"),i=t.select(\".selector-text\"),a=i.node()&&s.bBox(i.node()).width,o=r.font.size*p,l=c.lineCount(i),d=Math.max(a+10,g.minButtonWidth);t.attr(\"transform\",u(y+f,y)),e.attr({x:0,y:0,width:d,height:h}),c.positionText(i,d/2,h/2-(l-1)*o/2+3),f+=d+5}));var m=t._fullLayout._size,x=m.l+m.w*r.x,b=m.t+m.h*(1-r.y),_=\"left\";l.isRightAnchor(r)&&(x-=f,_=\"right\"),l.isCenterAnchor(r)&&(x-=f/2,_=\"center\");var w=\"top\";l.isBottomAnchor(r)&&(b-=h,w=\"bottom\"),l.isMiddleAnchor(r)&&(b-=h/2,w=\"middle\"),f=Math.ceil(f),h=Math.ceil(h),x=Math.round(x),b=Math.round(b),a.autoMargin(t,i+\"-range-selector\",{x:r.x,y:r.y,l:f*d[_],r:f*v[_],b:h*v[w],t:h*d[w]}),o.attr(\"transform\",u(x,b))}(t,h,f,o._name,r)}))}},48040:function(t,e,r){\"use strict\";var n=r(73220),i=r(3400).titleCase;t.exports=function(t,e){var r=t._name,a={};if(\"all\"===e.step)a[r+\".autorange\"]=!0;else{var o=function(t,e){var r,a=t.range,o=new Date(t.r2l(a[1])),s=e.step,l=n[\"utc\"+i(s)],u=e.count;switch(e.stepmode){case\"backward\":r=t.l2r(+l.offset(o,-u));break;case\"todate\":var c=l.offset(o,-u);r=t.l2r(+l.ceil(c))}return[r,a[1]]}(t,e);a[r+\".range[0]\"]=o[0],a[r+\".range[1]\"]=o[1]}return a}},41152:function(t,e,r){\"use strict\";t.exports={moduleType:\"component\",name:\"rangeselector\",schema:{subplots:{xaxis:{rangeselector:r(26680)}}},layoutAttributes:r(26680),handleDefaults:r(22148),draw:r(50216)}},11200:function(t,e,r){\"use 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o=e[r],s=o[a.name];s&&s.visible&&s.autorange&&(s._input.autorange=!0,s._input.range=s.range=i(t,o))}}},74636:function(t){\"use strict\";t.exports={name:\"rangeslider\",containerClassName:\"rangeslider-container\",bgClassName:\"rangeslider-bg\",rangePlotClassName:\"rangeslider-rangeplot\",maskMinClassName:\"rangeslider-mask-min\",maskMaxClassName:\"rangeslider-mask-max\",slideBoxClassName:\"rangeslider-slidebox\",grabberMinClassName:\"rangeslider-grabber-min\",grabAreaMinClassName:\"rangeslider-grabarea-min\",handleMinClassName:\"rangeslider-handle-min\",grabberMaxClassName:\"rangeslider-grabber-max\",grabAreaMaxClassName:\"rangeslider-grabarea-max\",handleMaxClassName:\"rangeslider-handle-max\",maskMinOppAxisClassName:\"rangeslider-mask-min-opp-axis\",maskMaxOppAxisClassName:\"rangeslider-mask-max-opp-axis\",maskColor:\"rgba(0,0,0,0.4)\",maskOppAxisColor:\"rgba(0,0,0,0.2)\",slideBoxFill:\"transparent\",slideBoxCursor:\"ew-resize\",grabAreaFill:\"transparent\",grabAreaCursor:\"col-resize\",grabAreaWidth:10,handleWidth:4,handleRadius:1,handleStrokeWidth:1,extraPad:15}},94040:function(t,e,r){\"use strict\";var n=r(3400),i=r(31780),a=r(79811),o=r(11200),s=r(10936);t.exports=function(t,e,r){var l=t[r],u=e[r];if(l.rangeslider||e._requestRangeslider[u._id]){n.isPlainObject(l.rangeslider)||(l.rangeslider={});var c,f,h=l.rangeslider,p=i.newContainer(u,\"rangeslider\");if(_(\"visible\")){_(\"bgcolor\",e.plot_bgcolor),_(\"bordercolor\"),_(\"borderwidth\"),_(\"thickness\"),_(\"autorange\",!u.isValidRange(h.range)),_(\"range\");var d=e._subplots;if(d)for(var v=d.cartesian.filter((function(t){return t.substr(0,t.indexOf(\"y\"))===a.name2id(r)})).map((function(t){return t.substr(t.indexOf(\"y\"),t.length)})),g=n.simpleMap(v,a.id2name),y=0;y<g.length;y++){var m=g[y];c=h[m]||{},f=i.newContainer(p,m,\"yaxis\");var x,b=e[m];c.range&&b.isValidRange(c.range)&&(x=\"fixed\"),\"match\"!==w(\"rangemode\",x)&&w(\"range\",b.range.slice())}p._input=h}}function _(t,e){return n.coerce(h,p,o,t,e)}function w(t,e){return n.coerce(c,f,s,t,e)}}},20060:function(t,e,r){\"use strict\";var n=r(33428),i=r(24040),a=r(7316),o=r(3400),s=o.strTranslate,l=r(43616),u=r(76308),c=r(81668),f=r(57952),h=r(79811),p=r(86476),d=r(93972),v=r(74636);function g(t){return\"number\"==typeof t.clientX?t.clientX:t.touches&&t.touches.length>0?t.touches[0].clientX:0}function y(t,e,r,n){var i=o.ensureSingle(t,\"rect\",v.bgClassName,(function(t){t.attr({x:0,y:0,\"shape-rendering\":\"crispEdges\"})})),a=n.borderwidth%2==0?n.borderwidth:n.borderwidth-1,c=-n._offsetShift,f=l.crispRound(e,n.borderwidth);i.attr({width:n._width+a,height:n._height+a,transform:s(c,c),\"stroke-width\":f}).call(u.stroke,n.bordercolor).call(u.fill,n.bgcolor)}function m(t,e,r,n){var i=e._fullLayout;o.ensureSingleById(i._topdefs,\"clipPath\",n._clipId,(function(t){t.append(\"rect\").attr({x:0,y:0})})).select(\"rect\").attr({width:n._width,height:n._height})}function x(t,e,r,i){var s,u=e.calcdata,c=t.selectAll(\"g.\"+v.rangePlotClassName).data(r._subplotsWith,o.identity);c.enter().append(\"g\").attr(\"class\",(function(t){return v.rangePlotClassName+\" \"+t})).call(l.setClipUrl,i._clipId,e),c.order(),c.exit().remove(),c.each((function(t,o){var l=n.select(this),c=0===o,p=h.getFromId(e,t,\"y\"),d=p._name,v=i[d],g={data:[],layout:{xaxis:{type:r.type,domain:[0,1],range:i.range.slice(),calendar:r.calendar},width:i._width,height:i._height,margin:{t:0,b:0,l:0,r:0}},_context:e._context};r.rangebreaks&&(g.layout.xaxis.rangebreaks=r.rangebreaks),g.layout[d]={type:p.type,domain:[0,1],range:\"match\"!==v.rangemode?v.range.slice():p.range.slice(),calendar:p.calendar},p.rangebreaks&&(g.layout[d].rangebreaks=p.rangebreaks),a.supplyDefaults(g);var y=g._fullLayout.xaxis,m=g._fullLayout[d];y.clearCalc(),y.setScale(),m.clearCalc(),m.setScale();var x={id:t,plotgroup:l,xaxis:y,yaxis:m,isRangePlot:!0};c?s=x:(x.mainplot=\"xy\",x.mainplotinfo=s),f.rangePlot(e,x,function(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n],a=i[0].trace;a.xaxis+a.yaxis===e&&r.push(i)}return r}(u,t))}))}function b(t,e,r,n,i){o.ensureSingle(t,\"rect\",v.maskMinClassName,(function(t){t.attr({x:0,y:0,\"shape-rendering\":\"crispEdges\"})})).attr(\"height\",n._height).call(u.fill,v.maskColor),o.ensureSingle(t,\"rect\",v.maskMaxClassName,(function(t){t.attr({y:0,\"shape-rendering\":\"crispEdges\"})})).attr(\"height\",n._height).call(u.fill,v.maskColor),\"match\"!==i.rangemode&&(o.ensureSingle(t,\"rect\",v.maskMinOppAxisClassName,(function(t){t.attr({y:0,\"shape-rendering\":\"crispEdges\"})})).attr(\"width\",n._width).call(u.fill,v.maskOppAxisColor),o.ensureSingle(t,\"rect\",v.maskMaxOppAxisClassName,(function(t){t.attr({y:0,\"shape-rendering\":\"crispEdges\"})})).attr(\"width\",n._width).style(\"border-top\",v.maskOppBorder).call(u.fill,v.maskOppAxisColor))}function _(t,e,r,n){e._context.staticPlot||o.ensureSingle(t,\"rect\",v.slideBoxClassName,(function(t){t.attr({y:0,cursor:v.slideBoxCursor,\"shape-rendering\":\"crispEdges\"})})).attr({height:n._height,fill:v.slideBoxFill})}function w(t,e,r,n){var i=o.ensureSingle(t,\"g\",v.grabberMinClassName),a=o.ensureSingle(t,\"g\",v.grabberMaxClassName),s={x:0,width:v.handleWidth,rx:v.handleRadius,fill:u.background,stroke:u.defaultLine,\"stroke-width\":v.handleStrokeWidth,\"shape-rendering\":\"crispEdges\"},l={y:Math.round(n._height/4),height:Math.round(n._height/2)};o.ensureSingle(i,\"rect\",v.handleMinClassName,(function(t){t.attr(s)})).attr(l),o.ensureSingle(a,\"rect\",v.handleMaxClassName,(function(t){t.attr(s)})).attr(l);var c={width:v.grabAreaWidth,x:0,y:0,fill:v.grabAreaFill,cursor:e._context.staticPlot?void 0:v.grabAreaCursor};o.ensureSingle(i,\"rect\",v.grabAreaMinClassName,(function(t){t.attr(c)})).attr(\"height\",n._height),o.ensureSingle(a,\"rect\",v.grabAreaMaxClassName,(function(t){t.attr(c)})).attr(\"height\",n._height)}t.exports=function(t){for(var e=t._fullLayout,r=e._rangeSliderData,a=0;a<r.length;a++){var l=r[a][v.name];l._clipId=l._id+\"-\"+e._uid}var u=e._infolayer.selectAll(\"g.\"+v.containerClassName).data(r,(function(t){return t._name}));u.exit().each((function(t){var r=t[v.name];e._topdefs.select(\"#\"+r._clipId).remove()})).remove(),0!==r.length&&(u.enter().append(\"g\").classed(v.containerClassName,!0).attr(\"pointer-events\",\"all\"),u.each((function(r){var a=n.select(this),l=r[v.name],u=e[h.id2name(r.anchor)],f=l[h.id2name(r.anchor)];if(l.range){var T,k=o.simpleMap(l.range,r.r2l),A=o.simpleMap(r.range,r.r2l);T=A[0]<A[1]?[Math.min(k[0],A[0]),Math.max(k[1],A[1])]:[Math.max(k[0],A[0]),Math.min(k[1],A[1])],l.range=l._input.range=o.simpleMap(T,r.l2r)}r.cleanRange(\"rangeslider.range\");var M=e._size,S=r.domain;l._width=M.w*(S[1]-S[0]);var E=Math.round(M.l+M.w*S[0]),L=Math.round(M.t+M.h*(1-r._counterDomainMin)+(\"bottom\"===r.side?r._depth:0)+l._offsetShift+v.extraPad);a.attr(\"transform\",s(E,L)),l._rl=o.simpleMap(l.range,r.r2l);var C=l._rl[0],P=l._rl[1],O=P-C;if(l.p2d=function(t){return t/l._width*O+C},l.d2p=function(t){return(t-C)/O*l._width},r.rangebreaks){var I=r.locateBreaks(C,P);if(I.length){var z,D,R=0;for(z=0;z<I.length;z++)R+=(D=I[z]).max-D.min;var F=l._width/(P-C-R),B=[-F*C];for(z=0;z<I.length;z++)D=I[z],B.push(B[B.length-1]-F*(D.max-D.min));for(l.d2p=function(t){for(var e=B[0],r=0;r<I.length;r++){var n=I[r];if(t>=n.max)e=B[r+1];else if(t<n.min)break}return e+F*t},z=0;z<I.length;z++)(D=I[z]).pmin=l.d2p(D.min),D.pmax=l.d2p(D.max);l.p2d=function(t){for(var e=B[0],r=0;r<I.length;r++){var n=I[r];if(t>=n.pmax)e=B[r+1];else if(t<n.pmin)break}return(t-e)/F}}}if(\"match\"!==f.rangemode){var N=u.r2l(f.range[0]),j=u.r2l(f.range[1])-N;l.d2pOppAxis=function(t){return(t-N)/j*l._height}}a.call(y,t,r,l).call(m,t,r,l).call(x,t,r,l).call(b,t,r,l,f).call(_,t,r,l).call(w,t,r,l),function(t,e,r,a){if(!e._context.staticPlot){var s=t.select(\"rect.\"+v.slideBoxClassName).node(),l=t.select(\"rect.\"+v.grabAreaMinClassName).node(),u=t.select(\"rect.\"+v.grabAreaMaxClassName).node();t.on(\"mousedown\",c),t.on(\"touchstart\",c)}function c(){var c=n.event,f=c.target,h=g(c),v=h-t.node().getBoundingClientRect().left,y=a.d2p(r._rl[0]),m=a.d2p(r._rl[1]),x=p.coverSlip();function b(t){var c,p,b,_=+g(t)-h;switch(f){case s:if(b=\"ew-resize\",y+_>r._length||m+_<0)return;c=y+_,p=m+_;break;case l:if(b=\"col-resize\",y+_>r._length)return;c=y+_,p=m;break;case u:if(b=\"col-resize\",m+_<0)return;c=y,p=m+_;break;default:b=\"ew-resize\",c=v,p=v+_}if(p<c){var w=p;p=c,c=w}a._pixelMin=c,a._pixelMax=p,d(n.select(x),b),function(t,e,r,n){function a(t){return r.l2r(o.constrain(t,n._rl[0],n._rl[1]))}var s=a(n.p2d(n._pixelMin)),l=a(n.p2d(n._pixelMax));window.requestAnimationFrame((function(){i.call(\"_guiRelayout\",e,r._name+\".range\",[s,l])}))}(0,e,r,a)}function _(){x.removeEventListener(\"mousemove\",b),x.removeEventListener(\"mouseup\",_),this.removeEventListener(\"touchmove\",b),this.removeEventListener(\"touchend\",_),o.removeElement(x)}this.addEventListener(\"touchmove\",b),this.addEventListener(\"touchend\",_),x.addEventListener(\"mousemove\",b),x.addEventListener(\"mouseup\",_)}}(a,t,r,l),function(t,e,r,n,i,a){var l=v.handleWidth/2;function u(t){return o.constrain(t,0,n._width)}function c(t){return o.constrain(t,0,n._height)}function f(t){return o.constrain(t,-l,n._width+l)}var h=u(n.d2p(r._rl[0])),p=u(n.d2p(r._rl[1]));if(t.select(\"rect.\"+v.slideBoxClassName).attr(\"x\",h).attr(\"width\",p-h),t.select(\"rect.\"+v.maskMinClassName).attr(\"width\",h),t.select(\"rect.\"+v.maskMaxClassName).attr(\"x\",p).attr(\"width\",n._width-p),\"match\"!==a.rangemode){var d=n._height-c(n.d2pOppAxis(i._rl[1])),g=n._height-c(n.d2pOppAxis(i._rl[0]));t.select(\"rect.\"+v.maskMinOppAxisClassName).attr(\"x\",h).attr(\"height\",d).attr(\"width\",p-h),t.select(\"rect.\"+v.maskMaxOppAxisClassName).attr(\"x\",h).attr(\"y\",g).attr(\"height\",n._height-g).attr(\"width\",p-h),t.select(\"rect.\"+v.slideBoxClassName).attr(\"y\",d).attr(\"height\",g-d)}var y=.5,m=Math.round(f(h-l))-y,x=Math.round(f(p-l))+y;t.select(\"g.\"+v.grabberMinClassName).attr(\"transform\",s(m,y)),t.select(\"g.\"+v.grabberMaxClassName).attr(\"transform\",s(x,y))}(a,0,r,l,u,f),\"bottom\"===r.side&&c.draw(t,r._id+\"title\",{propContainer:r,propName:r._name+\".title\",placeholder:e._dfltTitle.x,attributes:{x:r._offset+r._length/2,y:L+l._height+l._offsetShift+10+1.5*r.title.font.size,\"text-anchor\":\"middle\"}})})))}},97944:function(t,e,r){\"use strict\";var n=r(79811),i=r(72736),a=r(74636),o=r(84284).LINE_SPACING,s=a.name;function l(t){var e=t&&t[s];return e&&e.visible}e.isVisible=l,e.makeData=function(t){var e=n.list({_fullLayout:t},\"x\",!0),r=t.margin,i=[];if(!t._has(\"gl2d\"))for(var a=0;a<e.length;a++){var o=e[a];if(l(o)){i.push(o);var u=o[s];u._id=s+o._id,u._height=(t.height-r.b-r.t)*u.thickness,u._offsetShift=Math.floor(u.borderwidth/2)}}t._rangeSliderData=i},e.autoMarginOpts=function(t,e){var r=t._fullLayout,n=e[s],l=e._id.charAt(0),u=0,c=0;return\"bottom\"===e.side&&(u=e._depth,e.title.text!==r._dfltTitle[l]&&(c=1.5*e.title.font.size+10+n._offsetShift,c+=(e.title.text.match(i.BR_TAG_ALL)||[]).length*e.title.font.size*o)),{x:0,y:e._counterDomainMin,l:0,r:0,t:0,b:n._height+u+Math.max(r.margin.b,c),pad:a.extraPad+2*n._offsetShift}}},49692:function(t,e,r){\"use strict\";var n=r(3400),i=r(11200),a=r(10936),o=r(97944);t.exports={moduleType:\"component\",name:\"rangeslider\",schema:{subplots:{xaxis:{rangeslider:n.extendFlat({},i,{yaxis:a})}}},layoutAttributes:r(11200),handleDefaults:r(94040),calcAutorange:r(26652),draw:r(20060),isVisible:o.isVisible,makeData:o.makeData,autoMarginOpts:o.autoMarginOpts}},10936:function(t){\"use strict\";t.exports={_isSubplotObj:!0,rangemode:{valType:\"enumerated\",values:[\"auto\",\"fixed\",\"match\"],dflt:\"match\",editType:\"calc\"},range:{valType:\"info_array\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},editType:\"calc\"}},93956:function(t,e,r){\"use strict\";var n=r(13916),i=r(52904).line,a=r(98192).u,o=r(92880).extendFlat,s=r(67824).overrideAll,l=r(31780).templatedArray;r(36208),t.exports=s(l(\"selection\",{type:{valType:\"enumerated\",values:[\"rect\",\"path\"]},xref:o({},n.xref,{}),yref:o({},n.yref,{}),x0:{valType:\"any\"},x1:{valType:\"any\"},y0:{valType:\"any\"},y1:{valType:\"any\"},path:{valType:\"string\",editType:\"arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:.7,editType:\"arraydraw\"},line:{color:i.color,width:o({},i.width,{min:1,dflt:1}),dash:o({},a,{dflt:\"dot\"})}}),\"arraydraw\",\"from-root\")},83280:function(t){\"use strict\";t.exports={BENDPX:1.5,MINSELECT:12,SELECTDELAY:100,SELECTID:\"-select\"}},74224:function(t,e,r){\"use strict\";var n=r(3400),i=r(54460),a=r(51272),o=r(93956),s=r(65152);function l(t,e,r){function a(r,i){return n.coerce(t,e,o,r,i)}var l=a(\"path\"),u=\"path\"!==a(\"type\",l?\"path\":\"rect\");u&&delete e.path,a(\"opacity\"),a(\"line.color\"),a(\"line.width\"),a(\"line.dash\");for(var c=[\"x\",\"y\"],f=0;f<2;f++){var h,p,d,v=c[f],g={_fullLayout:r},y=i.coerceRef(t,e,g,v);if((h=i.getFromId(g,y))._selectionIndices.push(e._index),d=s.rangeToShapePosition(h),p=s.shapePositionToRange(h),u){var m=v+\"0\",x=v+\"1\",b=t[m],_=t[x];t[m]=p(t[m],!0),t[x]=p(t[x],!0),i.coercePosition(e,g,a,y,m),i.coercePosition(e,g,a,y,x);var w=e[m],T=e[x];void 0!==w&&void 0!==T&&(e[m]=d(w),e[x]=d(T),t[m]=b,t[x]=_)}}u&&n.noneOrAll(t,e,[\"x0\",\"x1\",\"y0\",\"y1\"])}t.exports=function(t,e){a(t,e,{name:\"selections\",handleItemDefaults:l});for(var r=e.selections,n=0;n<r.length;n++){var i=r[n];i&&void 0===i.path&&(void 0!==i.x0&&void 0!==i.x1&&void 0!==i.y0&&void 0!==i.y1||(e.selections[n]=null))}}},23640:function(t,e,r){\"use strict\";var n=r(9856).readPaths,i=r(55496),a=r(1936).clearOutlineControllers,o=r(76308),s=r(43616),l=r(31780).arrayEditor,u=r(65152),c=u.getPathString;function f(t){var e=t._fullLayout;for(var r in a(t),e._selectionLayer.selectAll(\"path\").remove(),e._plots){var n=e._plots[r].selectionLayer;n&&n.selectAll(\"path\").remove()}for(var i=0;i<e.selections.length;i++)p(t,i)}function h(t){return t._context.editSelection}function p(t,e){t._fullLayout._paperdiv.selectAll('.selectionlayer [data-index=\"'+e+'\"]').remove();var r=u.makeSelectionsOptionsAndPlotinfo(t,e),a=r.options,p=r.plotinfo;a._input&&function(r){var u=c(t,a),g={\"data-index\":e,\"fill-rule\":\"evenodd\",d:u},y=a.opacity,m=\"rgba(0,0,0,0)\",x=a.line.color||o.contrast(t._fullLayout.plot_bgcolor),b=a.line.width,_=a.line.dash;b||(b=5,_=\"solid\");var w=h(t)&&t._fullLayout._activeSelectionIndex===e;w&&(m=t._fullLayout.activeselection.fillcolor,y=t._fullLayout.activeselection.opacity);for(var T=[],k=1;k>=0;k--){var A=r.append(\"path\").attr(g).style(\"opacity\",k?.1:y).call(o.stroke,x).call(o.fill,m).call(s.dashLine,k?\"solid\":_,k?4+b:b);if(d(A,t,a),w){var M=l(t.layout,\"selections\",a);A.style({cursor:\"move\"});var S={element:A.node(),plotinfo:p,gd:t,editHelpers:M,isActiveSelection:!0},E=n(u,t);i(E,A,S)}else A.style(\"pointer-events\",k?\"all\":\"none\");T[k]=A}var L=T[0];T[1].node().addEventListener(\"click\",(function(){return function(t,e){if(h(t)){var r=+e.node().getAttribute(\"data-index\");if(r>=0){if(r===t._fullLayout._activeSelectionIndex)return void v(t);t._fullLayout._activeSelectionIndex=r,t._fullLayout._deactivateSelection=v,f(t)}}}(t,L)}))}(t._fullLayout._selectionLayer)}function d(t,e,r){var n=r.xref+r.yref;s.setClipUrl(t,\"clip\"+e._fullLayout._uid+n,e)}function v(t){h(t)&&t._fullLayout._activeSelectionIndex>=0&&(a(t),delete t._fullLayout._activeSelectionIndex,f(t))}t.exports={draw:f,drawOne:p,activateLastSelection:function(t){if(h(t)){var e=t._fullLayout.selections.length-1;t._fullLayout._activeSelectionIndex=e,t._fullLayout._deactivateSelection=v,f(t)}}}},34200:function(t,e,r){\"use strict\";var n=r(98192).u,i=r(92880).extendFlat;t.exports={newselection:{mode:{valType:\"enumerated\",values:[\"immediate\",\"gradual\"],dflt:\"immediate\",editType:\"none\"},line:{color:{valType:\"color\",editType:\"none\"},width:{valType:\"number\",min:1,dflt:1,editType:\"none\"},dash:i({},n,{dflt:\"dot\",editType:\"none\"}),editType:\"none\"},editType:\"none\"},activeselection:{fillcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"none\"},opacity:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"none\"},editType:\"none\"}}},81004:function(t){\"use strict\";t.exports=function(t,e,r){r(\"newselection.mode\"),r(\"newselection.line.width\")&&(r(\"newselection.line.color\"),r(\"newselection.line.dash\")),r(\"activeselection.fillcolor\"),r(\"activeselection.opacity\")}},5968:function(t,e,r){\"use strict\";var n=r(72760).selectMode,i=r(1936).clearOutline,a=r(9856),o=a.readPaths,s=a.writePaths,l=a.fixDatesForPaths;t.exports=function(t,e){if(t.length){var r=t[0][0];if(r){var a=r.getAttribute(\"d\"),u=e.gd,c=u._fullLayout.newselection,f=e.plotinfo,h=f.xaxis,p=f.yaxis,d=e.isActiveSelection,v=e.dragmode,g=(u.layout||{}).selections||[];if(!n(v)&&void 0!==d){var y=u._fullLayout._activeSelectionIndex;if(y<g.length)switch(u._fullLayout.selections[y].type){case\"rect\":v=\"select\";break;case\"path\":v=\"lasso\"}}var m,x=o(a,u,f,d),b={xref:h._id,yref:p._id,opacity:c.opacity,line:{color:c.line.color,width:c.line.width,dash:c.line.dash}};1===x.length&&(m=x[0]),m&&5===m.length&&\"select\"===v?(b.type=\"rect\",b.x0=m[0][1],b.y0=m[0][2],b.x1=m[2][1],b.y1=m[2][2]):(b.type=\"path\",h&&p&&l(x,h,p),b.path=s(x),m=null),i(u);for(var _=e.editHelpers,w=(_||{}).modifyItem,T=[],k=0;k<g.length;k++){var A=u._fullLayout.selections[k];if(A){if(T[k]=A._input,void 0!==d&&k===u._fullLayout._activeSelectionIndex){var M=b;switch(A.type){case\"rect\":w(\"x0\",M.x0),w(\"x1\",M.x1),w(\"y0\",M.y0),w(\"y1\",M.y1);break;case\"path\":w(\"path\",M.path)}}}else T[k]=A}return void 0===d?(T.push(b),T):_?_.getUpdateObj():{}}}}},5840:function(t,e,r){\"use strict\";var n=r(3400).strTranslate;function i(t,e){switch(t.type){case\"log\":return t.p2d(e);case\"date\":return t.p2r(e,0,t.calendar);default:return t.p2r(e)}}t.exports={p2r:i,r2p:function(t,e){switch(t.type){case\"log\":return t.d2p(e);case\"date\":return t.r2p(e,0,t.calendar);default:return t.r2p(e)}},axValue:function(t){var e=\"y\"===t._id.charAt(0)?1:0;return function(r){return i(t,r[e])}},getTransform:function(t){return n(t.xaxis._offset,t.yaxis._offset)}}},22676:function(t,e,r){\"use strict\";var n=r(23640),i=r(43156);t.exports={moduleType:\"component\",name:\"selections\",layoutAttributes:r(93956),supplyLayoutDefaults:r(74224),supplyDrawNewSelectionDefaults:r(81004),includeBasePlot:r(36632)(\"selections\"),draw:n.draw,drawOne:n.drawOne,reselect:i.reselect,prepSelect:i.prepSelect,clearOutline:i.clearOutline,clearSelectionsCache:i.clearSelectionsCache,selectOnClick:i.selectOnClick}},43156:function(t,e,r){\"use strict\";var n=r(14756),i=r(61456),a=r(24040),o=r(43616).dashStyle,s=r(76308),l=r(93024),u=r(10624).makeEventData,c=r(72760),f=c.freeMode,h=c.rectMode,p=c.drawMode,d=c.openMode,v=c.selectMode,g=r(65152),y=r(85448),m=r(55496),x=r(1936).clearOutline,b=r(9856),_=b.handleEllipse,w=b.readPaths,T=r(93940).newShapes,k=r(5968),A=r(23640).activateLastSelection,M=r(3400),S=M.sorterAsc,E=r(92065),L=r(91200),C=r(79811).getFromId,P=r(73696),O=r(39172).redrawReglTraces,I=r(83280),z=I.MINSELECT,D=E.filter,R=E.tester,F=r(5840),B=F.p2r,N=F.axValue,j=F.getTransform;function U(t){return void 0!==t.subplot}function V(t,e,r,n,i,a,o){var s,l,u,c,f,h,p,v,g,y=e._hoverdata,x=e._fullLayout.clickmode.indexOf(\"event\")>-1,b=[];if(function(t){return t&&Array.isArray(t)&&!0!==t[0].hoverOnBox}(y)){W(t,e,a);var _=function(t,e){var r,n,i=t[0],a=-1,o=[];for(n=0;n<e.length;n++)if(r=e[n],i.fullData._expandedIndex===r.cd[0].trace._expandedIndex){if(!0===i.hoverOnBox)break;void 0!==i.pointNumber?a=i.pointNumber:void 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0!==h?h:J(_)),u=function(t,e,r){return{pointNumber:t,searchInfo:e,subtract:!!r}}(_.pointNumber,_.searchInfo,p),c=G(a.selectionDefs.concat([u])),g=0;g<s.length;g++)if(f=tt(s[g]._module.selectPoints(s[g],c),s[g]),b.length)for(var w=0;w<f.length;w++)b.push(f[w]);else b=f;if($(e,s,v={points:b}),u&&a&&a.selectionDefs.push(u),o){var T=a.mergedPolygons,k=d(a.dragmode);m(et(T,k),o,a)}x&&ft(e,v)}}}function q(t){return\"pointNumber\"in t&&\"searchInfo\"in t}function H(t){return{xmin:0,xmax:0,ymin:0,ymax:0,pts:[],contains:function(e,r,n,i){var a=t.searchInfo.cd[0].trace._expandedIndex;return i.cd[0].trace._expandedIndex===a&&n===t.pointNumber},isRect:!1,degenerate:!1,subtract:!!t.subtract}}function G(t){if(t.length){for(var e=[],r=q(t[0])?0:t[0][0][0],n=r,i=q(t[0])?0:t[0][0][1],a=i,o=0;o<t.length;o++)if(q(t[o]))e.push(H(t[o]));else{var s=R(t[o]);s.subtract=!!t[o].subtract,e.push(s),r=Math.min(r,s.xmin),n=Math.max(n,s.xmax),i=Math.min(i,s.ymin),a=Math.max(a,s.ymax)}return{xmin:r,xmax:n,ymin:i,ymax:a,pts:[],contains:function(t,r,n,i){for(var a=!1,o=0;o<e.length;o++)e[o].contains(t,r,n,i)&&(a=!e[o].subtract);return a},isRect:!1,degenerate:!1}}}function W(t,e,r){var n=e._fullLayout,i=r.plotinfo,a=r.dragmode,o=n._lastSelectedSubplot&&n._lastSelectedSubplot===i.id,s=(t.shiftKey||t.altKey)&&!(p(a)&&d(a));o&&s&&i.selection&&i.selection.selectionDefs&&!r.selectionDefs?(r.selectionDefs=i.selection.selectionDefs,r.mergedPolygons=i.selection.mergedPolygons):s&&i.selection||Y(r),o||(x(e),n._lastSelectedSubplot=i.id)}function Y(t,e){var r=t.dragmode,n=t.plotinfo,i=t.gd;(function(t){return t._fullLayout._activeShapeIndex>=0})(i)&&i._fullLayout._deactivateShape(i),function(t){return t._fullLayout._activeSelectionIndex>=0}(i)&&i._fullLayout._deactivateSelection(i);var o=i._fullLayout._zoomlayer,s=p(r),l=v(r);if(s||l){var u,c,f=o.selectAll(\".select-outline-\"+n.id);f&&i._fullLayout._outlining&&(s&&(u=T(f,t)),u&&a.call(\"_guiRelayout\",i,{shapes:u}),l&&!U(t)&&(c=k(f,t)),c&&(i._fullLayout._noEmitSelectedAtStart=!0,a.call(\"_guiRelayout\",i,{selections:c}).then((function(){e&&A(i)}))),i._fullLayout._outlining=!1)}n.selection={},n.selection.selectionDefs=t.selectionDefs=[],n.selection.mergedPolygons=t.mergedPolygons=[]}function X(t){return t._id}function Z(t,e,r,n){if(!t.calcdata)return[];var i,a,o,s=[],l=e.map(X),u=r.map(X);for(o=0;o<t.calcdata.length;o++)if(!0===(a=(i=t.calcdata[o])[0].trace).visible&&a._module&&a._module.selectPoints)if(!U({subplot:n})||a.subplot!==n&&a.geo!==n)if(\"splom\"===a.type){if(a._xaxes[l[0]]&&a._yaxes[u[0]]){var c=K(a._module,i,e[0],r[0]);c.scene=t._fullLayout._splomScenes[a.uid],s.push(c)}}else if(\"sankey\"===a.type){var 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c=l[u],f=c.data,h=c.fullData,p=c.pointIndex,d=c.pointIndices;d?([].push.apply(f.selectedpoints,d),i._fullInput!==i&&[].push.apply(h.selectedpoints,d)):(f.selectedpoints.push(p),i._fullInput!==i&&h.selectedpoints.push(p))}}else for(n=0;n<e.length;n++)delete(i=e[n].cd[0].trace).selectedpoints,delete i._input.selectedpoints,i._fullInput!==i&&delete i._fullInput.selectedpoints;!function(t,e){for(var r=!1,n=0;n<e.length;n++){var i=e[n],o=i.cd;a.traceIs(o[0].trace,\"regl\")&&(r=!0);var s=i._module,l=s.styleOnSelect||s.style;l&&(l(t,o,o[0].node3),o[0].nodeRangePlot3&&l(t,o,o[0].nodeRangePlot3))}r&&(P(t),O(t))}(t,e)}function Q(t,e,r){for(var i=(r?n.difference:n.union)({regions:t},{regions:[e]}).regions.reverse(),a=0;a<i.length;a++){var o=i[a];o.subtract=st(o,i.slice(0,a))}return i}function tt(t,e){if(Array.isArray(t))for(var r=e.cd,n=e.cd[0].trace,i=0;i<t.length;i++)t[i]=u(t[i],n,r);return t}function et(t,e){for(var r=[],n=0;n<t.length;n++){r[n]=[];for(var 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v=\"pixel\"===h.xsizemode?h.xanchor:h.x0,g=\"pixel\"===h.xsizemode?h.xanchor:h.x1;(f=c(u=i.getFromId(t,h.xref),v,g,h.path,a.paramIsX))&&(h._extremes[u._id]=i.findExtremes(u,f,s(h)))}if(\"paper\"!==h.yref&&\"domain\"!==d){var y=\"pixel\"===h.ysizemode?h.yanchor:h.y0,m=\"pixel\"===h.ysizemode?h.yanchor:h.y1;(f=c(u=i.getFromId(t,h.yref),y,m,h.path,a.paramIsY))&&(h._extremes[u._id]=i.findExtremes(u,f,l(h)))}}}},85448:function(t){\"use strict\";t.exports={segmentRE:/[MLHVQCTSZ][^MLHVQCTSZ]*/g,paramRE:/[^\\s,]+/g,paramIsX:{M:{0:!0,drawn:0},L:{0:!0,drawn:0},H:{0:!0,drawn:0},V:{},Q:{0:!0,2:!0,drawn:2},C:{0:!0,2:!0,4:!0,drawn:4},T:{0:!0,drawn:0},S:{0:!0,2:!0,drawn:2},Z:{}},paramIsY:{M:{1:!0,drawn:1},L:{1:!0,drawn:1},H:{},V:{0:!0,drawn:0},Q:{1:!0,3:!0,drawn:3},C:{1:!0,3:!0,5:!0,drawn:5},T:{1:!0,drawn:1},S:{1:!0,3:!0,drawn:5},Z:{}},numParams:{M:2,L:2,H:1,V:1,Q:4,C:6,T:2,S:4,Z:0}}},43712:function(t,e,r){\"use strict\";var n=r(3400),i=r(54460),a=r(51272),o=r(46056),s=r(65152);function 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n=r(3400),i=r(54460),a=r(72736),o=r(43616),s=r(9856).readPaths,l=r(65152),u=l.getPathString,c=r(97728),f=r(84284).FROM_TL;t.exports=function(t,e,r,h){if(h.selectAll(\".shape-label\").remove(),r.label.text||r.label.texttemplate){var p;if(r.label.texttemplate){var d={};if(\"path\"!==r.type){var v=i.getFromId(t,r.xref),g=i.getFromId(t,r.yref);for(var y in c){var m=c[y](r,v,g);void 0!==m&&(d[y]=m)}}p=n.texttemplateStringForShapes(r.label.texttemplate,{},t._fullLayout._d3locale,d)}else p=r.label.text;var x,b,_,w,T={\"data-index\":e},k=r.label.font,A=h.append(\"g\").attr(T).classed(\"shape-label\",!0).append(\"text\").attr({\"data-notex\":1}).classed(\"shape-label-text\",!0).text(p);if(r.path){var M=u(t,r),S=s(M,t);x=1/0,_=1/0,b=-1/0,w=-1/0;for(var E=0;E<S.length;E++)for(var L=0;L<S[E].length;L++)for(var C=S[E][L],P=1;P<C.length;P+=2){var O=C[P],I=C[P+1];x=Math.min(x,O),b=Math.max(b,O),_=Math.min(_,I),w=Math.max(w,I)}}else{var 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n=r(3400).strTranslate,i=r(86476),a=r(72760),o=a.drawMode,s=a.selectMode,l=r(24040),u=r(76308),c=r(7e3),f=c.i000,h=c.i090,p=c.i180,d=c.i270,v=r(1936).clearOutlineControllers,g=r(9856),y=g.pointsOnRectangle,m=g.pointsOnEllipse,x=g.writePaths,b=r(93940).newShapes,_=r(93940).createShapeObj,w=r(5968),T=r(60728);function k(t,e){var r,n,i,a=t[e][1],o=t[e][2],s=t.length;return n=t[r=(e+1)%s][1],i=t[r][2],n===a&&i===o&&(n=t[r=(e+2)%s][1],i=t[r][2]),[r,n,i]}t.exports=function t(e,r,a,c){c||(c=0);var g=a.gd;function A(){t(e,r,a,c++),(m(e[0])||a.hasText)&&M({redrawing:!0})}function M(t){var e={};void 0!==a.isActiveShape&&(a.isActiveShape=!1,e=b(r,a)),void 0!==a.isActiveSelection&&(a.isActiveSelection=!1,e=w(r,a),g._fullLayout._reselect=!0),Object.keys(e).length&&l.call((t||{}).redrawing?\"relayout\":\"_guiRelayout\",g,e)}var 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n,i=t[0][0],o=e.gd,p=i.getAttribute(\"d\"),g=o._fullLayout.newshape,y=e.plotinfo,w=e.isActiveShape,T=y.xaxis,k=y.yaxis,A=!!y.domain||!y.xaxis,M=!!y.domain||!y.yaxis,S=a(r),E=m(p,o,y,w),L={editable:!0,visible:g.visible,name:g.name,showlegend:g.showlegend,legend:g.legend,legendwidth:g.legendwidth,legendgroup:g.legendgroup,legendgrouptitle:{text:g.legendgrouptitle.text,font:g.legendgrouptitle.font},legendrank:g.legendrank,label:g.label,xref:A?\"paper\":T._id,yref:M?\"paper\":k._id,layer:g.layer,opacity:g.opacity,line:{color:g.line.color,width:g.line.width,dash:g.line.dash}};if(S||(L.fillcolor=g.fillcolor,L.fillrule=g.fillrule),1===E.length&&(n=E[0]),n&&5===n.length&&\"drawrect\"===r)L.type=\"rect\",L.x0=n[0][1],L.y0=n[0][2],L.x1=n[2][1],L.y1=n[2][2];else if(n&&\"drawline\"===r)L.type=\"line\",L.x0=n[0][1],L.y0=n[0][2],L.x1=n[1][1],L.y1=n[1][2];else if(n&&\"drawcircle\"===r){L.type=\"circle\";var C=n[s][1],P=n[l][1],O=n[u][1],I=n[c][1],z=n[s][2],D=n[l][2],R=n[u][2],F=n[c][2],B=y.xaxis&&(\"date\"===y.xaxis.type||\"log\"===y.xaxis.type),N=y.yaxis&&(\"date\"===y.yaxis.type||\"log\"===y.yaxis.type);B&&(C=v(y.xaxis,C),P=v(y.xaxis,P),O=v(y.xaxis,O),I=v(y.xaxis,I)),N&&(z=v(y.yaxis,z),D=v(y.yaxis,D),R=v(y.yaxis,R),F=v(y.yaxis,F));var j=(P+I)/2,U=(z+R)/2,V=b({x0:j,y0:U,x1:j+(I-P+O-C)/2*f,y1:U+(F-D+R-z)/2*h});B&&(V.x0=d(y.xaxis,V.x0),V.x1=d(y.xaxis,V.x1)),N&&(V.y0=d(y.yaxis,V.y0),V.y1=d(y.yaxis,V.y1)),L.x0=V.x0,L.y0=V.y0,L.x1=V.x1,L.y1=V.y1}else L.type=\"path\",T&&k&&_(E,T,k),L.path=x(E),n=null;return L}t.exports={newShapes:function(t,e){if(t.length&&t[0][0]){var r=e.gd,n=e.isActiveShape,a=e.dragmode,o=(r.layout||{}).shapes||[];if(!i(a)&&void 0!==n){var s=r._fullLayout._activeShapeIndex;if(s<o.length)switch(r._fullLayout.shapes[s].type){case\"rect\":a=\"drawrect\";break;case\"circle\":a=\"drawcircle\";break;case\"line\":a=\"drawline\";break;case\"path\":var l=o[s].path||\"\";a=\"Z\"===l[l.length-1]?\"drawclosedpath\":\"drawopenpath\"}}var u=w(t,e,a);g(r);for(var c=e.editHelpers,f=(c||{}).modifyItem,h=[],p=0;p<o.length;p++){var d=r._fullLayout.shapes[p];if(h[p]=d._input,void 0!==n&&p===r._fullLayout._activeShapeIndex){var v=u;switch(d.type){case\"line\":case\"rect\":case\"circle\":f(\"x0\",v.x0),f(\"x1\",v.x1),f(\"y0\",v.y0),f(\"y1\",v.y1);break;case\"path\":f(\"path\",v.path)}}}return void 0===n?(h.push(u),h):c?c.getUpdateObj():{}}},createShapeObj:w}},1936:function(t){\"use strict\";t.exports={clearOutlineControllers:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".outline-controllers\").remove()},clearOutline:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".select-outline\").remove(),t._fullLayout._outlining=!1}}},65152:function(t,e,r){\"use strict\";var n=r(85448),i=r(3400),a=r(54460);e.rangeToShapePosition=function(t){return\"log\"===t.type?t.r2d:function(t){return 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n?1-e:e};else{var s=e.rangeToShapePosition(r);a=function(t){return s(r.p2r(t-r._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},e.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},e.makeShapesOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.shapes[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return n?n._hadPlotinfo=!0:(n={},r.xref&&\"paper\"!==r.xref&&(n.xaxis=t._fullLayout[r.xref+\"axis\"]),r.yref&&\"paper\"!==r.yref&&(n.yaxis=t._fullLayout[r.yref+\"axis\"])),n.xsizemode=r.xsizemode,n.ysizemode=r.ysizemode,n.xanchor=r.xanchor,n.yanchor=r.yanchor,{options:r,plotinfo:n}},e.makeSelectionsOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.selections[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return n?n._hadPlotinfo=!0:(n={},r.xref&&(n.xaxis=t._fullLayout[r.xref+\"axis\"]),r.yref&&(n.yaxis=t._fullLayout[r.yref+\"axis\"])),{options:r,plotinfo:n}},e.getPathString=function(t,r){var o,s,l,u,c,f,h,p,d=r.type,v=a.getRefType(r.xref),g=a.getRefType(r.yref),y=a.getFromId(t,r.xref),m=a.getFromId(t,r.yref),x=t._fullLayout._size;if(y?\"domain\"===v?s=function(t){return y._offset+y._length*t}:(o=e.shapePositionToRange(y),s=function(t){return y._offset+y.r2p(o(t,!0))}):s=function(t){return x.l+x.w*t},m?\"domain\"===g?u=function(t){return m._offset+m._length*(1-t)}:(l=e.shapePositionToRange(m),u=function(t){return m._offset+m.r2p(l(t,!0))}):u=function(t){return x.t+x.h*(1-t)},\"path\"===d)return y&&\"date\"===y.type&&(s=e.decodeDate(s)),m&&\"date\"===m.type&&(u=e.decodeDate(u)),function(t,e,r){var a=t.path,o=t.xsizemode,s=t.ysizemode,l=t.xanchor,u=t.yanchor;return a.replace(n.segmentRE,(function(t){var a=0,c=t.charAt(0),f=n.paramIsX[c],h=n.paramIsY[c],p=n.numParams[c],d=t.substr(1).replace(n.paramRE,(function(t){return f[a]?t=\"pixel\"===o?e(l)+Number(t):e(t):h[a]&&(t=\"pixel\"===s?r(u)-Number(t):r(t)),++a>p&&(t=\"X\"),t}));return a>p&&(d=d.replace(/[\\s,]*X.*/,\"\"),i.log(\"Ignoring extra params in segment \"+t)),c+d}))}(r,s,u);if(\"pixel\"===r.xsizemode){var b=s(r.xanchor);c=b+r.x0,f=b+r.x1}else c=s(r.x0),f=s(r.x1);if(\"pixel\"===r.ysizemode){var _=u(r.yanchor);h=_-r.y0,p=_-r.y1}else h=u(r.y0),p=u(r.y1);if(\"line\"===d)return\"M\"+c+\",\"+h+\"L\"+f+\",\"+p;if(\"rect\"===d)return\"M\"+c+\",\"+h+\"H\"+f+\"V\"+p+\"H\"+c+\"Z\";var w=(c+f)/2,T=(h+p)/2,k=Math.abs(w-c),A=Math.abs(T-h),M=\"A\"+k+\",\"+A,S=w+k+\",\"+T;return\"M\"+S+M+\" 0 1,1 \"+w+\",\"+(T-A)+M+\" 0 0,1 \"+S+\"Z\"}},41592:function(t,e,r){\"use strict\";var n=r(4016);t.exports={moduleType:\"component\",name:\"shapes\",layoutAttributes:r(46056),supplyLayoutDefaults:r(43712),supplyDrawNewShapeDefaults:r(65144),includeBasePlot:r(36632)(\"shapes\"),calcAutorange:r(96084),draw:n.draw,drawOne:n.drawOne}},97728:function(t){\"use strict\";function e(t,e){return e?e.d2l(t):t}function r(t,e){return e?e.l2d(t):t}function n(t,r){return e(t.x1,r)-e(t.x0,r)}function i(t,r,n){return e(t.y1,n)-e(t.y0,n)}t.exports={x0:function(t){return t.x0},x1:function(t){return t.x1},y0:function(t){return t.y0},y1:function(t){return t.y1},slope:function(t,e,r){return\"line\"!==t.type?void 0:i(t,0,r)/n(t,e)},dx:n,dy:i,width:function(t,e){return Math.abs(n(t,e))},height:function(t,e,r){return Math.abs(i(t,0,r))},length:function(t,e,r){return\"line\"!==t.type?void 0:Math.sqrt(Math.pow(n(t,e),2)+Math.pow(i(t,0,r),2))},xcenter:function(t,n){return r((e(t.x1,n)+e(t.x0,n))/2,n)},ycenter:function(t,n,i){return r((e(t.y1,i)+e(t.y0,i))/2,i)}}},89861:function(t,e,r){\"use 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n=r(25376),i=r(66741),a=r(92880).extendDeepAll,o=r(67824).overrideAll,s=r(85656),l=r(31780).templatedArray,u=r(60876),c=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});t.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:c,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:u.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:u.railBgColor},bordercolor:{valType:\"color\",dflt:u.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:u.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:u.tickLength},tickcolor:{valType:\"color\",dflt:u.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:u.minorTickLength}}),\"arraydraw\",\"from-root\")},60876:function(t){\"use strict\";t.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},8132:function(t,e,r){\"use 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u=n.select(this);u.call(m,o,s,t).call(M,o,b),u.on(\"click\",(function(){n.event.defaultPrevented||(s.execute&&(s.args2&&o.active===l?(v(t,o,0,e,r,a,-1),i.executeAPICommand(t,s.method,s.args2)):(v(t,o,0,e,r,a,l),i.executeAPICommand(t,s.method,s.args))),t.emit(\"plotly_buttonclicked\",{menu:o,button:s,active:o.active}))})),u.on(\"mouseover\",(function(){u.call(w)})),u.on(\"mouseout\",(function(){u.call(T,o),c.call(_,o)}))})),c.call(_,o),x?(k.w=Math.max(y.openWidth,y.headerWidth),k.h=b.y-k.t):(k.w=b.x-k.l,k.h=Math.max(y.openHeight,y.headerHeight)),k.direction=o.direction,a&&(c.size()?function(t,e,r,n,i,a){var o,s,l,u=i.direction,c=\"up\"===u||\"down\"===u,h=i._dims,p=i.active;if(c)for(s=0,l=0;l<p;l++)s+=h.heights[l]+f.gapButton;else for(o=0,l=0;l<p;l++)o+=h.widths[l]+f.gapButton;n.enable(a,o,s),n.hbar&&n.hbar.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\"),n.vbar&&n.vbar.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\")}(0,0,0,a,o,k):function(t){var e=!!t.hbar,r=!!t.vbar;e&&t.hbar.transition().attr(\"opacity\",\"0\").each(\"end\",(function(){e=!1,r||t.disable()})),r&&t.vbar.transition().attr(\"opacity\",\"0\").each(\"end\",(function(){r=!1,e||t.disable()}))}(a))}function m(t,e,r,n){t.call(x,e).call(b,e,r,n)}function x(t,e){s.ensureSingle(t,\"rect\",f.itemRectClassName,(function(t){t.attr({rx:f.rx,ry:f.ry,\"shape-rendering\":\"crispEdges\"})})).call(a.stroke,e.bordercolor).call(a.fill,e.bgcolor).style(\"stroke-width\",e.borderwidth+\"px\")}function b(t,e,r,n){var i=s.ensureSingle(t,\"text\",f.itemTextClassName,(function(t){t.attr({\"text-anchor\":\"start\",\"data-notex\":1})})),a=r.label,u=n._fullLayout._meta;u&&(a=s.templateString(a,u)),i.call(o.font,e.font).text(a).call(l.convertToTspans,n)}function _(t,e){var r=e.active;t.each((function(t,i){var o=n.select(this);i===r&&e.showactive&&o.select(\"rect.\"+f.itemRectClassName).call(a.fill,f.activeColor)}))}function w(t){t.select(\"rect.\"+f.itemRectClassName).call(a.fill,f.hoverColor)}function T(t,e){t.select(\"rect.\"+f.itemRectClassName).call(a.fill,e.bgcolor)}function k(t,e){var r=e._dims={width1:0,height1:0,heights:[],widths:[],totalWidth:0,totalHeight:0,openWidth:0,openHeight:0,lx:0,ly:0},a=o.tester.selectAll(\"g.\"+f.dropdownButtonClassName).data(s.filterVisible(e.buttons));a.enter().append(\"g\").classed(f.dropdownButtonClassName,!0);var u=-1!==[\"up\",\"down\"].indexOf(e.direction);a.each((function(i,a){var s=n.select(this);s.call(m,e,i,t);var h=s.select(\".\"+f.itemTextClassName),p=h.node()&&o.bBox(h.node()).width,d=Math.max(p+f.textPadX,f.minWidth),v=e.font.size*c,g=l.lineCount(h),y=Math.max(v*g,f.minHeight)+f.textOffsetY;y=Math.ceil(y),d=Math.ceil(d),r.widths[a]=d,r.heights[a]=y,r.height1=Math.max(r.height1,y),r.width1=Math.max(r.width1,d),u?(r.totalWidth=Math.max(r.totalWidth,d),r.openWidth=r.totalWidth,r.totalHeight+=y+f.gapButton,r.openHeight+=y+f.gapButton):(r.totalWidth+=d+f.gapButton,r.openWidth+=d+f.gapButton,r.totalHeight=Math.max(r.totalHeight,y),r.openHeight=r.totalHeight)})),u?r.totalHeight-=f.gapButton:r.totalWidth-=f.gapButton,r.headerWidth=r.width1+f.arrowPadX,r.headerHeight=r.height1,\"dropdown\"===e.type&&(u?(r.width1+=f.arrowPadX,r.totalHeight=r.height1):r.totalWidth=r.width1,r.totalWidth+=f.arrowPadX),a.remove();var h=r.totalWidth+e.pad.l+e.pad.r,p=r.totalHeight+e.pad.t+e.pad.b,d=t._fullLayout._size;r.lx=d.l+d.w*e.x,r.ly=d.t+d.h*(1-e.y);var 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s(t,e,r){this.gd=t,this.container=e,this.id=r,this.position=null,this.translateX=null,this.translateY=null,this.hbar=null,this.vbar=null,this.bg=this.container.selectAll(\"rect.scrollbox-bg\").data([0]),this.bg.exit().on(\".drag\",null).on(\"wheel\",null).remove(),this.bg.enter().append(\"rect\").classed(\"scrollbox-bg\",!0).style(\"pointer-events\",\"all\").attr({opacity:0,x:0,y:0,width:0,height:0})}s.barWidth=2,s.barLength=20,s.barRadius=2,s.barPad=1,s.barColor=\"#808BA4\",s.prototype.enable=function(t,e,r){var o=this.gd._fullLayout,l=o.width,u=o.height;this.position=t;var c,f,h,p,d=this.position.l,v=this.position.w,g=this.position.t,y=this.position.h,m=this.position.direction,x=\"down\"===m,b=\"left\"===m,_=\"up\"===m,w=v,T=y;x||b||\"right\"===m||_||(this.position.direction=\"down\",x=!0),x||_?(f=(c=d)+w,x?(h=g,T=(p=Math.min(h+T,u))-h):T=(p=g+T)-(h=Math.max(p-T,0))):(p=(h=g)+T,b?w=(f=d+w)-(c=Math.max(f-w,0)):(c=d,w=(f=Math.min(c+w,l))-c)),this._box={l:c,t:h,w:w,h:T};var k=v>w,A=s.barLength+2*s.barPad,M=s.barWidth+2*s.barPad,S=d,E=g+y;E+M>u&&(E=u-M);var L=this.container.selectAll(\"rect.scrollbar-horizontal\").data(k?[0]:[]);L.exit().on(\".drag\",null).remove(),L.enter().append(\"rect\").classed(\"scrollbar-horizontal\",!0).call(i.fill,s.barColor),k?(this.hbar=L.attr({rx:s.barRadius,ry:s.barRadius,x:S,y:E,width:A,height:M}),this._hbarXMin=S+A/2,this._hbarTranslateMax=w-A):(delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax);var C=y>T,P=s.barWidth+2*s.barPad,O=s.barLength+2*s.barPad,I=d+v,z=g;I+P>l&&(I=l-P);var D=this.container.selectAll(\"rect.scrollbar-vertical\").data(C?[0]:[]);D.exit().on(\".drag\",null).remove(),D.enter().append(\"rect\").classed(\"scrollbar-vertical\",!0).call(i.fill,s.barColor),C?(this.vbar=D.attr({rx:s.barRadius,ry:s.barRadius,x:I,y:z,width:P,height:O}),this._vbarYMin=z+O/2,this._vbarTranslateMax=T-O):(delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax);var R=this.id,F=c-.5,B=C?f+P+.5:f+.5,N=h-.5,j=k?p+M+.5:p+.5,U=o._topdefs.selectAll(\"#\"+R).data(k||C?[0]:[]);if(U.exit().remove(),U.enter().append(\"clipPath\").attr(\"id\",R).append(\"rect\"),k||C?(this._clipRect=U.select(\"rect\").attr({x:Math.floor(F),y:Math.floor(N),width:Math.ceil(B)-Math.floor(F),height:Math.ceil(j)-Math.floor(N)}),this.container.call(a.setClipUrl,R,this.gd),this.bg.attr({x:d,y:g,width:v,height:y})):(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(a.setClipUrl,null),delete this._clipRect),k||C){var V=n.behavior.drag().on(\"dragstart\",(function(){n.event.sourceEvent.preventDefault()})).on(\"drag\",this._onBoxDrag.bind(this));this.container.on(\"wheel\",null).on(\"wheel\",this._onBoxWheel.bind(this)).on(\".drag\",null).call(V);var q=n.behavior.drag().on(\"dragstart\",(function(){n.event.sourceEvent.preventDefault(),n.event.sourceEvent.stopPropagation()})).on(\"drag\",this._onBarDrag.bind(this));k&&this.hbar.on(\".drag\",null).call(q),C&&this.vbar.on(\".drag\",null).call(q)}this.setTranslate(e,r)},s.prototype.disable=function(){(this.hbar||this.vbar)&&(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(a.setClipUrl,null),delete this._clipRect),this.hbar&&(this.hbar.on(\".drag\",null),this.hbar.remove(),delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax),this.vbar&&(this.vbar.on(\".drag\",null),this.vbar.remove(),delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax)},s.prototype._onBoxDrag=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t-=n.event.dx),this.vbar&&(e-=n.event.dy),this.setTranslate(t,e)},s.prototype._onBoxWheel=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t+=n.event.deltaY),this.vbar&&(e+=n.event.deltaY),this.setTranslate(t,e)},s.prototype._onBarDrag=function(){var t=this.translateX,e=this.translateY;if(this.hbar){var r=t+this._hbarXMin,i=r+this._hbarTranslateMax;t=(o.constrain(n.event.x,r,i)-r)/(i-r)*(this.position.w-this._box.w)}if(this.vbar){var a=e+this._vbarYMin,s=a+this._vbarTranslateMax;e=(o.constrain(n.event.y,a,s)-a)/(s-a)*(this.position.h-this._box.h)}this.setTranslate(t,e)},s.prototype.setTranslate=function(t,e){var r=this.position.w-this._box.w,n=this.position.h-this._box.h;if(t=o.constrain(t||0,0,r),e=o.constrain(e||0,0,n),this.translateX=t,this.translateY=e,this.container.call(a.setTranslate,this._box.l-this.position.l-t,this._box.t-this.position.t-e),this._clipRect&&this._clipRect.attr({x:Math.floor(this.position.l+t-.5),y:Math.floor(this.position.t+e-.5)}),this.hbar){var i=t/r;this.hbar.call(a.setTranslate,t+i*this._hbarTranslateMax,e)}if(this.vbar){var s=e/n;this.vbar.call(a.setTranslate,t,e+s*this._vbarTranslateMax)}}},84284:function(t){\"use strict\";t.exports={FROM_BL:{left:0,center:.5,right:1,bottom:0,middle:.5,top:1},FROM_TL:{left:0,center:.5,right:1,bottom:1,middle:.5,top:0},FROM_BR:{left:1,center:.5,right:0,bottom:0,middle:.5,top:1},LINE_SPACING:1.3,CAP_SHIFT:.7,MID_SHIFT:.35,OPPOSITE_SIDE:{left:\"right\",right:\"left\",top:\"bottom\",bottom:\"top\"}}},36208:function(t){\"use strict\";t.exports={axisRefDescription:function(t,e,r){return[\"If set to a\",t,\"axis id (e.g. *\"+t+\"* or\",\"*\"+t+\"2*), the `\"+t+\"` position refers to a\",t,\"coordinate. 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L=(v+.5)/84;e.maskBreaks(i*(1-L)+L*p)!==O&&d++}(h*=d/84)||(t[n].drop=!0),s&&c>A&&(h=c)}(h>0||0===n)&&(t[n].periodX=i+h/2)}}(C,t,t._definedDelta),t.rangebreaks){var it=\"y\"===t._id.charAt(0),st=1;\"auto\"===t.tickmode&&(st=t.tickfont?t.tickfont.size:12);var lt=NaN;for(r=C.length-1;r>-1;r--)if(C[r].drop)C.splice(r,1);else{C[r].value=Dt(C[r].value,t);var ut=t.c2p(C[r].value);(it?lt>ut-st:lt<ut+st)?C.splice(f?r+1:r,1):lt=ut}}zt(t)&&360===Math.abs(c[1]-c[0])&&C.pop(),t._tmax=(C[C.length-1]||{}).value,t._prevDateHead=\"\",t._inCalcTicks=!0;var ct,ft,ht=function(e){e.text=\"\",t._prevDateHead=n};for(C=C.concat(P),r=0;r<C.length;r++){var pt=C[r].minor,dt=C[r].value;pt?L.push({x:dt,minor:!0}):(n=t._prevDateHead,ct=H.tickText(t,dt,!1,C[r].simpleLabel),void 0!==(ft=C[r].periodX)&&(ct.periodX=ft,(ft>p||ft<h)&&(ft>p&&(ct.periodX=p),ft<h&&(ct.periodX=h),ht(ct))),C[r].skipLabel&&ht(ct),v.push(ct))}return v=v.concat(L),t._inCalcTicks=!1,u&&v.length&&(v[0].noTick=!0),v};var st=[2,5,10],lt=[1,2,3,6,12],ut=[1,2,5,10,15,30],ct=[1,2,3,7,14],ft=[-.046,0,.301,.477,.602,.699,.778,.845,.903,.954,1],ht=[-.301,0,.301,.699,1],pt=[15,30,45,90,180];function dt(t,e,r){return e*s.roundUp(t/e,r)}function vt(t){var e=t.dtick;if(t._tickexponent=0,i(e)||\"string\"==typeof e||(e=1),\"category\"!==t.type&&\"multicategory\"!==t.type||(t._tickround=null),\"date\"===t.type){var r=t.r2l(t.tick0),n=t.l2r(r).replace(/(^-|i)/g,\"\"),a=n.length;if(\"M\"===String(e).charAt(0))a>10||\"01-01\"!==n.substr(5)?t._tickround=\"d\":t._tickround=+e.substr(1)%12==0?\"y\":\"m\";else if(e>=M&&a<=10||e>=15*M)t._tickround=\"d\";else if(e>=L&&a<=16||e>=E)t._tickround=\"M\";else if(e>=C&&a<=19||e>=L)t._tickround=\"S\";else{var o=t.l2r(r+e).replace(/^-/,\"\").length;t._tickround=Math.max(a,o)-20,t._tickround<0&&(t._tickround=4)}}else if(i(e)||\"L\"===e.charAt(0)){var s=t.range.map(t.r2d||Number);i(e)||(e=Number(e.substr(1))),t._tickround=2-Math.floor(Math.log(e)/Math.LN10+.01);var 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r=!1,n=e._id,i=t._fullLayout._axisConstraintGroups,a=0;a<i.length;a++)if(i[a][n]){r=!0;break}r&&\"domain\"===e.constrain||(e._input.domain=e.domain=e._inputDomain,delete e._inputDomain)}}},51184:function(t,e,r){\"use strict\";var n=r(33428),i=r(3400),a=i.numberFormat,o=r(49760),s=r(89184),l=r(24040),u=i.strTranslate,c=r(72736),f=r(76308),h=r(43616),p=r(93024),d=r(54460),v=r(93972),g=r(86476),y=r(72760),m=y.selectingOrDrawing,x=y.freeMode,b=r(84284).FROM_TL,_=r(73696),w=r(39172).redrawReglTraces,T=r(7316),k=r(79811).getFromId,A=r(22676).prepSelect,M=r(22676).clearOutline,S=r(22676).selectOnClick,E=r(21160),L=r(33816),C=L.MINDRAG,P=L.MINZOOM,O=!0;function I(t,e,r,n){var a=i.ensureSingle(t.draglayer,e,r,(function(e){e.classed(\"drag\",!0).style({fill:\"transparent\",\"stroke-width\":0}).attr(\"data-subplot\",t.id)}));return a.call(v,n),a.node()}function z(t,e,r,i,a,o,s){var l=I(t,\"rect\",e,r);return n.select(l).call(h.setRect,i,a,o,s),l}function D(t,e){for(var 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t.append(\"path\").attr(\"class\",\"zoombox\").style({fill:e>.2?\"rgba(0,0,0,0)\":\"rgba(255,255,255,0)\",\"stroke-width\":0}).attr(\"transform\",u(r,n)).attr(\"d\",i+\"Z\")}function j(t,e,r){return t.append(\"path\").attr(\"class\",\"zoombox-corners\").style({fill:f.background,stroke:f.defaultLine,\"stroke-width\":1,opacity:0}).attr(\"transform\",u(e,r)).attr(\"d\",\"M0,0Z\")}function U(t,e,r,n,i,a){t.attr(\"d\",n+\"M\"+r.l+\",\"+r.t+\"v\"+r.h+\"h\"+r.w+\"v-\"+r.h+\"h-\"+r.w+\"Z\"),V(t,e,i,a)}function V(t,e,r,n){r||(t.transition().style(\"fill\",n>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),e.transition().style(\"opacity\",1).duration(200))}function q(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}function H(t){O&&t.data&&t._context.showTips&&(i.notifier(i._(t,\"Double-click to zoom back out\"),\"long\"),O=!1)}function G(t){var 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0!==t.onwheel?\"wheel\":\"mousewheel\";t._onwheel&&t.removeEventListener(r,t._onwheel),t._onwheel=e,t.addEventListener(r,e,{passive:!1})}else void 0!==t.onwheel?t.onwheel=e:void 0!==t.onmousewheel?t.onmousewheel=e:t.isAddedWheelEvent||(t.isAddedWheelEvent=!0,t.addEventListener(\"wheel\",e,{passive:!1}))}function X(t){var e=[];for(var r in t)e.push(t[r]);return e}t.exports={makeDragBox:function(t,e,r,s,u,f,v,y){var O,I,V,Z,K,J,$,Q,tt,et,rt,nt,it,at,ot,st,lt,ut,ct,ft,ht,pt,dt,vt=t._fullLayout._zoomlayer,gt=v+y===\"nsew\",yt=1===(v+y).length;function mt(){if(O=e.xaxis,I=e.yaxis,tt=O._length,et=I._length,$=O._offset,Q=I._offset,(V={})[O._id]=O,(Z={})[I._id]=I,v&&y)for(var r=e.overlays,n=0;n<r.length;n++){var i=r[n].xaxis;V[i._id]=i;var a=r[n].yaxis;Z[a._id]=a}K=X(V),J=X(Z),it=D(K,y),at=D(J,v),ot=!at&&!it,nt=W(t,t._fullLayout._axisMatchGroups,V,Z);var o=(rt=W(t,t._fullLayout._axisConstraintGroups,V,Z,nt)).isSubplotConstrained||nt.isSubplotConstrained;st=y||o,lt=v||o;var s=t._fullLayout;ut=s._has(\"scattergl\"),ct=s._has(\"splom\"),ft=s._has(\"svg\")}r+=e.yaxis._shift,mt();var xt=function(t,e,r){return t?\"nsew\"===t?r?\"\":\"pan\"===e?\"move\":\"crosshair\":t.toLowerCase()+\"-resize\":\"pointer\"}(at+it,t._fullLayout.dragmode,gt),bt=z(e,v+y+\"drag\",xt,r,s,u,f);if(ot&&!gt)return bt.onmousedown=null,bt.style.pointerEvents=\"none\",bt;var _t,wt,Tt,kt,At,Mt,St,Et,Lt,Ct,Pt={element:bt,gd:t,plotinfo:e};function Ot(){Pt.plotinfo.selection=!1,M(t)}function It(t,r){var i=Pt.gd;if(i._fullLayout._activeShapeIndex>=0)i._fullLayout._deactivateShape(i);else{var o=i._fullLayout.clickmode;if(q(i),2!==t||yt||Ht(),gt)o.indexOf(\"select\")>-1&&S(r,i,K,J,e.id,Pt),o.indexOf(\"event\")>-1&&p.click(i,r,e.id);else if(1===t&&yt){var s=v?I:O,u=\"s\"===v||\"w\"===y?0:1,f=s._name+\".range[\"+u+\"]\",h=function(t,e){var r,n=t.range[e],i=Math.abs(n-t.range[1-e]);return\"date\"===t.type?n:\"log\"===t.type?(r=Math.ceil(Math.max(0,-Math.log(i)/Math.LN10))+3,a(\".\"+r+\"g\")(Math.pow(10,n))):(r=Math.floor(Math.log(Math.abs(n))/Math.LN10)-Math.floor(Math.log(i)/Math.LN10)+4,a(\".\"+String(r)+\"g\")(n))}(s,u),d=\"left\",g=\"middle\";if(s.fixedrange)return;v?(g=\"n\"===v?\"top\":\"bottom\",\"right\"===s.side&&(d=\"right\")):\"e\"===y&&(d=\"right\"),i._context.showAxisRangeEntryBoxes&&n.select(bt).call(c.makeEditable,{gd:i,immediate:!0,background:i._fullLayout.paper_bgcolor,text:String(h),fill:s.tickfont?s.tickfont.color:\"#444\",horizontalAlign:d,verticalAlign:g}).on(\"edit\",(function(t){var e=s.d2r(t);void 0!==e&&l.call(\"_guiRelayout\",i,f,e)}))}}}function zt(e,r){if(t._transitioningWithDuration)return!1;var n=Math.max(0,Math.min(tt,pt*e+_t)),i=Math.max(0,Math.min(et,dt*r+wt)),a=Math.abs(n-_t),o=Math.abs(i-wt);function s(){St=\"\",Tt.r=Tt.l,Tt.t=Tt.b,Lt.attr(\"d\",\"M0,0Z\")}if(Tt.l=Math.min(_t,n),Tt.r=Math.max(_t,n),Tt.t=Math.min(wt,i),Tt.b=Math.max(wt,i),rt.isSubplotConstrained)a>P||o>P?(St=\"xy\",a/tt>o/et?(o=a*et/tt,wt>i?Tt.t=wt-o:Tt.b=wt+o):(a=o*tt/et,_t>n?Tt.l=_t-a:Tt.r=_t+a),Lt.attr(\"d\",G(Tt))):s();else if(nt.isSubplotConstrained)if(a>P||o>P){St=\"xy\";var l=Math.min(Tt.l/tt,(et-Tt.b)/et),u=Math.max(Tt.r/tt,(et-Tt.t)/et);Tt.l=l*tt,Tt.r=u*tt,Tt.b=(1-l)*et,Tt.t=(1-u)*et,Lt.attr(\"d\",G(Tt))}else s();else!at||o<Math.min(Math.max(.6*a,C),P)?a<C||!it?s():(Tt.t=0,Tt.b=et,St=\"x\",Lt.attr(\"d\",function(t,e){return\"M\"+(t.l-.5)+\",\"+(e-P-.5)+\"h-3v\"+(2*P+1)+\"h3ZM\"+(t.r+.5)+\",\"+(e-P-.5)+\"h3v\"+(2*P+1)+\"h-3Z\"}(Tt,wt))):!it||a<Math.min(.6*o,P)?(Tt.l=0,Tt.r=tt,St=\"y\",Lt.attr(\"d\",function(t,e){return\"M\"+(e-P-.5)+\",\"+(t.t-.5)+\"v-3h\"+(2*P+1)+\"v3ZM\"+(e-P-.5)+\",\"+(t.b+.5)+\"v3h\"+(2*P+1)+\"v-3Z\"}(Tt,_t))):(St=\"xy\",Lt.attr(\"d\",G(Tt)));Tt.w=Tt.r-Tt.l,Tt.h=Tt.b-Tt.t,St&&(Ct=!0),t._dragged=Ct,U(Et,Lt,Tt,At,Mt,kt),Dt(),t.emit(\"plotly_relayouting\",ht),Mt=!0}function Dt(){ht={},\"xy\"!==St&&\"x\"!==St||(R(K,Tt.l/tt,Tt.r/tt,ht,rt.xaxes),Vt(\"x\",ht)),\"xy\"!==St&&\"y\"!==St||(R(J,(et-Tt.b)/et,(et-Tt.t)/et,ht,rt.yaxes),Vt(\"y\",ht))}function Rt(){Dt(),q(t),Gt(),H(t)}Pt.prepFn=function(e,r,n){var a=Pt.dragmode,s=t._fullLayout.dragmode;s!==a&&(Pt.dragmode=s),mt(),pt=t._fullLayout._invScaleX,dt=t._fullLayout._invScaleY,ot||(gt?e.shiftKey?\"pan\"===s?s=\"zoom\":m(s)||(s=\"pan\"):e.ctrlKey&&(s=\"pan\"):s=\"pan\"),x(s)?Pt.minDrag=1:Pt.minDrag=void 0,m(s)?(Pt.xaxes=K,Pt.yaxes=J,A(e,r,n,Pt,s)):(Pt.clickFn=It,m(a)&&Ot(),ot||(\"zoom\"===s?(Pt.moveFn=zt,Pt.doneFn=Rt,Pt.minDrag=1,function(e,r,n){var a=bt.getBoundingClientRect();_t=r-a.left,wt=n-a.top,t._fullLayout._calcInverseTransform(t);var s=i.apply3DTransform(t._fullLayout._invTransform)(_t,wt);_t=s[0],wt=s[1],Tt={l:_t,r:_t,w:0,t:wt,b:wt,h:0},kt=t._hmpixcount?t._hmlumcount/t._hmpixcount:o(t._fullLayout.plot_bgcolor).getLuminance(),Mt=!1,St=\"xy\",Ct=!1,Et=N(vt,kt,$,Q,At=\"M0,0H\"+tt+\"V\"+et+\"H0V0\"),Lt=j(vt,$,Q)}(0,r,n)):\"pan\"===s&&(Pt.moveFn=Ut,Pt.doneFn=Gt))),t._fullLayout._redrag=function(){var e=t._dragdata;if(e&&e.element===bt){var r=t._fullLayout.dragmode;m(r)||(mt(),Wt([0,0,tt,et]),Pt.moveFn(e.dx,e.dy))}}},g.init(Pt);var Ft=[0,0,tt,et],Bt=null,Nt=L.REDRAWDELAY,jt=e.mainplot?t._fullLayout._plots[e.mainplot]:e;function Ut(e,r){if(e*=pt,r*=dt,!t._transitioningWithDuration){if(t._fullLayout._replotting=!0,\"ew\"===it||\"ns\"===at){var n=it?-e:0,i=at?-r:0;if(nt.isSubplotConstrained){if(it&&at){var a=(e/tt-r/et)/2;n=-(e=a*tt),i=-(r=-a*et)}at?n=-i*tt/et:i=-n*et/tt}return it&&(F(K,e),Vt(\"x\")),at&&(F(J,r),Vt(\"y\")),Wt([n,i,tt,et]),qt(),void t.emit(\"plotly_relayouting\",ht)}var o,s,l=\"w\"===it==(\"n\"===at)?1:-1;if(it&&at&&(rt.isSubplotConstrained||nt.isSubplotConstrained)){var u=(e/tt+l*r/et)/2;e=u*tt,r=l*u*et}if(\"w\"===it?e=p(K,0,e):\"e\"===it?e=p(K,1,-e):it||(e=0),\"n\"===at?r=p(J,1,r):\"s\"===at?r=p(J,0,-r):at||(r=0),o=\"w\"===it?e:0,s=\"n\"===at?r:0,rt.isSubplotConstrained&&!nt.isSubplotConstrained||nt.isSubplotConstrained&&it&&at&&l>0){var c;if(nt.isSubplotConstrained||!it&&1===at.length){for(c=0;c<K.length;c++)K[c].range=K[c]._r.slice(),E(K[c],1-r/et);o=(e=r*tt/et)/2}if(nt.isSubplotConstrained||!at&&1===it.length){for(c=0;c<J.length;c++)J[c].range=J[c]._r.slice(),E(J[c],1-e/tt);s=(r=e*et/tt)/2}}nt.isSubplotConstrained&&at||Vt(\"x\"),nt.isSubplotConstrained&&it||Vt(\"y\");var f=tt-e,h=et-r;!nt.isSubplotConstrained||it&&at||(it?(s=o?0:e*et/tt,h=f*et/tt):(o=s?0:r*tt/et,f=h*tt/et)),Wt([o,s,f,h]),qt(),t.emit(\"plotly_relayouting\",ht)}function p(t,e,r){for(var n,i,a=1-e,o=0;o<t.length;o++){var s=t[o];if(!s.fixedrange){n=s,i=s._rl[a]+(s._rl[e]-s._rl[a])/B(r/s._length);var l=s.l2r(i);!1!==l&&void 0!==l&&(s.range[e]=l)}}return n._length*(n._rl[e]-i)/(n._rl[e]-n._rl[a])}}function Vt(t,e){for(var r=nt.isSubplotConstrained?{x:J,y:K}[t]:nt[t+\"axes\"],n=nt.isSubplotConstrained?{x:K,y:J}[t]:[],i=0;i<r.length;i++){var a=r[i],o=a._id,s=nt.xLinks[o]||nt.yLinks[o],l=n[0]||V[s]||Z[s];l&&(e?(e[a._name+\".range[0]\"]=e[l._name+\".range[0]\"],e[a._name+\".range[1]\"]=e[l._name+\".range[1]\"]):a.range=l.range.slice())}}function qt(){var r,n=[];function i(t){for(r=0;r<t.length;r++)t[r].fixedrange||n.push(t[r]._id)}function a(t,e){for(r=0;r<t.length;r++){var i=t[r],a=i[e];i.fixedrange||\"sync\"!==a.tickmode||n.push(a._id)}}for(st&&(i(K),i(rt.xaxes),i(nt.xaxes),a(e.overlays,\"xaxis\")),lt&&(i(J),i(rt.yaxes),i(nt.yaxes),a(e.overlays,\"yaxis\")),ht={},r=0;r<n.length;r++){var o=n[r],s=k(t,o);d.drawOne(t,s,{skipTitle:!0}),ht[s._name+\".range[0]\"]=s.range[0],ht[s._name+\".range[1]\"]=s.range[1]}d.redrawComponents(t,n)}function Ht(){if(!t._transitioningWithDuration){var e=t._context.doubleClick,r=[];it&&(r=r.concat(K)),at&&(r=r.concat(J)),nt.xaxes&&(r=r.concat(nt.xaxes)),nt.yaxes&&(r=r.concat(nt.yaxes));var n,i,a={};if(\"reset+autosize\"===e)for(e=\"autosize\",i=0;i<r.length;i++){var 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r,i,a,o,s,h,p,d,v,g=c(0,e);function y(t){return e.invert(t)}function m(r){var n=e.rotate(),i=e.invert(t.midPt);r(\"projection.rotation.lon\",-n[0]),r(\"center.lon\",i[0]),r(\"center.lat\",i[1])}return g.on(\"zoomstart\",(function(){n.select(this).style(l),r=n.mouse(this),i=e.rotate(),a=e.translate(),o=i,s=y(r)})).on(\"zoom\",(function(){if(h=n.mouse(this),function(t){var r=y(t);if(!r)return!0;var n=e(r);return Math.abs(n[0]-t[0])>2||Math.abs(n[1]-t[1])>2}(r))return g.scale(e.scale()),void g.translate(e.translate());e.scale(n.event.scale),e.translate([a[0],n.event.translate[1]]),s?y(h)&&(d=y(h),p=[o[0]+(d[0]-s[0]),i[1],i[2]],e.rotate(p),o=p):s=y(r=h),v=!0,t.render(!0);var l=e.rotate(),u=e.invert(t.midPt);t.graphDiv.emit(\"plotly_relayouting\",{\"geo.projection.scale\":e.scale()/t.fitScale,\"geo.center.lon\":u[0],\"geo.center.lat\":u[1],\"geo.projection.rotation.lon\":-l[0]})})).on(\"zoomend\",(function(){n.select(this).style(u),v&&f(t,e,m)})),g}function d(t,e){var r,i={r:e.rotate(),k:e.scale()},a=c(0,e),h=function(t){for(var e=0,r=arguments.length,i=[];++e<r;)i.push(arguments[e]);var a=n.dispatch.apply(null,i);return a.of=function(e,r){return function(i){var o;try{o=i.sourceEvent=n.event,i.target=t,n.event=i,a[i.type].apply(e,r)}finally{n.event=o}}},a}(a,\"zoomstart\",\"zoom\",\"zoomend\"),p=0,d=a.on;function y(t){var r=e.rotate();t(\"projection.rotation.lon\",-r[0]),t(\"projection.rotation.lat\",-r[1])}return a.on(\"zoomstart\",(function(){n.select(this).style(l);var t,u,c,f,y,b,_,w,T,k,A,M=n.mouse(this),S=e.rotate(),E=S,L=e.translate(),C=(u=.5*(t=S)[0]*o,c=.5*t[1]*o,f=.5*t[2]*o,y=Math.sin(u),b=Math.cos(u),_=Math.sin(c),w=Math.cos(c),T=Math.sin(f),[b*w*(k=Math.cos(f))+y*_*T,y*w*k-b*_*T,b*_*k+y*w*T,b*w*T-y*_*k]);r=v(e,M),d.call(a,\"zoom\",(function(){var t,a,o,l,u,c,f,p,d,y,b=n.mouse(this);if(e.scale(i.k=n.event.scale),r){if(v(e,b)){e.rotate(S).translate(L);var _=v(e,b),w=function(t,e){if(t&&e){var 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c=r.match(i);o=\"x\"+c[1],s=\"y\"+c[2]}for(var f=0;f<t.length;f++)a=t[f],\"gl2d\"===e&&n.traceIs(a,\"gl2d\")?a[l[0]]===o&&a[l[1]]===s&&u.push(a):a[l]===r&&u.push(a);return u}},2428:function(t,e,r){\"use strict\";var n=r(62644),i=r(97264),a=r(29128),o=r(33816),s=r(89184);function l(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxInited=!1,this.boxStart=[0,0],this.boxEnd=[0,0],this.dragStart=[0,0]}t.exports=function(t){var e=t.mouseContainer,r=t.glplot,u=new l(e,r);function c(){t.xaxis.autorange=!1,t.yaxis.autorange=!1}function f(e,n,i){var a,s,l=t.calcDataBox(),f=r.viewBox,h=u.lastPos[0],p=u.lastPos[1],d=o.MINDRAG*r.pixelRatio,v=o.MINZOOM*r.pixelRatio;function g(e,r,n){var 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a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var 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e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=1.5,n=e.title.font.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?n*(r+(i?1:0))-10:n*(r+(i?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},t.exports=function(t){return new a(t)}},39952:function(t,e,r){\"use strict\";var n=r(67824).overrideAll,i=r(17188),a=r(64859),o=r(9616),s=r(33816),l=r(57952),u=r(65460),c=r(84888).op;e.name=\"gl2d\",e.attr=[\"xaxis\",\"yaxis\"],e.idRoot=[\"x\",\"y\"],e.idRegex=s.idRegex,e.attrRegex=s.attrRegex,e.attributes=r(26720),e.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},e.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),e.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:u.hoverlabel},\"plot\",\"nested\"),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=c(r,\"gl2d\",o),u=s._scene2d;void 0===u&&(u=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=u),u.plot(l,t.calcdata,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];s._scene2d&&0===c(t,\"gl2d\",o).length&&(s._scene2d.destroy(),delete n._plots[o])}l.clean.apply(this,arguments)},e.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++)e._plots[r[n]]._scene2d.updateFx(e.dragmode)}},17188:function(t,e,r){\"use strict\";var n,i,a=r(24040),o=r(54460),s=r(93024),l=r(67792).gl_plot2d,u=r(67792).gl_spikes2d,c=r(67792).gl_select_box,f=r(5408),h=r(92568),p=r(2428),d=r(16576),v=r(71888),g=v.enforce,y=v.clean,m=r(19280).doAutoRange,x=r(72760),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=r(33816).SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=u(this.glplot),this.selectBox=c(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}t.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var u=0;u<4;++u){var c=a[4*(r*o+l)+u];a[4*(r*o+l)+u]=a[4*(r*s+l)+u],a[4*(r*s+l)+u]=c}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\",{willReadFrequently:!0}),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var u=n[r._name];u.range=s,u.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};y(s,this.xaxis),y(s,this.yaxis);var l,u,c=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[c.l+f[0]*c.w,c.b+h[0]*c.h,i-c.r-(1-f[1])*c.w,a-c.t-(1-h[1])*c.h],this.mouseContainer.style.width=c.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=c.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=c.h*(h[1]-h[0]),this.mouseContainer.style.left=c.l+f[0]*c.w+\"px\",this.mouseContainer.style.top=c.t+(1-h[1])*c.h+\"px\",u=0;u<2;++u)(l=this[w[u]])._length=o.viewBox[u+2]-o.viewBox[u],m(this.graphDiv,l),l.setScale();g(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],u=this.traces[i.uid];u?u.update(i,l):(u=i._module.plot(this,i,l),this.traces[i.uid]=u)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var u=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],c=0;c<2;c++)e.boxStart[c]===e.boxEnd[c]&&(u[c]=t.dataBox[c],u[c+2]=t.dataBox[c+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var v=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),v.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var g=this.fullData[v.trace.index]||{},y=v.pointIndex,m=s.castHoverinfo(g,i,y);if(m&&\"all\"!==m){var x=m.split(\"+\");-1===x.indexOf(\"x\")&&(v.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(v.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(v.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(v.textLabel=void 0),-1===x.indexOf(\"name\")&&(v.name=void 0)}s.loneHover({x:v.screenCoord[0],y:v.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",v.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",v.traceCoord[1]),zLabel:v.traceCoord[2],text:v.textLabel,name:v.name,color:s.castHoverOption(g,y,\"bgcolor\")||v.color,borderColor:s.castHoverOption(g,y,\"bordercolor\"),fontFamily:s.castHoverOption(g,y,\"font.family\"),fontSize:s.castHoverOption(g,y,\"font.size\"),fontColor:s.castHoverOption(g,y,\"font.color\"),nameLength:s.castHoverOption(g,y,\"namelength\"),textAlign:s.castHoverOption(g,y,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},12536:function(t,e,r){\"use strict\";var n=r(67824).overrideAll,i=r(65460),a=r(98432),o=r(84888).op,s=r(3400),l=r(9616),u=\"gl3d\",c=\"scene\";e.name=u,e.attr=c,e.idRoot=c,e.idRegex=e.attrRegex=s.counterRegex(\"scene\"),e.attributes=r(6636),e.layoutAttributes=r(346),e.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),e.supplyLayoutDefaults=r(5208),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots[u],i=0;i<n.length;i++){var s=n[i],l=o(r,u,s),c=e[s],f=c.camera,h=c._scene;h||(h=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:f},e),c._scene=h),h.viewInitial||(h.viewInitial={up:{x:f.up.x,y:f.up.y,z:f.up.z},eye:{x:f.eye.x,y:f.eye.y,z:f.eye.z},center:{x:f.center.x,y:f.center.y,z:f.center.z}}),h.plot(l,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots[u]||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},e.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),c+e}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=0;n<r.length;n++)e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}},6636:function(t){\"use strict\";t.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},86140:function(t,e,r){\"use strict\";var n=r(76308),i=r(94724),a=r(92880).extendFlat,o=r(67824).overrideAll;t.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,autorangeoptions:{minallowed:i.autorangeoptions.minallowed,maxallowed:i.autorangeoptions.maxallowed,clipmin:i.autorangeoptions.clipmin,clipmax:i.autorangeoptions.clipmax,include:i.autorangeoptions.include,editType:\"plot\"},rangemode:i.rangemode,minallowed:i.minallowed,maxallowed:i.maxallowed,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.minor.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,labelalias:i.labelalias,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},64380:function(t,e,r){\"use strict\";var n=r(49760).mix,i=r(3400),a=r(31780),o=r(86140),s=r(14944),l=r(28336),u=[\"xaxis\",\"yaxis\",\"zaxis\"];t.exports=function(t,e,r){var c,f;function h(t,e){return i.coerce(c,f,o,t,e)}for(var p=0;p<u.length;p++){var d=u[p];c=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(c,f,h,r),l(c,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noAutotickangles:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelstep:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,noInsiderange:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,72.72727272727273).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},44728:function(t,e,r){\"use strict\";var n=r(43080),i=r(3400),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickFontWeight=[\"normal\",\"normal\",\"normal\",\"normal\"],this.tickFontStyle=[\"normal\",\"normal\",\"normal\",\"normal\"],this.tickFontVariant=[\"normal\",\"normal\",\"normal\",\"normal\"],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelFontWeight=[\"normal\",\"normal\",\"normal\",\"normal\"],this.labelFontStyle=[\"normal\",\"normal\",\"normal\",\"normal\"],this.labelFontVariant=[\"normal\",\"normal\",\"normal\",\"normal\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=this,o=0;o<3;++o){var s=e[a[o]];s.visible?(r.labels[o]=t._meta?i.templateString(s.title.text,t._meta):s.title.text,\"font\"in s.title&&(s.title.font.color&&(r.labelColor[o]=n(s.title.font.color)),s.title.font.family&&(r.labelFont[o]=s.title.font.family),s.title.font.size&&(r.labelSize[o]=s.title.font.size),s.title.font.weight&&(r.labelFontWeight[o]=s.title.font.weight),s.title.font.style&&(r.labelFontStyle[o]=s.title.font.style),s.title.font.variant&&(r.labelFontVariant[o]=s.title.font.variant)),\"showline\"in s&&(r.lineEnable[o]=s.showline),\"linecolor\"in s&&(r.lineColor[o]=n(s.linecolor)),\"linewidth\"in s&&(r.lineWidth[o]=s.linewidth),\"showgrid\"in s&&(r.gridEnable[o]=s.showgrid),\"gridcolor\"in s&&(r.gridColor[o]=n(s.gridcolor)),\"gridwidth\"in s&&(r.gridWidth[o]=s.gridwidth),\"log\"===s.type?r.zeroEnable[o]=!1:\"zeroline\"in s&&(r.zeroEnable[o]=s.zeroline),\"zerolinecolor\"in s&&(r.zeroLineColor[o]=n(s.zerolinecolor)),\"zerolinewidth\"in s&&(r.zeroLineWidth[o]=s.zerolinewidth),\"ticks\"in s&&s.ticks?r.lineTickEnable[o]=!0:r.lineTickEnable[o]=!1,\"ticklen\"in s&&(r.lineTickLength[o]=r._defaultLineTickLength[o]=s.ticklen),\"tickcolor\"in s&&(r.lineTickColor[o]=n(s.tickcolor)),\"tickwidth\"in s&&(r.lineTickWidth[o]=s.tickwidth),\"tickangle\"in s&&(r.tickAngle[o]=\"auto\"===s.tickangle?-3600:Math.PI*-s.tickangle/180),\"showticklabels\"in s&&(r.tickEnable[o]=s.showticklabels),\"tickfont\"in s&&(s.tickfont.color&&(r.tickColor[o]=n(s.tickfont.color)),s.tickfont.family&&(r.tickFont[o]=s.tickfont.family),s.tickfont.size&&(r.tickSize[o]=s.tickfont.size),s.tickfont.weight&&(r.tickFontWeight[o]=s.tickfont.weight),s.tickfont.style&&(r.tickFontStyle[o]=s.tickfont.style),s.tickfont.variant&&(r.tickFontVariant[o]=s.tickfont.variant)),\"mirror\"in s?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(s.mirror)?(r.lineTickMirror[o]=!0,r.lineMirror[o]=!0):!0===s.mirror?(r.lineTickMirror[o]=!1,r.lineMirror[o]=!0):(r.lineTickMirror[o]=!1,r.lineMirror[o]=!1):r.lineMirror[o]=!1,\"showbackground\"in s&&!1!==s.showbackground?(r.backgroundEnable[o]=!0,r.backgroundColor[o]=n(s.backgroundcolor)):r.backgroundEnable[o]=!1):(r.tickEnable[o]=!1,r.labelEnable[o]=!1,r.lineEnable[o]=!1,r.lineTickEnable[o]=!1,r.gridEnable[o]=!1,r.zeroEnable[o]=!1,r.backgroundEnable[o]=!1)}},t.exports=function(t,e){var r=new o;return r.merge(t,e),r}},5208:function(t,e,r){\"use strict\";var n=r(3400),i=r(76308),a=r(24040),o=r(168),s=r(64380),l=r(346),u=r(84888).op,c=\"gl3d\";function f(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),f=[\"up\",\"center\",\"eye\"],h=0;h<f.length;h++)r(\"camera.\"+f[h]+\".x\"),r(\"camera.\"+f[h]+\".y\"),r(\"camera.\"+f[h]+\".z\");r(\"camera.projection.type\");var p=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),d=r(\"aspectmode\",p?\"manual\":\"auto\");p||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===d&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var v=u(n.fullData,c,n.id);s(t,e,{font:n.font,scene:n.id,data:v,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var g=n.getDfltFromLayout(\"dragmode\");if(!1!==g&&!g)if(g=\"orbit\",t.camera&&t.camera.up){var y=t.camera.up.x,m=t.camera.up.y,x=t.camera.up.z;0!==x&&(y&&m&&x?x/Math.sqrt(y*y+m*m+x*x)>.999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}t.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:c,attributes:l,handleDefaults:f,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},346:function(t,e,r){\"use strict\";var n=r(86140),i=r(86968).u,a=r(92880).extendFlat,o=r(3400).counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}t.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},9020:function(t,e,r){\"use strict\";var n=r(43080),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},t.exports=function(t){var e=new a;return e.merge(t),e}},87152:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],u=0;u<3;++u){var c=s[a[u]];if(c._length=(r[u].hi-r[u].lo)*r[u].pixelsPerDataUnit/t.dataScale[u],Math.abs(c._length)===1/0||isNaN(c._length))l[u]=[];else{c._input_range=c.range.slice(),c.range[0]=r[u].lo/t.dataScale[u],c.range[1]=r[u].hi/t.dataScale[u],c._m=1/(t.dataScale[u]*r[u].pixelsPerDataUnit),c.range[0]===c.range[1]&&(c.range[0]-=1,c.range[1]+=1);var f=c.tickmode;if(\"auto\"===c.tickmode){c.tickmode=\"linear\";var h=c.nticks||i.constrain(c._length/40,4,9);n.autoTicks(c,Math.abs(c.range[1]-c.range[0])/h)}for(var p=n.calcTicks(c,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[u],\"date\"===c.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[u]=p,c.tickmode=f}}for(e.ticks=l,u=0;u<3;++u)for(o[u]=.5*(t.glplot.bounds[0][u]+t.glplot.bounds[1][u]),d=0;d<2;++d)e.bounds[d][u]=t.glplot.bounds[d][u];t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=r(54460),i=r(3400),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},94424:function(t){\"use strict\";function e(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}t.exports=function(t,r){return e(t.projection,e(t.view,e(t.model,[r[0],r[1],r[2],1])))}},98432:function(t,e,r){\"use strict\";var n,i,a=r(67792).gl_plot3d,o=a.createCamera,s=a.createScene,l=r(5408),u=r(89184),c=r(24040),f=r(3400),h=f.preserveDrawingBuffer(),p=r(54460),d=r(93024),v=r(43080),g=r(16576),y=r(94424),m=r(44728),x=r(9020),b=r(87152),_=r(19280).applyAutorangeOptions,w=!1;function T(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=m(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=c.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=c.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var k=T.prototype;k.prepareOptions=function(){var t=this,e={canvas:t.canvas,gl:t.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:t.camera,pixelRatio:t.pixelRatio};if(t.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");e.gl=i,e.canvas=n}return e};var A=!0;k.tryCreatePlot=function(){var t=this,e=t.prepareOptions(),r=!0;try{t.glplot=s(e)}catch(n){if(t.staticMode||!A||h)r=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=e.glOptions.preserveDrawingBuffer=!0,t.glplot=s(e)}catch(t){h=e.glOptions.preserveDrawingBuffer=!1,r=!1}}}return A=!1,r},k.initializeGLCamera=function(){var t=this,e=t.fullSceneLayout.camera,r=\"orthographic\"===e.projection.type;t.camera=o(t.container,{center:[e.center.x,e.center.y,e.center.z],eye:[e.eye.x,e.eye.y,e.eye.z],up:[e.up.x,e.up.y,e.up.z],_ortho:r,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},k.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"touchstart\",(function(){w=!0})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!u&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},k.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var u=Object.keys(e.traces),c=null,h=e.glplot.selection,v=0;v<u.length;++v)\"skip\"!==(t=e.traces[u[v]]).data.hoverinfo&&t.handlePick(h)&&(c=t),t.setContourLevels&&t.setContourLevels();function g(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==c){var m=y(e.glplot.cameraParams,h.dataCoordinate);t=c.data;var x,_=r._fullData[t.index],T=h.index,k={xLabel:g(\"x\",h.traceCoordinate[0],t.xhoverformat),yLabel:g(\"y\",h.traceCoordinate[1],t.yhoverformat),zLabel:g(\"z\",h.traceCoordinate[2],t.zhoverformat)},A=d.castHoverinfo(_,e.fullLayout,T),M=(A||\"\").split(\"+\"),S=A&&\"all\"===A;_.hovertemplate||S||(-1===M.indexOf(\"x\")&&(k.xLabel=void 0),-1===M.indexOf(\"y\")&&(k.yLabel=void 0),-1===M.indexOf(\"z\")&&(k.zLabel=void 0),-1===M.indexOf(\"text\")&&(h.textLabel=void 0),-1===M.indexOf(\"name\")&&(c.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=g(\"x\",h.traceCoordinate[3],t.uhoverformat),(S||-1!==M.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=g(\"y\",h.traceCoordinate[4],t.vhoverformat),(S||-1!==M.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=g(\"z\",h.traceCoordinate[5],t.whoverformat),(S||-1!==M.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=h.traceCoordinate[6].toPrecision(3),(S||-1!==M.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=h.traceCoordinate[7].toPrecision(3),(S||-1!==M.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),h.textLabel&&E.push(h.textLabel),x=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(h.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),h.textLabel&&E.push(h.textLabel),x=E.join(\"<br>\")):x=h.textLabel;var L={x:h.traceCoordinate[0],y:h.traceCoordinate[1],z:h.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:T};d.appendArrayPointValue(L,_,T),t._module.eventData&&(L=_._module.eventData(L,h,_,{},T));var C={points:[L]};if(e.fullSceneLayout.hovermode){var P=[];d.loneHover({trace:_,x:(.5+.5*m[0]/m[3])*s,y:(.5-.5*m[1]/m[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:x,name:c.name,color:d.castHoverOption(_,T,\"bgcolor\")||c.color,borderColor:d.castHoverOption(_,T,\"bordercolor\"),fontFamily:d.castHoverOption(_,T,\"font.family\"),fontSize:d.castHoverOption(_,T,\"font.size\"),fontColor:d.castHoverOption(_,T,\"font.color\"),nameLength:d.castHoverOption(_,T,\"namelength\"),textAlign:d.castHoverOption(_,T,\"align\"),hovertemplate:f.castOption(_,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},L,k),eventData:[L]},{container:n,gd:r,inOut_bbox:P}),L.bbox=P[0]}h.distance<5&&(h.buttons||w)?r.emit(\"plotly_click\",C):r.emit(\"plotly_hover\",C),this.oldEventData=C}else d.loneUnhover(n),this.oldEventData&&r.emit(\"plotly_unhover\",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)},k.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var M=[\"xaxis\",\"yaxis\",\"zaxis\"];function S(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=M[i],o=a.charAt(0),s=n[a],l=e[o],u=e[o+\"calendar\"],c=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(c||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,u),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,u),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],c-1)}}k.plot=function(t,e,r){var n=this;if(n.plotArgs=[t,e,r],!n.glplot.contextLost){var 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r={};if(i.isPlainObject(t))r.id=t.id,r.style=t;else if(\"string\"==typeof t)if(r.id=t,-1!==y.styleValuesMapbox.indexOf(t))r.style=T(t);else if(y.stylesNonMapbox[t]){r.style=y.stylesNonMapbox[t];var n=r.style.sources[\"plotly-\"+t],a=n?n.tiles:void 0;a&&a[0]&&\"?api_key=\"===a[0].slice(-9)&&(a[0]+=e._mapboxAccessToken)}else r.style=t;else r.id=y.styleValueDflt,r.style=T(y.styleValueDflt);return r.transition={duration:0,delay:0},r}function T(t){return y.styleUrlPrefix+t+\"-\"+y.styleUrlSuffix}function k(t){return[t.lon,t.lat]}b.updateData=function(t){var e,r,n,i,a=this.traceHash,o=t.slice().sort((function(t,e){return _[t[0].trace.type]-_[e[0].trace.type]}));for(n=0;n<o.length;n++){var s=o[n],l=!1;(e=a[(r=s[0].trace).uid])&&(e.type===r.type?(e.update(s),l=!0):e.dispose()),!l&&r._module&&(a[r.uid]=r._module.plot(this,s))}var u=Object.keys(a);t:for(n=0;n<u.length;n++){var c=u[n];for(i=0;i<t.length;i++)if(c===(r=t[i][0].trace).uid)continue t;(e=a[c]).dispose(),delete 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e=r.div.getBoundingClientRect(),a=[t.originalEvent.offsetX,t.originalEvent.offsetY];t.target.getBoundingClientRect=function(){return e},r.xaxis.p2c=function(){return i.unproject(a).lng},r.yaxis.p2c=function(){return i.unproject(a).lat},n._fullLayout._rehover=function(){n._fullLayout._hoversubplot===r.id&&n._fullLayout[r.id]&&u.hover(n,t,r.id)},u.hover(n,t,r.id),n._fullLayout._hoversubplot=r.id})),i.on(\"dragstart\",(function(){r.dragging=!0,a()})),i.on(\"zoomstart\",a),i.on(\"mouseout\",(function(){n._fullLayout._hoversubplot=null})),i.on(\"drag\",s),i.on(\"zoom\",s),i.on(\"dblclick\",(function(){var t=n._fullLayout[r.id];o.call(\"_storeDirectGUIEdit\",n.layout,n._fullLayout._preGUI,r.getViewEdits(t));var e=r.viewInitial;i.setCenter(k(e.center)),i.setZoom(e.zoom),i.setBearing(e.bearing),i.setPitch(e.pitch);var a=r.getView();t._input.center=t.center=a.center,t._input.zoom=t.zoom=a.zoom,t._input.bearing=t.bearing=a.bearing,t._input.pitch=t.pitch=a.pitch,n.emit(\"plotly_doubleclick\",null),n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(a))})),r.clearOutline=function(){v(r.dragOptions),d(r.dragOptions.gd)},r.onClickInPanFn=function(t){return function(e){var i=n._fullLayout.clickmode;i.indexOf(\"select\")>-1&&g(e.originalEvent,n,[r.xaxis],[r.yaxis],r.id,t),i.indexOf(\"event\")>-1&&u.click(n,e.originalEvent)}}},b.updateFx=function(t){var e=this,r=e.map,n=e.gd;if(!e.isStatic){var a,o=t.dragmode;a=function(t,r){r.isRect?(t.range={})[e.id]=[u([r.xmin,r.ymin]),u([r.xmax,r.ymax])]:(t.lassoPoints={})[e.id]=r.map(u)};var 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e,r,s=this,u=s.isSmith,c=s.gd,f=s.layers,h=t._zoomlayer,p=S.MINZOOM,d=S.OFFEDGE,v=s.radius,x=s.innerRadius,T=s.cx,k=s.cy,A=s.cxx,M=s.cyy,L=s.sectorInRad,C=s.vangles,P=s.radialAxis,O=E.clampTiny,I=E.findXYatLength,z=E.findEnclosingVertexAngles,D=S.cornerHalfWidth,R=S.cornerLen/2,F=g.makeDragger(f,\"path\",\"maindrag\",!1===t.dragmode?\"none\":\"crosshair\");n.select(F).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(T,k)),F.onmousemove=function(t){m.hover(c,t,s.id),c._fullLayout._lasthover=F,c._fullLayout._hoversubplot=s.id},F.onmouseout=function(t){c._dragging||y.unhover(c,t)};var B,N,j,U,V,q,H,G,W,Y={element:F,gd:c,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function X(t,e){return Math.sqrt(t*t+e*e)}function Z(t,e){return X(t-A,e-M)}function K(t,e){return Math.atan2(M-e,t-A)}function J(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function $(t,e){if(0===t)return s.pathSector(2*D);var 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I,z,D,B=g.makeRectDragger(c,T,\"crosshair\",-x,-x,m,m),N={element:B,gd:u};!1===t.dragmode&&(N.dragmode=!1),V(n.select(B),v.visible&&h<f,{transform:l(b,_)}),N.prepFn=function(){I=null,z=null,D=null,N.moveFn=j,N.doneFn=q,w(u)},N.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<S.MINDRAG&&(t=0,e=0),[t,e]},y.init(N)}function j(t,e){if(I)I(t,e);else{var n=[t,-e],a=[Math.cos(M),Math.sin(M)],s=Math.abs(o.dot(n,a)/Math.sqrt(o.dot(n,n)));isNaN(s)||(I=s<.5?H:G)}var l={};!function(t){null!==z?t[i.id+\".radialaxis.angle\"]=z:null!==D&&(t[i.id+\".radialaxis.range[\"+r+\"]\"]=D)}(l),u.emit(\"plotly_relayouting\",l)}function q(){null!==z?a.call(\"_guiRelayout\",u,i.id+\".radialaxis.angle\",z):null!==D&&a.call(\"_guiRelayout\",u,i.id+\".radialaxis.range[\"+r+\"]\",D)}function H(t,e){if(0!==r){var n=b+t,a=_+e;z=Math.atan2(d-a,n-p),i.vangles&&(z=U(z,i.vangles)),z=F(z);var o=l(p,d)+s(-z);c[\"radial-axis\"].attr(\"transform\",o),c[\"radial-line\"].select(\"line\").attr(\"transform\",o);var 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i=t[0].trace,o=\"h\"===i.orientation,s=\"waterfall\"===i.type,l=\"funnel\"===i.type;function u(t){return c(o?r:n,+t,!0).text}var f,h,p=i.textinfo,d=t[e],v=p.split(\"+\"),g=[],y=function(t){return-1!==v.indexOf(t)};if(y(\"label\")&&g.push((h=t[e].p,c(o?n:r,h,!0).text)),y(\"text\")&&(0===(f=a.castOption(i,d.i,\"text\"))||f)&&g.push(f),s){var m=+d.rawS||d.s,x=d.v,b=x-m;y(\"initial\")&&g.push(u(b)),y(\"delta\")&&g.push(u(m)),y(\"final\")&&g.push(u(x))}if(l){y(\"value\")&&g.push(u(d.s));var _=0;y(\"percent initial\")&&_++,y(\"percent previous\")&&_++,y(\"percent total\")&&_++;var w=_>1;y(\"percent initial\")&&(f=a.formatPercent(d.begR),w&&(f+=\" of initial\"),g.push(f)),y(\"percent previous\")&&(f=a.formatPercent(d.difR),w&&(f+=\" of previous\"),g.push(f)),y(\"percent total\")&&(f=a.formatPercent(d.sumR),w&&(f+=\" of total\"),g.push(f))}return g.join(\"<br>\")}(e,r,n,i):v.getValue(s.text,r),v.coerceString(m,o)}(I,n,i,S,O);k=function(t,e){var r=v.getValue(t.textposition,e);return v.coerceEnumerated(x,r)}(D,i);var B=\"stack\"===w.mode||\"relative\"===w.mode,N=n[i],j=!B||N._outmost,U=N.hasB,V=g&&g-y>_;if(F&&\"none\"!==k&&(!N.isBlank&&s!==u&&f!==p||\"auto\"!==k&&\"inside\"!==k)){var q=I.font,H=d.getBarColor(n[i],D),G=d.getInsideTextFont(D,i,q,H),W=d.getOutsideTextFont(D,i,q),Y=D.insidetextanchor||\"end\",X=r.datum();R?\"log\"===S.type&&X.s0<=0&&(s=S.range[0]<S.range[1]?0:S._length):\"log\"===O.type&&X.s0<=0&&(f=O.range[0]<O.range[1]?O._length:0);var Z,K,J,$,Q,tt=Math.abs(u-s),et=Math.abs(p-f),rt=tt-2*_,nt=et-2*_;if(\"outside\"===k&&(j||N.hasB||(k=\"inside\")),\"auto\"===k)if(j){k=\"inside\",Z=z(r,F,Q=a.ensureUniformFontSize(t,G)),J=(K=l.bBox(Z.node())).width,$=K.height;var it,at=J>0&&$>0;it=V?U?E(rt-2*g,nt,J,$,R)||E(rt,nt-2*g,J,$,R):R?E(rt-(g-y),nt,J,$,R)||E(rt,nt-2*(g-y),J,$,R):E(rt,nt-(g-y),J,$,R)||E(rt-2*(g-y),nt,J,$,R):E(rt,nt,J,$,R),at&&it?k=\"inside\":(k=\"outside\",Z.remove(),Z=null)}else k=\"inside\";if(!Z){var ot=(Z=z(r,F,Q=a.ensureUniformFontSize(t,\"outside\"===k?W:G))).attr(\"transform\");if(Z.attr(\"transform\",\"\"),J=(K=l.bBox(Z.node())).width,$=K.height,Z.attr(\"transform\",ot),J<=0||$<=0)return void Z.remove()}var st,lt=D.textangle;st=\"outside\"===k?function(t,e,r,n,i,a){var o,s=!!a.isHorizontal,l=!!a.constrained,u=a.angle||0,c=i.width,f=i.height,h=Math.abs(e-t),p=Math.abs(n-r);o=s?p>2*_?_:0:h>2*_?_:0;var d=1;l&&(d=s?Math.min(1,p/f):Math.min(1,h/c));var v=L(u),g=C(i,v),y=(s?g.x:g.y)/2,m=(i.left+i.right)/2,x=(i.top+i.bottom)/2,b=(t+e)/2,w=(r+n)/2,T=0,k=0,M=s?A(e,t):A(r,n);return s?(b=e-M*o,T=M*y):(w=n+M*o,k=-M*y),{textX:m,textY:x,targetX:b,targetY:w,anchorX:T,anchorY:k,scale:d,rotate:v}}(s,u,f,p,K,{isHorizontal:R,constrained:\"both\"===D.constraintext||\"outside\"===D.constraintext,angle:lt}):P(s,u,f,p,K,{isHorizontal:R,constrained:\"both\"===D.constraintext||\"inside\"===D.constraintext,angle:lt,anchor:Y,hasB:U,r:g,overhead:y}),st.fontSize=Q.size,h(\"histogram\"===D.type?\"bar\":D.type,st,I),N.transform=st;var ut=M(Z,I,w,T);a.setTransormAndDisplay(ut,st)}else r.select(\"text\").remove()}(t,e,R,r,T,H,G,W,Y,rt,it,g,y),e.layerClipId&&l.hideOutsideRangePoint(u,R.select(\"text\"),w,O,f.xcalendar,f.ycalendar)}));var W=!1===f.cliponaxis;l.setClipUrl(u,W?null:e.layerClipId,t)}));u.getComponentMethod(\"errorbars\",\"plot\")(t,D,e,g)},toMoveInsideBar:P}},45784:function(t){\"use strict\";function e(t,e,r,n,i){var a=e.c2p(n?t.s0:t.p0,!0),o=e.c2p(n?t.s1:t.p1,!0),s=r.c2p(n?t.p0:t.s0,!0),l=r.c2p(n?t.p1:t.s1,!0);return i?[(a+o)/2,(s+l)/2]:n?[o,(s+l)/2]:[(a+o)/2,l]}t.exports=function(t,r){var n,i=t.cd,a=t.xaxis,o=t.yaxis,s=i[0].trace,l=\"funnel\"===s.type,u=\"h\"===s.orientation,c=[];if(!1===r)for(n=0;n<i.length;n++)i[n].selected=0;else for(n=0;n<i.length;n++){var f=i[n],h=\"ct\"in f?f.ct:e(f,a,o,u,l);r.contains(h,!1,n,t)?(c.push({pointNumber:n,x:a.c2d(f.x),y:o.c2d(f.y)}),f.selected=1):f.selected=0}return c}},72592:function(t,e,r){\"use strict\";t.exports=i;var n=r(3400).distinctVals;function i(t,e){this.traces=t,this.sepNegVal=e.sepNegVal,this.overlapNoMerge=e.overlapNoMerge;for(var r=1/0,i=e.posAxis._id.charAt(0),a=[],o=0;o<t.length;o++){for(var s=t[o],l=0;l<s.length;l++){var u=s[l],c=u.p;void 0===c&&(c=u[i]),void 0!==c&&a.push(c)}s[0]&&s[0].width1&&(r=Math.min(s[0].width1,r))}this.positions=a;var f=n(a);this.distinctPositions=f.vals,1===f.vals.length&&r!==1/0?this.minDiff=r:this.minDiff=Math.min(f.minDiff,r);var 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i,a=t.cd[0].trace.hoveron,o=[];return-1!==a.indexOf(\"boxes\")&&(o=o.concat(l(t,e,r,n))),-1!==a.indexOf(\"points\")&&(i=u(t,e,r)),\"closest\"===n?i?[i]:o:i?(o.push(i),o):o},hoverOnBoxes:l,hoverOnPoints:u}},67244:function(t,e,r){\"use strict\";t.exports={attributes:r(63188),layoutAttributes:r(16560),supplyDefaults:r(90624).supplyDefaults,crossTraceDefaults:r(90624).crossTraceDefaults,supplyLayoutDefaults:r(68832).supplyLayoutDefaults,calc:r(62555),crossTraceCalc:r(96404).crossTraceCalc,plot:r(18728).plot,style:r(25776).style,styleOnSelect:r(25776).styleOnSelect,hoverPoints:r(27576).hoverPoints,eventData:r(10392),selectPoints:r(8264),moduleType:\"trace\",name:\"box\",basePlotModule:r(57952),categories:[\"cartesian\",\"svg\",\"symbols\",\"oriented\",\"box-violin\",\"showLegend\",\"boxLayout\",\"zoomScale\"],meta:{}}},16560:function(t){\"use 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b=t.selectAll(\"path.box\").data(\"violin\"!==r.type||r.box.visible?i.identity:[]);b.enter().append(\"path\").style(\"vector-effect\",o?\"none\":\"non-scaling-stroke\").attr(\"class\",\"box\"),b.exit().remove(),b.each((function(t){if(t.empty)return n.select(this).attr(\"d\",\"M0,0Z\");var e=f.c2l(t.pos+p,!0),a=f.l2p(e-s)+v,o=f.l2p(e+l)+v,b=h?(a+o)/2:f.l2p(e)+v,_=r.whiskerwidth,w=h?a*_+(1-_)*b:f.l2p(e-d)+v,T=h?o*_+(1-_)*b:f.l2p(e+d)+v,k=f.l2p(e-s*x)+v,A=f.l2p(e+l*x)+v,M=\"sd\"===r.sizemode,S=c.c2p(M?t.mean-t.sd:t.q1,!0),E=M?c.c2p(t.mean+t.sd,!0):c.c2p(t.q3,!0),L=i.constrain(M?c.c2p(t.mean,!0):c.c2p(t.med,!0),Math.min(S,E)+1,Math.max(S,E)-1),C=void 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n=r(49084),i=r(29736).axisHoverFormat,a=r(21776).Ks,o=r(52948),s=r(45464),l=r(92880).extendFlat,u={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},sizemode:{valType:\"enumerated\",values:[\"scaled\",\"absolute\",\"raw\"],editType:\"calc\",dflt:\"scaled\"},sizeref:{valType:\"number\",editType:\"calc\",min:0},anchor:{valType:\"enumerated\",editType:\"calc\",values:[\"tip\",\"tail\",\"cm\",\"center\"],dflt:\"cm\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"norm\"]}),uhoverformat:i(\"u\",1),vhoverformat:i(\"v\",1),whoverformat:i(\"w\",1),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),showlegend:l({},s.showlegend,{dflt:!1})};l(u,n(\"\",{colorAttr:\"u/v/w 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O=C.selectAll(\"text\").data(P);function I(e,r,n,i){if(!e.match(\"s\")||n>=0==i>=0||r(n).slice(-1).match(_)||r(i).slice(-1).match(_))return r;var a=e.slice().replace(\"s\",\"f\").replace(/\\d+/,(function(t){return parseInt(t)-1})),o=k(t,{tickformat:a});return function(t){return Math.abs(t)<1?d.tickText(o,t).text:r(t)}}O.enter().append(\"text\"),O.attr(\"text-anchor\",(function(){return A})).attr(\"class\",(function(t){return t})).attr(\"x\",null).attr(\"y\",null).attr(\"dx\",null).attr(\"dy\",null),O.exit().remove();var z,D=v.mode+v.align;if(v._hasDelta&&(z=function(){var e=k(t,{tickformat:v.delta.valueformat},v._range);e.setScale(),d.prepTicks(e);var i=function(t){return d.tickText(e,t).text},o=v.delta.suffix,s=v.delta.prefix,l=function(t){return v.delta.relative?t.relativeDelta:t.delta},u=function(t,e){return 0===t||\"number\"!=typeof t||isNaN(t)?\"-\":(t>0?v.delta.increasing.symbol:v.delta.decreasing.symbol)+s+e(t)+o},h=function(t){return 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U,V,q,H=j.select(\"path\");w(M)?(H.transition().duration(M.duration).ease(M.easing).each(\"end\",(function(){S&&S()})).each(\"interrupt\",(function(){S&&S()})).attrTween(\"d\",(U=N,V=L(r[0].lastY),q=L(r[0].y),function(){var t=i(V,q);return function(e){return U.endAngle(t(e))()}})),p._lastValue=r[0].y):H.attr(\"d\",\"number\"==typeof r[0].y?N.endAngle(L(r[0].y)):\"M0,0Z\"),H.call(T),j.exit().remove(),F=[];var G=p.gauge.threshold.value;(G||0===G)&&F.push({range:[G,G],color:p.gauge.threshold.color,line:{color:p.gauge.threshold.line.color,width:p.gauge.threshold.line.width},thickness:p.gauge.threshold.thickness});var W=_.selectAll(\"g.threshold-arc\").data(F);W.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),W.select(\"path\").call(P).call(T),W.exit().remove();var Y=_.selectAll(\"g.gauge-outline\").data([x]);Y.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),Y.select(\"path\").call(P).call(T),Y.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:W,layer:Y,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:g});var X=I.selectAll(\"g.bullet\").data(R?e:[]);X.exit().remove();var Z=I.selectAll(\"g.bulletaxis\").data(R?e:[]);Z.exit().remove(),R&&function(t,e,r,n){var i,a,o,s,u,c=r[0].trace,f=n.gauge,p=n.layer,v=n.gaugeBg,g=n.gaugeOutline,y=n.size,x=c.domain,b=n.transitionOpts,_=n.onComplete;f.enter().append(\"g\").classed(\"bullet\",!0),f.attr(\"transform\",l(y.l,y.t)),p.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),p.selectAll(\"g.xbulletaxistick,path,text\").remove();var A=y.h,M=c.gauge.bar.thickness*A,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(c._hasNumber||c._hasDelta?1-h.bulletNumberDomainSize:1);function L(t){t.attr(\"width\",(function(t){return 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O=f.selectAll(\"g.value-bullet\").data([c.gauge.bar]);O.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),O.select(\"rect\").attr(\"height\",M).attr(\"y\",(A-M)/2).call(T),w(b)?O.select(\"rect\").transition().duration(b.duration).ease(b.easing).each(\"end\",(function(){_&&_()})).each(\"interrupt\",(function(){_&&_()})).attr(\"width\",Math.max(0,i.c2p(Math.min(c.gauge.axis.range[1],r[0].y)))):O.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,i.c2p(Math.min(c.gauge.axis.range[1],r[0].y))):0),O.exit().remove();var I=r.filter((function(){return 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r=\"slices.\"+t;a(r+\".show\")&&(a(r+\".fill\"),a(r+\".locations\"))})),a(\"spaceframe.show\")&&a(\"spaceframe.fill\"),a(\"surface.show\")&&(a(\"surface.count\"),a(\"surface.fill\"),a(\"surface.pattern\")),a(\"contour.show\")&&(a(\"contour.color\"),a(\"contour.width\")),[\"text\",\"hovertext\",\"hovertemplate\",\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lighting.vertexnormalsepsilon\",\"lighting.facenormalsepsilon\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"flatshading\",\"opacity\"].forEach((function(t){a(t)})),o(t,e,n,a,{prefix:\"\",cLetter:\"c\"}),e._length=null):e.visible=!1}t.exports={supplyDefaults:function(t,e,r,i){s(t,e,0,i,(function(r,i){return n.coerce(t,e,a,r,i)}))},supplyIsoDefaults:s}},6296:function(t,e,r){\"use 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n=r(49084),i=r(29736).axisHoverFormat,a=r(21776).Ks,o=r(16716),s=r(45464),l=r(92880).extendFlat;t.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=r(67792).gl_mesh3d,i=r(67792).delaunay_triangulate,a=r(67792).alpha_shape,o=r(67792).convex_hull,s=r(33040).parseColorScale,l=r(3400).isArrayOrTypedArray,u=r(43080),c=r(8932).extractOpts,f=r(52094);function h(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var p=h.prototype;function d(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=u(t[n]);return e}function v(t,e,r,n){for(var i=[],a=e.length,o=0;o<a;o++)i[o]=t.d2l(e[o],0,n)*r;return i}function g(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function y(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}p.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return l(r)&&void 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p={positions:h,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:u(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var m=c(t);this.color=\"#fff\";var x=t.intensitymode;p[x+\"Intensity\"]=t.intensity,p[x+\"IntensityBounds\"]=[m.min,m.max],p.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],p.vertexColors=d(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],p.cellColors=d(t.facecolor)):(this.color=t.color,p.meshColor=u(t.color));this.mesh.update(p)},p.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},t.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new 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a,s=t._fullData,l=[];for(i=1/0,a=0;a<s.length;a++){var u=s[a];if(\"ohlc\"===u.type&&!0===u.visible&&u.xaxis===e._id){l.push(u);var c=e.makeCalcdata(u,\"x\");u._origX=c;var f=o(r,e,\"x\",c).vals;u._xcalc=f;var h=n.distinctVals(f).minDiff;h&&isFinite(h)&&(i=Math.min(i,h))}}for(i===1/0&&(i=1),a=0;a<l.length;a++)l[a]._minDiff=i}return i*r.tickwidth}(t,r,e),c=e._minDiff;e._minDiff=null;var f=e._origX;e._origX=null;var h=e._xcalc;e._xcalc=null;var p=u(t,e,f,h,i,l);return e._extremes[r._id]=a.findExtremes(r,h,{vpad:c/2}),p.length?(n.extendFlat(p[0].t,{wHover:c/2,tickLen:s}),p):[{t:{empty:!0}}]},calcCommon:u}},23860:function(t,e,r){\"use strict\";var n=r(3400),i=r(52744),a=r(31147),o=r(20279);function s(t,e,r,n){r(n+\".line.color\"),r(n+\".line.width\",e.line.width),r(n+\".line.dash\",e.line.dash)}t.exports=function(t,e,r,l){function u(r,i){return 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T=a.getDistanceFunction(n,b,_,w);if(a.getClosest(l,T,t),!1===t.index)return null;var k=l[t.index];if(k.empty)return null;var A=c[k.dir],M=A.line.color;return o.opacity(M)&&A.line.width?t.color=M:t.color=A.fillcolor,t.x0=u.c2p(k.pos+v-y,!0),t.x1=u.c2p(k.pos+v+y,!0),t.xLabelVal=void 0!==k.orig_p?k.orig_p:k.pos,t.spikeDistance=w(k)*s/i,t.xSpike=u.c2p(k.pos,!0),t}function f(t,e,r,a){var o=t.cd,s=t.ya,l=o[0].trace,u=o[0].t,f=[],h=c(t,e,r,a);if(!h)return[];var p=o[h.index].hi||l.hoverinfo,d=p.split(\"+\");if(\"all\"!==p&&-1===d.indexOf(\"y\"))return[];for(var v=[\"high\",\"open\",\"close\",\"low\"],g={},y=0;y<v.length;y++){var m,x=v[y],b=l[x][h.index],_=s.c2p(b,!0);b in g?(m=g[b]).yLabel+=\"<br>\"+u.labels[x]+n.hoverLabelText(s,b,l.yhoverformat):((m=i.extendFlat({},h)).y0=m.y1=_,m.yLabelVal=b,m.yLabel=u.labels[x]+n.hoverLabelText(s,b,l.yhoverformat),m.name=\"\",f.push(m),g[b]=m)}return f}function h(t,e,r,i){var a=t.cd,o=t.ya,l=a[0].trace,f=a[0].t,h=c(t,e,r,i);if(!h)return[];var 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n=r(71688).wrap,i=r(94288).hasColorscale,a=r(47128),o=r(68944),s=r(43616),l=r(3400),u=r(38248);function c(t,e,r){t.valueInds.push(e),t.count+=r}function f(t,e,r){return{categoryInds:t,color:e,rawColor:r,valueInds:[],count:0}}function h(t,e,r){t.valueInds.push(e),t.count+=r}t.exports=function(t,e){var r=l.filterVisible(e.dimensions);if(0===r.length)return[];var p,d,v,g=r.map((function(t){var e;if(\"trace\"===t.categoryorder)e=null;else if(\"array\"===t.categoryorder)e=t.categoryarray;else{e=o(t.values);for(var r=!0,n=0;n<e.length;n++)if(!u(e[n])){r=!1;break}e.sort(r?l.sorterAsc:void 0),\"category descending\"===t.categoryorder&&(e=e.reverse())}return function(t,e){e=null==e?[]:e.map((function(t){return t}));var r={},n={},i=[];e.forEach((function(t,e){r[t]=0,n[t]=e}));for(var a=0;a<t.length;a++){var o,s=t[a];void 0===r[s]?(r[s]=1,o=e.push(s)-1,n[s]=o):(r[s]++,o=n[s]),i.push(o)}var l=e.map((function(t){return 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n=r(33428),i=r(67756).Gz,a=r(36424),o=r(93024),s=r(3400),l=s.strTranslate,u=r(43616),c=r(49760),f=r(72736);function h(t,e,r,i){var a=e._context.staticPlot,o=t.map(F.bind(0,e,r)),c=i.selectAll(\"g.parcatslayer\").data([null]);c.enter().append(\"g\").attr(\"class\",\"parcatslayer\").style(\"pointer-events\",a?\"none\":\"all\");var h=c.selectAll(\"g.trace.parcats\").data(o,p),m=h.enter().append(\"g\").attr(\"class\",\"trace parcats\");h.attr(\"transform\",(function(t){return l(t.x,t.y)})),m.append(\"g\").attr(\"class\",\"paths\");var x=h.select(\"g.paths\").selectAll(\"path.path\").data((function(t){return t.paths}),p);x.attr(\"fill\",(function(t){return t.model.color}));var w=x.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",0);_(w),x.attr(\"d\",(function(t){return 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z=E.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);E.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(z),E.exit().remove(),S.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var D=e._fullLayout.paper_bgcolor;M.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(D)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){u.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),S.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){u.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),M.exit().remove(),A.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",O).on(\"dragend\",I)),h.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),h.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function v(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function 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y(t){if(!t.parcatsViewModel.dragDimension&&(_(n.select(this)),o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(v),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=m(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function m(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function x(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function b(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=m(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function _(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function w(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return c.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function T(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function k(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function A(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var 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k(t){t.on(\"mousemove\",(function(t){i.event.preventDefault(),t.parent.inBrushDrag||T(this,t)})).on(\"mouseleave\",(function(t){t.parent.inBrushDrag||m()})).call(i.behavior.drag().on(\"dragstart\",(function(t){!function(t,e){i.event.sourceEvent.stopPropagation();var r=e.height-i.mouse(t)[1]-2*n.verticalPadding,a=e.unitToPaddedPx.invert(r),o=e.brush,s=_(e,r),l=s.interval,u=o.svgBrush;if(u.wasDragged=!1,u.grabbingBar=\"ns\"===s.region,u.grabbingBar){var c=l.map(e.unitToPaddedPx);u.grabPoint=r-c[0]-n.verticalPadding,u.barLength=c[1]-c[0]}u.clickableOrdinalRange=s.clickableOrdinalRange,u.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(u.stayingIntervals=u.stayingIntervals.filter((function(t){return t[0]!==l[0]&&t[1]!==l[1]}))),u.startExtent=s.region?l[\"s\"===s.region?1:0]:a,e.parent.inBrushDrag=!0,u.brushStartCallback()}(this,t)})).on(\"drag\",(function(t){w(this,t)})).on(\"dragend\",(function(t){!function(t,e){var r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,m(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&M(r)):M(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),a.newExtent=[p(0,l,a.newExtent[0],a.stayingIntervals),p(1,l,a.newExtent[1],a.stayingIntervals)];var u=a.newExtent[1]>a.newExtent[0];a.extent=a.stayingIntervals.concat(u?[a.newExtent]:[]),a.extent.length||M(r),a.brushCallback(e),u?b(t.parentNode,s):(s(),b(t.parentNode))}else s();a.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}(this,t)})))}function A(t,e){return t[0]-e[0]}function M(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function S(t){for(var e,r=t.slice(),n=[],i=r.shift();i;){for(e=i.slice();(i=r.shift())&&i[0]<=e[1];)e[1]=Math.max(e[1],i[1]);n.push(e)}return 1===n.length&&n[0][0]>n[0][1]&&(n=[]),n}t.exports={makeBrush:function(t,e,r,n,i,a){var o,l=function(){var t,e,r=[];return{set:function(n){1===(r=n.map((function(t){return t.slice().sort(s)})).sort(A)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=S(r),e=r.reduce((function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]}),[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=i,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map((function(t){return t.slice()}))}(e),n=r.slice();e.filter.set(n),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t,e,r){var i=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);i.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t,e,r){var i=r._context.staticPlot,a=t.selectAll(\".background\").data(o);a.enter().append(\"rect\").classed(\"background\",!0).call(d).call(v).style(\"pointer-events\",i?\"none\":\"auto\").attr(\"transform\",l(0,n.verticalPadding)),a.call(k).attr(\"height\",(function(t){return t.height-n.verticalPadding}));var s=t.selectAll(\".highlight-shadow\").data(o);s.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",e).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),s.attr(\"y1\",(function(t){return t.height})).call(x);var u=t.selectAll(\".highlight\").data(o);u.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),u.attr(\"y1\",(function(t){return t.height})).call(x)}(i,e,r)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(A)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},61664:function(t,e,r){\"use strict\";t.exports={attributes:r(82296),supplyDefaults:r(60664),calc:r(95044),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:r(19976),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},19976:function(t,e,r){\"use strict\";var n=r(33428),i=r(84888)._M,a=r(24196),o=r(9616);e.name=\"parcoords\",e.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},e.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},e.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this,r=t.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":r,preserveAspectRatio:\"none\",x:0,y:0,width:t.style.width,height:t.style.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},95044:function(t,e,r){\"use strict\";var n=r(3400).isArrayOrTypedArray,i=r(8932),a=r(71688).wrap;t.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},30140:function(t){\"use strict\";t.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:[\"contextLineLayer\",\"focusLineLayer\",\"pickLineLayer\"],axisTitleOffset:28,axisExtentOffset:10,bar:{width:4,captureWidth:10,fillColor:\"magenta\",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:\"axis-extent-text\",parcoordsLineLayers:\"parcoords-line-layers\",parcoordsLineLayer:\"parcoords-lines\",parcoords:\"parcoords\",parcoordsControlView:\"parcoords-control-view\",yAxis:\"y-axis\",axisOverlays:\"axis-overlays\",axis:\"axis\",axisHeading:\"axis-heading\",axisTitle:\"axis-title\",axisExtent:\"axis-extent\",axisExtentTop:\"axis-extent-top\",axisExtentTopText:\"axis-extent-top-text\",axisExtentBottom:\"axis-extent-bottom\",axisExtentBottomText:\"axis-extent-bottom-text\",axisBrush:\"axis-brush\"},id:{filterBarPattern:\"filter-bar-pattern\"}}},60664:function(t,e,r){\"use strict\";var n=r(3400),i=r(94288).hasColorscale,a=r(27260),o=r(86968).Q,s=r(51272),l=r(54460),u=r(82296),c=r(71864),f=r(30140).maxDimensionCount,h=r(26284);function p(t,e,r,i){function a(r,i){return n.coerce(t,e,u.dimensions,r,i)}var o=a(\"values\"),s=a(\"visible\");if(o&&o.length||(s=e.visible=!1),s){a(\"label\"),a(\"tickvals\"),a(\"ticktext\"),a(\"tickformat\");var f=a(\"range\");e._ax={_id:\"y\",type:\"linear\",showexponent:\"all\",exponentformat:\"B\",range:f},l.setConvert(e._ax,i.layout),a(\"multiselect\");var h=a(\"constraintrange\");h&&(e.constraintrange=c.cleanRanges(h,e))}}t.exports=function(t,e,r,l){function c(r,i){return n.coerce(t,e,u,r,i)}var d=t.dimensions;Array.isArray(d)&&d.length>f&&(n.log(\"parcoords traces support up to \"+f+\" dimensions at the moment\"),d.splice(f));var v=s(t,e,{name:\"dimensions\",layout:l,handleItemDefaults:p}),g=function(t,e,r,o,s){var l=s(\"line.color\",r);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,c);o(e,l,c),Array.isArray(v)&&v.length||(e.visible=!1),h(e,v,\"values\",g);var y={weight:l.font.weight,style:l.font.style,variant:l.font.variant,family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(c,\"labelfont\",y),n.coerceFont(c,\"tickfont\",y),n.coerceFont(c,\"rangefont\",y),c(\"labelangle\"),c(\"labelside\"),c(\"unselected.line.color\"),c(\"unselected.line.opacity\")}},95724:function(t,e,r){\"use strict\";var n=r(3400).isTypedArray;e.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},e.isOrdinal=function(t){return!!t.tickvals},e.isVisible=function(t){return t.visible||!(\"visible\"in t)}},29928:function(t,e,r){\"use strict\";var n=r(61664);n.plot=r(24196),t.exports=n},51352:function(t,e,r){\"use strict\";var n=[\"precision highp float;\",\"\",\"varying vec4 fragColor;\",\"\",\"attribute vec4 p01_04, p05_08, p09_12, p13_16,\",\"               p17_20, p21_24, p25_28, p29_32,\",\"               p33_36, p37_40, p41_44, p45_48,\",\"               p49_52, p53_56, p57_60, colors;\",\"\",\"uniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\",\"             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\",\"\",\"uniform vec2 resolution, viewBoxPos, viewBoxSize;\",\"uniform float maskHeight;\",\"uniform float drwLayer; // 0: context, 1: focus, 2: pick\",\"uniform vec4 contextColor;\",\"uniform sampler2D maskTexture, palette;\",\"\",\"bool isPick    = (drwLayer > 1.5);\",\"bool isContext = (drwLayer < 0.5);\",\"\",\"const vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\",\"const vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\",\"\",\"float val(mat4 p, mat4 v) {\",\"    return dot(matrixCompMult(p, v) * UNITS, UNITS);\",\"}\",\"\",\"float axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\",\"    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\",\"    return y1 * (1.0 - ratio) + y2 * ratio;\",\"}\",\"\",\"int iMod(int a, int b) {\",\"    return a - b * (a / b);\",\"}\",\"\",\"bool fOutside(float p, float lo, float hi) {\",\"    return (lo < hi) && (lo > p || p > hi);\",\"}\",\"\",\"bool vOutside(vec4 p, vec4 lo, vec4 hi) {\",\"    return (\",\"        fOutside(p[0], lo[0], hi[0]) ||\",\"        fOutside(p[1], lo[1], hi[1]) ||\",\"        fOutside(p[2], lo[2], hi[2]) ||\",\"        fOutside(p[3], lo[3], hi[3])\",\"    );\",\"}\",\"\",\"bool mOutside(mat4 p, mat4 lo, mat4 hi) {\",\"    return (\",\"        vOutside(p[0], lo[0], hi[0]) ||\",\"        vOutside(p[1], lo[1], hi[1]) ||\",\"        vOutside(p[2], lo[2], hi[2]) ||\",\"        vOutside(p[3], lo[3], hi[3])\",\"    );\",\"}\",\"\",\"bool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    return mOutside(A, loA, hiA) ||\",\"           mOutside(B, loB, hiB) ||\",\"           mOutside(C, loC, hiC) ||\",\"           mOutside(D, loD, hiD);\",\"}\",\"\",\"bool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    mat4 pnts[4];\",\"    pnts[0] = A;\",\"    pnts[1] = B;\",\"    pnts[2] = C;\",\"    pnts[3] = D;\",\"\",\"    for(int i = 0; i < 4; ++i) {\",\"        for(int j = 0; j < 4; ++j) {\",\"            for(int k = 0; k < 4; ++k) {\",\"                if(0 == iMod(\",\"                    int(255.0 * texture2D(maskTexture,\",\"                        vec2(\",\"                            (float(i * 2 + j / 2) + 0.5) / 8.0,\",\"                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\",\"                        ))[3]\",\"                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\",\"                    2\",\"                )) return true;\",\"            }\",\"        }\",\"    }\",\"    return false;\",\"}\",\"\",\"vec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    float x = 0.5 * sign(v) + 0.5;\",\"    float y = axisY(x, A, B, C, D);\",\"    float z = 1.0 - abs(v);\",\"\",\"    z += isContext ? 0.0 : 2.0 * float(\",\"        outsideBoundingBox(A, B, C, D) ||\",\"        outsideRasterMask(A, B, C, D)\",\"    );\",\"\",\"    return vec4(\",\"        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\",\"        z,\",\"        1.0\",\"    );\",\"}\",\"\",\"void main() {\",\"    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\",\"    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\",\"    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\",\"    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\",\"\",\"    float v = colors[3];\",\"\",\"    gl_Position = position(isContext, v, A, B, C, D);\",\"\",\"    fragColor =\",\"        isContext ? vec4(contextColor) :\",\"        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\",\"}\"].join(\"\\n\"),i=[\"precision highp float;\",\"\",\"varying vec4 fragColor;\",\"\",\"void main() {\",\"    gl_FragColor = fragColor;\",\"}\"].join(\"\\n\"),a=r(30140).maxDimensionCount,o=r(3400),s=1e-6,l=new Uint8Array(4),u=new Uint8Array(4),c={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var u=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*u,a.offset=2*l*n,e(a),l*n+u<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function v(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,u=r[64*a+l];63===l&&0===o&&(u*=-1),n[i++]=u}return n}function g(t){var e=\"0\"+t;return e.substr(e.length-2)}function y(t){return t<a?\"p\"+g(t+1)+\"_\"+g(t+4):\"colors\"}function m(t,e,r,n,i,a,s,l,u,c,f,h,p,d){for(var v=[[],[]],g=0;g<64;g++)v[0][g]=g===i?1:0,v[1][g]=g===a?1:0;s*=d,l*=d,u*=d,c*=d;var y=t.lines.canvasOverdrag*d,m=t.domain,x=t.canvasWidth*d,b=t.canvasHeight*d,_=t.pad.l*d,w=t.pad.b*d,T=t.layoutHeight*d,k=t.layoutWidth*d,A=t.deselectedLines.color,M=t.deselectedLines.opacity;return o.extendFlat({key:f,resolution:[x,b],viewBoxPos:[s+y,l],viewBoxSize:[u,c],i0:i,i1:a,dim0A:v[0].slice(0,16),dim0B:v[0].slice(16,32),dim0C:v[0].slice(32,48),dim0D:v[0].slice(48,64),dim1A:v[1].slice(0,16),dim1B:v[1].slice(16,32),dim1C:v[1].slice(32,48),dim1D:v[1].slice(48,64),drwLayer:h,contextColor:[A[0]/255,A[1]/255,A[2]/255,\"auto\"!==M?A[3]*M:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:s+y)+(_-y)+k*m.x[0],scissorWidth:(n===r?x-s+y:u+.5)+(n===e?s+y:0),scissorY:l+w+T*m.y[0],scissorHeight:c,viewportX:_-y+k*m.x[0],viewportY:w+T*m.y[0],viewportWidth:x,viewportHeight:b},p)}function x(t){var e=2047,r=Math.max(0,Math.floor(t[0]*e),0),n=Math.min(e,Math.ceil(t[1]*e),e);return[Math.min(r,n),Math.max(r,n)]}t.exports=function(t,e){var r,l,g,b,_,w=e.context,T=e.pick,k=e.regl,A=k._gl,M=A.getParameter(A.ALIASED_LINE_WIDTH_RANGE),S=Math.max(M[0],Math.min(M[1],e.viewModel.plotGlPixelRatio)),E={currentRafs:{},drawCompleted:!0,clearOnly:!1},L=function(t){for(var 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a=u[e][n],o=i.map((function(t){return t.slice()})),s=\"dimensions[\"+n+\"].constraintrange\",l=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===l[s]){var h=a.constraintrange;l[s]=h||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),a.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete a.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[f[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return s(t,e,r)-s(t,e,n)}}(r,u[e].filter(a));l[e].sort(n),u[e].filter((function(t){return!a(t)})).sort((function(t){return u[e].indexOf(t)})).forEach((function(t){l[e].splice(l[e].indexOf(t),1),l[e].splice(u[e].indexOf(t),0,t)})),t.emit(\"plotly_restyle\",[{dimensions:[l[e]]},[f[e]]])}})}}).reglPrecompiled=o},74996:function(t,e,r){\"use strict\";var n=r(45464),i=r(86968).u,a=r(25376),o=r(22548),s=r(21776).Ks,l=r(21776).Gw,u=r(92880).extendFlat,c=r(98192).c,f=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});t.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},pattern:c,editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:u({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:u({},f,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:u({},f,{}),outsidetextfont:u({},f,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:u({},f,{}),position:{valType:\"enumerated\",values:[\"top 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n=r(7316);e.name=\"pie\",e.plot=function(t,r,i,a){n.plotBasePlot(e.name,t,r,i,a)},e.clean=function(t,r,i,a){n.cleanBasePlot(e.name,t,r,i,a)}},45768:function(t,e,r){\"use strict\";var n=r(38248),i=r(49760),a=r(76308),o={};function s(t){return function(e,r){return!!e&&!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e)}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r<t.length;r++)a.push(i(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)a.push(i(t[r]).darken(20).toHexString());e[n]=a}return a}t.exports={calc:function(t,e){var r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],u=e.labels,c=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(u=new Array(h),r=0;r<h;r++)u[r]=String(e.label0+r*e.dlabel);var d={},v=s(o[\"_\"+e.type+\"colormap\"]),g=0,y=!1;for(r=0;r<h;r++){var m,x,b;if(p){if(m=f[r],!n(m))continue;m=+m}else m=1;void 0!==(x=u[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(g+=m),a.push({v:m,label:x,color:v(c[r],x),i:r,pts:[r],hidden:b})):(y=!0,(i=a[_]).v+=m,i.pts.push(r),i.hidden||(g+=m),!1===i.color&&c[r]&&(i.color=v(c[r],x)))}return a=a.filter((function(t){return t.v>=0})),(\"funnelarea\"===e.type?y:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var u=0,c=0;c<i.length;c++){var f=i[c];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[u%a.length],u++))}}},makePullColorFn:s,generateExtendedColors:l}},74174:function(t,e,r){\"use strict\";var n=r(38248),i=r(3400),a=r(74996),o=r(86968).Q,s=r(31508).handleText,l=r(3400).coercePattern;function u(t,e){var r=i.isArrayOrTypedArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var u=e[l];if(n(u)&&u>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}function c(t,e,r,n,i){n(\"marker.line.width\")&&n(\"marker.line.color\",i?void 0:r.paper_bgcolor);var a=n(\"marker.colors\");l(n,\"marker.pattern\",a),t.marker&&!e.marker.pattern.fgcolor&&(e.marker.pattern.fgcolor=t.marker.colors),e.marker.pattern.bgcolor||(e.marker.pattern.bgcolor=r.paper_bgcolor)}t.exports={handleLabelsAndValues:u,handleMarkerDefaults:c,supplyDefaults:function(t,e,r,n){function l(r,n){return i.coerce(t,e,a,r,n)}var f=u(l(\"labels\"),l(\"values\")),h=f.len;if(e._hasLabels=f.hasLabels,e._hasValues=f.hasValues,!e._hasLabels&&e._hasValues&&(l(\"label0\"),l(\"dlabel\")),h){e._length=h,c(t,e,n,l,!0),l(\"scalegroup\");var p,d=l(\"text\"),v=l(\"texttemplate\");if(v||(p=l(\"textinfo\",i.isArrayOrTypedArray(d)?\"text+percent\":\"percent\")),l(\"hovertext\"),l(\"hovertemplate\"),v||p&&\"none\"!==p){var g=l(\"textposition\");s(t,e,n,l,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&l(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&l(\"insidetextorientation\")}else\"none\"===p&&l(\"textposition\",\"none\");o(e,n,l);var y=l(\"hole\");if(l(\"title.text\")){var m=l(\"title.position\",y?\"middle center\":\"top center\");y||\"middle center\"!==m||(e.title.position=\"top center\"),i.coerceFont(l,\"title.font\",n.font)}l(\"sort\"),l(\"direction\"),l(\"rotation\"),l(\"pull\")}else e.visible=!1}}},53644:function(t,e,r){\"use strict\";var n=r(10624).appendArrayMultiPointValues;t.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},21552:function(t,e,r){\"use strict\";var n=r(43616),i=r(76308);t.exports=function(t,e,r,a){var o=r.marker.pattern;o&&o.shape?n.pointStyle(t,r,a,e):i.fill(t,e.color)}},69656:function(t,e,r){\"use strict\";var n=r(3400);function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}e.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},e.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},e.getFirstFilled=function(t,e){if(n.isArrayOrTypedArray(t))for(var r=0;r<e.length;r++){var i=t[e[r]];if(i||0===i||\"\"===i)return i}},e.castOption=function(t,r){return n.isArrayOrTypedArray(t)?e.getFirstFilled(t,r):t||void 0},e.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},75792:function(t,e,r){\"use strict\";t.exports={attributes:r(74996),supplyDefaults:r(74174).supplyDefaults,supplyLayoutDefaults:r(90248),layoutAttributes:r(85204),calc:r(45768).calc,crossTraceCalc:r(45768).crossTraceCalc,plot:r(37820).plot,style:r(22152),styleOne:r(10528),moduleType:\"trace\",name:\"pie\",basePlotModule:r(80036),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},85204:function(t){\"use strict\";t.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},90248:function(t,e,r){\"use strict\";var n=r(3400),i=r(85204);t.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},37820:function(t,e,r){\"use strict\";var n=r(33428),i=r(7316),a=r(93024),o=r(76308),s=r(43616),l=r(3400),u=l.strScale,c=l.strTranslate,f=r(72736),h=r(82744),p=h.recordMinTextSize,d=h.clearMinTextSize,v=r(78048).TEXTPAD,g=r(69656),y=r(53644),m=r(3400).isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,u=i.trace,c=\"funnelarea\"===u.type;\"_hasHoverLabel\"in u||(u._hasHoverLabel=!1),\"_hasHoverEvent\"in u||(u._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,f=e._fullData[u.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[g.castOption(h,t.pts)],_module:u._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),f.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),v=s+t.pxmid[1]*(1-p),m=r.separators,x=[];if(h&&-1!==h.indexOf(\"label\")&&x.push(t.label),t.text=g.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf(\"text\")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=g.formatPieValue(t.v,m),h&&-1!==h.indexOf(\"value\")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=g.formatPiePercent(t.percent,m),h&&-1!==h.indexOf(\"percent\")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:u,x0:d-p*i.r,x1:d+p*i.r,y:v,_x0:c?o+t.TL[0]:d-p*i.r,_x1:c?o+t.TR[0]:d+p*i.r,_y0:c?s+t.TL[1]:v-p*i.r,_y1:c?s+t.BL[1]:v+p*i.r,text:x.join(\"<br>\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[y(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],u._hasHoverLabel=!0}u._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[y(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[u.index],o=n.select(this).datum();u._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[y(o,i)],event:n.event}),u._hasHoverEvent=!1),u._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),u._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[u.index];e._dragging||!1===r.hovermode||(e._hoverdata=[y(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size,s=g.castOption(t.insidetextfont.weight,e.pts)||g.castOption(t.textfont.weight,e.pts)||r.weight,l=g.castOption(t.insidetextfont.style,e.pts)||g.castOption(t.textfont.style,e.pts)||r.style,u=g.castOption(t.insidetextfont.variant,e.pts)||g.castOption(t.textfont.variant,e.pts)||r.variant;return{color:n||o.contrast(e.color),family:i,size:a,weight:s,style:l,variant:u}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var 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m=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/m,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;v.push(a)}(d||p)&&((a=T(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a)),(d||h)&&((a=k(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a));for(var x=0,b=0,_=0;_<v.length;_++){var w=v[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return v[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=O(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,u=t.r/(void 0===(l=t.trace.aspectratio)?1:l),c=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(c+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?c*=2:-1!==a.title.position.indexOf(\"right\")&&(c+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=c/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function O(t){var e,r=t.pull;if(!r)return 0;if(l.isArrayOrTypedArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function I(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var u=s/2,c=l/2;\"funnelarea\"!==a.type||a.scalegroup||(c/=a.aspectratio),i.r=Math.min(u,c)/(1+O(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var u,c;i.aspectratio>1?c=(u=r.r)/i.aspectratio:u=(c=r.r)*i.aspectratio,l=(u*=(1+i.baseratio)/2)*c}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function z(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,u=o.split(\"+\"),c=function(t){return-1!==u.indexOf(t)},f=c(\"label\"),h=c(\"text\"),p=c(\"value\"),d=c(\"percent\"),v=n.separators;if(s=f?[e.label]:[],h){var y=g.getFirstFilled(i.text,e.pts);m(y)&&s.push(y)}p&&s.push(g.formatPieValue(e.v,v)),d&&s.push(g.formatPiePercent(e.v/r.vTotal,v)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(m(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}t.exports={plot:function(t,e){var r=t._context.staticPlot,a=t._fullLayout,h=a._size;d(\"pie\",a),_(e,t),I(e,h);var v=l.makeTraceGroups(a._pielayer,e,\"trace\").each((function(e){var d=n.select(this),v=e[0],y=v.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,u=\"px0\",c=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,u=\"px1\",c=\"px0\"}for(n=z(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[u]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=z(a,s),r.midangle=s,n=z(a,s+=l*r.v/2),r.stopangle=s,r[c]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),d.attr(\"stroke-linejoin\",\"round\"),d.each((function(){var m=n.select(this).selectAll(\"g.slice\").data(e);m.enter().append(\"g\").classed(\"slice\",!0),m.exit().remove();var _=[[[],[]],[[],[]]],T=!1;m.each((function(i,o){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=y.index,_[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var u=v.cx,c=v.cy,h=n.select(this),d=h.selectAll(\"path.surface\").data([i]);if(d.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":r?\"none\":\"all\"}),h.call(x,t,e),y.pull){var m=+g.castOption(y.pull,i.pts)||0;m>0&&(u+=m*i.pxmid[0],c+=m*i.pxmid[1])}i.cxFinal=u,i.cyFinal=c;var k=y.hole;if(i.v===v.vTotal){var A=\"M\"+(u+i.px0[0])+\",\"+(c+i.px0[1])+P(i.px0,i.pxmid,!0,1)+P(i.pxmid,i.px0,!0,1)+\"Z\";k?d.attr(\"d\",\"M\"+(u+k*i.px0[0])+\",\"+(c+k*i.px0[1])+P(i.px0,i.pxmid,!1,k)+P(i.pxmid,i.px0,!1,k)+\"Z\"+A):d.attr(\"d\",A)}else{var M=P(i.px0,i.px1,!0,1);if(k){var S=1-k;d.attr(\"d\",\"M\"+(u+k*i.px1[0])+\",\"+(c+k*i.px1[1])+P(i.px1,i.px0,!1,k)+\"l\"+S*i.px0[0]+\",\"+S*i.px0[1]+M+\"Z\")}else d.attr(\"d\",\"M\"+u+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}D(t,i,v);var E=g.castOption(y.textposition,i.pts),C=h.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==E?[0]:[]);C.enter().append(\"g\").classed(\"slicetext\",!0),C.exit().remove(),C.each((function(){var r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===E?function(t,e,r){return{color:g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,family:g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,size:g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size,weight:g.castOption(t.outsidetextfont.weight,e.pts)||g.castOption(t.textfont.weight,e.pts)||r.weight,style:g.castOption(t.outsidetextfont.style,e.pts)||g.castOption(t.textfont.style,e.pts)||r.style,variant:g.castOption(t.outsidetextfont.variant,e.pts)||g.castOption(t.textfont.variant,e.pts)||r.variant}}(y,i,a.font):b(y,i,a.font));r.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var d,m=s.bBox(r.node());if(\"outside\"===E)d=L(m,i);else if(d=w(m,i,v),\"auto\"===E&&d.scale<1){var x=l.ensureUniformFontSize(t,y.outsidetextfont);r.call(s.font,x),d=L(m=s.bBox(r.node()),i)}var _=d.textPosAngle,k=void 0===_?i.pxmid:z(v.r,_);if(d.targetX=u+k[0]*d.rCenter+(d.x||0),d.targetY=c+k[1]*d.rCenter+(d.y||0),R(d,m),d.outside){var A=d.targetY;i.yLabelMin=A-m.height/2,i.yLabelMid=A,i.yLabelMax=A+m.height/2,i.labelExtraX=0,i.labelExtraY=0,T=!0}d.fontSize=h.size,p(y.type,d,a),e[o].transform=d,l.setTransormAndDisplay(r,d)}))}function P(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*v.r+\",\"+n*v.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var k=n.select(this).selectAll(\"g.titletext\").data(y.title.text?[0]:[]);if(k.enter().append(\"g\").classed(\"titletext\",!0),k.exit().remove(),k.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=y.title.text;y._meta&&(i=l.templateString(i,y._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,y.title.font).call(f.convertToTspans,t),e=\"middle center\"===y.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(v):C(v,h),r.attr(\"transform\",c(e.x,e.y)+u(Math.min(1,e.scale))+c(e.tx,e.ty))})),T&&function(t,e){var r,n,i,a,o,s,u,c,f,h,p,d,v;function y(t,e){return t.pxmid[1]-e.pxmid[1]}function m(t,e){return e.pxmid[1]-t.pxmid[1]}function x(t,r){r||(r={});var i,c,f,p,d=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),v=n?t.yLabelMin:t.yLabelMax,y=n?t.yLabelMax:t.yLabelMin,m=t.cyFinal+o(t.px0[1],t.px1[1]),x=d-v;if(x*u>0&&(t.labelExtraY=x),l.isArrayOrTypedArray(e.pull))for(c=0;c<h.length;c++)(f=h[c])===t||(g.castOption(e.pull,t.pts)||0)>=(g.castOption(e.pull,f.pts)||0)||((t.pxmid[1]-f.pxmid[1])*u>0?(x=f.cyFinal+o(f.px0[1],f.px1[1])-v-t.labelExtraY)*u>0&&(t.labelExtraY+=x):(y+t.labelExtraY-m)*u>0&&(i=3*s*Math.abs(c-h.indexOf(t)),(p=f.cxFinal+a(f.px0[0],f.px1[0])+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=p)))}for(n=0;n<2;n++)for(i=n?y:m,o=n?Math.max:Math.min,u=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(c=t[n][r]).sort(i),f=t[1-n][r],h=f.concat(c),d=[],p=0;p<c.length;p++)void 0!==c[p].yLabelMid&&d.push(c[p]);for(v=!1,p=0;n&&p<f.length;p++)if(void 0!==f[p].yLabelMid){v=f[p];break}for(p=0;p<d.length;p++){var b=p&&d[p-1];v&&!p&&(b=v),x(d[p],b)}}}(_,y),function(t,e){t.each((function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var i=r.select(\"g.slicetext text\");t.transform.targetX+=t.labelExtraX,t.transform.targetY+=t.labelExtraY,l.setTransormAndDisplay(i,t.transform);var a=t.cxFinal+t.pxmid[0],s=\"M\"+a+\",\"+(t.cyFinal+t.pxmid[1]),u=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var c=t.labelExtraX*t.pxmid[1]/t.pxmid[0],f=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(c)>Math.abs(f)?s+=\"l\"+f*t.pxmid[0]/t.pxmid[1]+\",\"+f+\"H\"+(a+t.labelExtraX+u):s+=\"l\"+t.labelExtraX+\",\"+c+\"v\"+(f-c)+\"h\"+u}else s+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+u;l.ensureSingle(r,\"path\",\"textline\").call(o.stroke,e.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,e.outsidetextfont.size/8),d:s,fill:\"none\"})}else r.select(\"path.textline\").remove()}))}(m,y),T&&y.automargin){var A=s.bBox(d.node()),M=y.domain,S=h.w*(M.x[1]-M.x[0]),E=h.h*(M.y[1]-M.y[0]),P=(.5*S-v.r)/h.w,O=(.5*E-v.r)/h.h;i.autoMargin(t,\"pie.\"+y.uid+\".automargin\",{xl:M.x[0]-P,xr:M.x[1]+P,yb:M.y[0]-O,yt:M.y[1]+O,l:Math.max(v.cx-v.r-A.left,0),r:Math.max(A.right-(v.cx+v.r),0),b:Math.max(A.bottom-(v.cy+v.r),0),t:Math.max(v.cy-v.r-A.top,0),pad:5})}}))}));setTimeout((function(){v.selectAll(\"tspan\").each((function(){var t=n.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))}))}),0)},formatSliceLabel:D,transformInsideText:w,determineInsideTextFont:b,positionTitleOutside:C,prerenderTitles:_,layoutAreas:I,attachFxHandlers:x,computeTransform:R}},22152:function(t,e,r){\"use strict\";var n=r(33428),i=r(10528),a=r(82744).resizeText;t.exports=function(t){var e=t._fullLayout._pielayer.selectAll(\".trace\");a(t,e,\"pie\"),e.each((function(e){var r=e[0].trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\"path.surface\").each((function(e){n.select(this).call(i,e,r,t)}))}))}},10528:function(t,e,r){\"use strict\";var n=r(76308),i=r(69656).castOption,a=r(21552);t.exports=function(t,e,r,o){var s=r.marker.line,l=i(s.color,e.pts)||n.defaultLine,u=i(s.width,e.pts)||0;t.call(a,e,r,o).style(\"stroke-width\",u).call(n.stroke,l)}},35484:function(t,e,r){\"use strict\";var n=r(52904);t.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},11072:function(t,e,r){\"use strict\";var n=r(67792).gl_pointcloud2d,i=r(3400).isArrayOrTypedArray,a=r(43080),o=r(19280).findExtremes,s=r(44928);function l(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var u=l.prototype;u.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:i(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},u.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=s(t,{})},u.updateFast=function(t){var e,r,n,i,s,l,u=this.xData=this.pickXData=t.x,c=this.yData=this.pickYData=t.y,f=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(f){if(n=f,e=f.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)i=n[2*l],s=n[2*l+1],i<d[0]&&(d[0]=i),i>d[2]&&(d[2]=i),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=u.length,n=new Float32Array(2*e),r=new 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a=r.node;a.originalEvent=n.event,t._hoverdata=[a],n.select(e).call(m,r,i),s.click(t,{target:!0})}}})}},83248:function(t,e,r){\"use strict\";var n=r(49812),i=r(67756).Gz,a=r(33428),o=r(26800),s=r(48932),l=r(11820),u=r(49760),c=r(76308),f=r(43616),h=r(3400),p=h.strTranslate,d=h.strRotate,v=r(71688),g=v.keyFun,y=v.repeat,m=v.unwrap,x=r(72736),b=r(24040),_=r(84284),w=_.CAP_SHIFT,T=_.LINE_SPACING;function k(t,e,r){var n,i=m(e),a=i.trace,c=a.domain,f=\"h\"===a.orientation,p=a.node.pad,d=a.node.thickness,v={justify:o.sankeyJustify,left:o.sankeyLeft,right:o.sankeyRight,center:o.sankeyCenter}[a.node.align],g=t.width*(c.x[1]-c.x[0]),y=t.height*(c.y[1]-c.y[0]),x=i._nodes,b=i._links,_=i.circular;(n=_?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[g,y]:[y,g]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodeAlign(v).nodes(x).links(b);var w,T,k,A=n();for(var M in n.nodePadding()<p&&h.warn(\"node.pad was reduced to 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l=0;for(T=0;T<r.sourceLinks.length;T++)l+=r.sourceLinks[T].value;for(T=0;T<r.sourceLinks.length;T++)(e=r.sourceLinks[T]).concentrationOut=e.value/l;var c=0;for(T=0;T<r.targetLinks.length;T++)c+=r.targetLinks[T].value;for(T=0;T<r.targetLinks.length;T++)(e=r.targetLinks[T]).concenrationIn=e.value/c}}(),a.node.x.length&&a.node.y.length){for(w=0;w<Math.min(a.node.x.length,a.node.y.length,A.nodes.length);w++)if(a.node.x[w]&&a.node.y[w]){var C=[a.node.x[w]*g,a.node.y[w]*y];A.nodes[w].x0=C[0]-d/2,A.nodes[w].x1=C[0]+d/2;var P=A.nodes[w].y1-A.nodes[w].y0;A.nodes[w].y0=C[1]-P/2,A.nodes[w].y1=C[1]+P/2}\"snap\"===a.arrangement&&function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(w=0;w<n.length;w++){var s=t[n[w].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return i}(x=A.nodes).forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return 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e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:a,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:c.tinyRGB(n),tinyColorAlpha:n.getAlpha(),tinyColorHoverHue:c.tinyRGB(i),tinyColorHoverAlpha:i.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,linkArrowLength:t.linkArrowLength,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){var e=t.linkArrowLength;if(t.link.circular)return function(t,e){var r=t.width/2,n=t.circularPathData;return\"top\"===t.circularLinkType?\"M \"+(n.targetX-e)+\" \"+(n.targetY+r)+\" L\"+(n.rightInnerExtent-e)+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r-e)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r-e)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 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\"+(n.sourceY+n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r-e)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r-e)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+(n.rightInnerExtent-e)+\" \"+(n.targetY+r)+\"L\"+(n.targetX-e)+\" \"+(n.targetY+r)+(e>0?\"L\"+n.targetX+\" \"+n.targetY:\"\")+\"Z\"}(t.link,e);var r=Math.abs((t.link.target.x0-t.link.source.x1)/2);e>r&&(e=r);var n=t.link.source.x1,a=t.link.target.x0-e,o=i(n,a),s=o(.5),l=o(.5),u=t.link.y0-t.link.width/2,c=t.link.y0+t.link.width/2,f=t.link.y1-t.link.width/2,h=t.link.y1+t.link.width/2,p=\"M\"+n+\",\"+u,d=\"C\"+s+\",\"+u+\" \"+l+\",\"+f+\" \"+a+\",\"+f,v=\"C\"+l+\",\"+h+\" \"+s+\",\"+c+\" \"+n+\",\"+c,g=e>0?\"L\"+(a+e)+\",\"+(f+t.link.width/2):\"\";return p+d+(g+=\"L\"+a+\",\"+h)+v+\"Z\"}}function S(t,e){var r=u(e.color),n=l.nodePadAcross,i=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var a=e.dx,o=Math.max(.5,e.dy),s=\"node_\"+e.pointNumber;return e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:c.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join(\"_\"),interactionState:t.interactionState,figure:t}}function E(t){t.attr(\"transform\",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function C(t,e){t.call(L),e.attr(\"d\",M())}function P(t){t.attr(\"width\",(function(t){return t.node.x1-t.node.x0})).attr(\"height\",(function(t){return t.visibleHeight}))}function O(t){return t.link.width>1||t.linkLineWidth>0}function I(t){return p(t.translateX,t.translateY)+(t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\")}function z(t,e,r){t.on(\".basic\",null).on(\"mouseover.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.hover(this,t,e),t.interactionState.hovered=[this,t])})).on(\"mousemove.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.follow(this,t),t.interactionState.hovered=[this,t])})).on(\"mouseout.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.unhover(this,t,e),t.interactionState.hovered=!1)})).on(\"click.basic\",(function(t){t.interactionState.hovered&&(r.unhover(this,t,e),t.interactionState.hovered=!1),t.interactionState.dragInProgress||t.partOfGroup||r.select(this,t,e)}))}function D(t,e,r,i){var o=a.behavior.drag().origin((function(t){return{x:t.node.x0+t.visibleWidth/2,y:t.node.y0+t.visibleHeight/2}})).on(\"dragstart\",(function(a){if(\"fixed\"!==a.arrangement&&(h.ensureSingle(i._fullLayout._infolayer,\"g\",\"dragcover\",(function(t){i._fullLayout._dragCover=t})),h.raiseToTop(this),a.interactionState.dragInProgress=a.node,F(a.node),a.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,a.interactionState.hovered),a.interactionState.hovered=!1),\"snap\"===a.arrangement)){var o=a.traceId+\"|\"+a.key;a.forceLayouts[o]?a.forceLayouts[o].alpha(1):function(t,e,r,i){!function(t){for(var e=0;e<t.length;e++)t[e].y=(t[e].y0+t[e].y1)/2,t[e].x=(t[e].x0+t[e].x1)/2}(r.graph.nodes);var a=r.graph.nodes.filter((function(t){return t.originalX===r.node.originalX})).filter((function(t){return!t.partOfGroup}));r.forceLayouts[e]=n.forceSimulation(a).alphaDecay(0).force(\"collide\",n.forceCollide().radius((function(t){return t.dy/2+r.nodePad/2})).strength(1).iterations(l.forceIterations)).force(\"constrain\",function(t,e,r,n){return function(){for(var t=0,i=0;i<r.length;i++){var a=r[i];a===n.interactionState.dragInProgress?(a.x=a.lastDraggedX,a.y=a.lastDraggedY):(a.vx=(a.originalX-a.x)/l.forceTicksPerFrame,a.y=Math.min(n.size-a.dy/2,Math.max(a.dy/2,a.y))),t=Math.max(t,Math.abs(a.vx),Math.abs(a.vy))}!n.interactionState.dragInProgress&&t<.1&&n.forceLayouts[e].alpha()>0&&n.forceLayouts[e].alpha(0)}}(0,e,a,r)).stop()}(0,o,a),function(t,e,r,n,i){window.requestAnimationFrame((function a(){var o;for(o=0;o<l.forceTicksPerFrame;o++)r.forceLayouts[n].tick();if(function(t){for(var e=0;e<t.length;e++)t[e].y0=t[e].y-t[e].dy/2,t[e].y1=t[e].y0+t[e].dy,t[e].x0=t[e].x-t[e].dx/2,t[e].x1=t[e].x0+t[e].dx}(r.graph.nodes),r.sankey.update(r.graph),C(t.filter(B(r)),e),r.forceLayouts[n].alpha()>0)window.requestAnimationFrame(a);else{var 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a=(t.graph.nodes[i].x0+t.graph.nodes[i].x1)/2,o=(t.graph.nodes[i].y0+t.graph.nodes[i].y1)/2;r.push(a/t.figure.width),n.push(o/t.figure.height)}b.call(\"_guiRestyle\",e,{\"node.x\":[r],\"node.y\":[n]},t.trace.index).then((function(){e._fullLayout._dragCover&&e._fullLayout._dragCover.remove()}))}function F(t){t.lastDraggedX=t.x0+t.dx/2,t.lastDraggedY=t.y0+t.dy/2}function B(t){return function(e){return e.node.originalX===t.node.originalX}}t.exports=function(t,e,r,n,i){var o=t._context.staticPlot,s=!1;h.ensureSingle(t._fullLayout._infolayer,\"g\",\"first-render\",(function(){s=!0}));var v=t._fullLayout._dragCover,b=r.filter((function(t){return m(t).trace.visible})).map(k.bind(null,n)),_=e.selectAll(\".\"+l.cn.sankey).data(b,g);_.exit().remove(),_.enter().append(\"g\").classed(l.cn.sankey,!0).style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"shape-rendering\",\"geometricPrecision\").style(\"pointer-events\",o?\"none\":\"auto\").attr(\"transform\",I),_.each((function(e,r){t._fullData[r]._sankey=e;var n=\"bgsankey-\"+e.trace.uid+\"-\"+r;h.ensureSingle(t._fullLayout._draggers,\"rect\",n),t._fullData[r]._bgRect=a.select(\".\"+n),t._fullData[r]._bgRect.style(\"pointer-events\",o?\"none\":\"all\").attr(\"width\",e.width).attr(\"height\",e.height).attr(\"x\",e.translateX).attr(\"y\",e.translateY).classed(\"bgsankey\",!0).style({fill:\"transparent\",\"stroke-width\":0})})),_.transition().ease(l.ease).duration(l.duration).attr(\"transform\",I);var L=_.selectAll(\".\"+l.cn.sankeyLinks).data(y,g);L.enter().append(\"g\").classed(l.cn.sankeyLinks,!0).style(\"fill\",\"none\");var 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n=r(21776).Ks,i=r(21776).Gw,a=r(98304),o=r(52904),s=r(45464),l=r(49084),u=r(98192).u,c=r(92880).extendFlat,f=r(67824).overrideAll,h=o.marker,p=o.line,d=h.line;t.exports=f({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n,i,a=r.length,o=a/2;if(h.hasLines(e)&&o)if(\"hv\"===e.line.shape){for(n=[],i=0;i<o-1;i++)isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN,NaN,NaN):(n.push(r[2*i],r[2*i+1]),isNaN(r[2*i+2])||isNaN(r[2*i+3])?n.push(NaN,NaN):n.push(r[2*i+2],r[2*i+1]));n.push(r[a-2],r[a-1])}else if(\"hvh\"===e.line.shape){for(n=[],i=0;i<o-1;i++)if(isNaN(r[2*i])||isNaN(r[2*i+1])||isNaN(r[2*i+2])||isNaN(r[2*i+3]))isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN):n.push(r[2*i],r[2*i+1]),n.push(NaN,NaN);else{var s=(r[2*i]+r[2*i+2])/2;n.push(r[2*i],r[2*i+1],s,r[2*i+1],s,r[2*i+3])}n.push(r[a-2],r[a-1])}else if(\"vhv\"===e.line.shape){for(n=[],i=0;i<o-1;i++)if(isNaN(r[2*i])||isNaN(r[2*i+1])||isNaN(r[2*i+2])||isNaN(r[2*i+3]))isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN):n.push(r[2*i],r[2*i+1]),n.push(NaN,NaN);else{var l=(r[2*i+1]+r[2*i+3])/2;n.push(r[2*i],r[2*i+1],r[2*i],l,r[2*i+2],l)}n.push(r[a-2],r[a-1])}else if(\"vh\"===e.line.shape){for(n=[],i=0;i<o-1;i++)isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN,NaN,NaN):(n.push(r[2*i],r[2*i+1]),isNaN(r[2*i+2])||isNaN(r[2*i+3])?n.push(NaN,NaN):n.push(r[2*i],r[2*i+3]));n.push(r[a-2],r[a-1])}else n=r;var u=!1;for(i=0;i<n.length;i++)if(isNaN(n[i])){u=!0;break}var c=u||n.length>v.TOO_MANY_POINTS||h.hasMarkers(e)?\"rect\":\"round\";if(u&&e.connectgaps){var f=n[0],p=n[1];for(i=0;i<n.length;i+=2)isNaN(n[i])||isNaN(n[i+1])?(n[i]=f,n[i+1]=p):(f=n[i],p=n[i+1])}return{join:c,positions:n}},errorBarPositions:function(t,e,r,i,a){var s=o.getComponentMethod(\"errorbars\",\"makeComputeError\"),l=c.getFromId(t,e.xaxis,\"x\"),u=c.getFromId(t,e.yaxis,\"y\"),f=r.length/2,h={};function p(t,i){var a=i._id.charAt(0),o=e[\"error_\"+a];if(o&&o.visible&&(\"linear\"===i.type||\"log\"===i.type)){for(var l=s(o),u={x:0,y:1}[a],c={x:[0,1,2,3],y:[2,3,0,1]}[a],p=new Float64Array(4*f),d=1/0,v=-1/0,g=0,y=0;g<f;g++,y+=4){var m=t[g];if(n(m)){var x=r[2*g+u],b=l(m,g),_=b[0],w=b[1];if(n(_)&&n(w)){var T=m-_,k=m+w;p[y+c[0]]=x-i.c2l(T),p[y+c[1]]=i.c2l(k)-x,p[y+c[2]]=0,p[y+c[3]]=0,d=Math.min(d,m-_),v=Math.max(v,m+w)}}}h[a]={positions:r,errors:p,_bnds:[d,v]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(h.hasMarkers(e)){var s=r.font,u=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var f=n.sizes?n.sizes[i]:n.size,p=l(s)?s[i].size:s.size,d=l(u)?u.length>1?u[i]:u[0]:u,v=l(c)?c.length>1?c[i]:c[0]:c,g=y[d],m=y[v],x=f?f/.8+1:0,b=-m*x-.5*m;o.offset[i]=[g*x/p,b/p]}}return o}}},80220:function(t,e,r){\"use strict\";var n=r(3400),i=r(24040),a=r(80088),o=r(2876),s=r(88200),l=r(43028),u=r(43980),c=r(31147),f=r(74428),h=r(66828),p=r(70840),d=r(124);t.exports=function(t,e,r,v){function g(r,i){return n.coerce(t,e,o,r,i)}var y=!!t.marker&&a.isOpenSymbol(t.marker.symbol),m=l.isBubble(t),x=u(t,e,v,g);if(x){c(t,e,v,g),g(\"xhoverformat\"),g(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";g(\"text\"),g(\"hovertext\"),g(\"hovertemplate\"),g(\"mode\",b),l.hasMarkers(e)&&(f(t,e,r,v,g,{noAngleRef:!0,noStandOff:!0}),g(\"marker.line.width\",y||m?1:0)),l.hasLines(e)&&(g(\"connectgaps\"),h(t,e,r,v,g),g(\"line.shape\")),l.hasText(e)&&(g(\"texttemplate\"),d(t,e,v,g));var _=(e.line||{}).color,w=(e.marker||{}).color;g(\"fill\"),\"none\"!==e.fill&&p(t,e,r,g);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,g)}else e.visible=!1}},26768:function(t,e,r){\"use strict\";var n=r(3400),i=r(76308),a=r(13448).DESELECTDIM;t.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,u=l._scene,c=l.index,f=u.selectBatch[c],h=u.unselectBatch[c],p=u.textOptions[c],d=u.textSelectedOptions[c]||{},v=u.textUnselectedOptions[c]||{},g=n.extendFlat({},p);if(f.length||h.length){var y=d.color,m=v.color,x=p.color,b=n.isArrayOrTypedArray(x);for(g.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],g.color[r]=y||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;g.color[r]=m||(y?_:i.addOpacity(_,a))}}u.glText[c].update(g)}}},99396:function(t,e,r){\"use strict\";var n=r(76688);t.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},80088:function(t,e,r){\"use strict\";var n=r(67072);e.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},e.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},41272:function(t,e,r){\"use strict\";var n=r(24040),i=r(3400),a=r(44928);function o(t,e,r,o){var s=t.xa,l=t.ya,u=t.distance,c=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=i.isArrayOrTypedArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=i.isArrayOrTypedArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family,h.tw=Array.isArray(p.weight)?p.weight[f]:p.weight,h.ty=Array.isArray(p.style)?p.style[f]:p.style,h.tv=Array.isArray(p.variant)?p.variant[f]:p.variant);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.ma=i.isArrayOrTypedArray(d.angle)?d.angle[f]:d.angle,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var v=d&&d.line;v&&(h.mlc=Array.isArray(v.color)?v.color[f]:v.color,h.mlw=i.isArrayOrTypedArray(v.width)?v.width[f]:v.width);var g=d&&d.gradient;g&&\"none\"!==g.type&&(h.mgt=Array.isArray(g.type)?g.type[f]:g.type,h.mgc=Array.isArray(g.color)?g.color[f]:g.color);var y=s.c2p(h.x,!0),m=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,A=o._origY,M=i.extendFlat({},t,{color:a(o,h),x0:y-x,x1:y+x,xLabelVal:k?k[f]:h.x,y0:m-x,y1:m+x,yLabelVal:A?A[f]:h.y,cd:T,distance:u,spikeDistance:c,hovertemplate:h.ht});return h.htx?M.text=h.htx:h.tx?M.text=h.tx:o.text&&(M.text=o.text),i.fillText(h,o,M),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,M),M}t.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,u,c,f,h,p,d,v=t.cd,g=v[0].t,y=v[0].trace,m=t.xa,x=t.ya,b=g.x,_=g.y,w=m.c2p(e),T=x.c2p(r),k=t.distance;if(g.tree){var A=m.p2c(w-k),M=m.p2c(w+k),S=x.p2c(T-k),E=x.p2c(T+k);i=\"x\"===n?g.tree.range(Math.min(A,M),Math.min(x._rl[0],x._rl[1]),Math.max(A,M),Math.max(x._rl[0],x._rl[1])):g.tree.range(Math.min(A,M),Math.min(S,E),Math.max(A,M),Math.max(S,E))}else i=g.ids;var L=k;if(\"x\"===n){var C=!!y.xperiodalignment,P=!!y.yperiodalignment;for(c=0;c<i.length;c++){if(l=b[a=i[c]],f=Math.abs(m.c2p(l)-w),C){var O=m.c2p(y._xStarts[a]),I=m.c2p(y._xEnds[a]);f=w>=Math.min(O,I)&&w<=Math.max(O,I)?0:1/0}if(f<L){if(L=f,u=_[a],h=x.c2p(u)-T,P){var z=x.c2p(y._yStarts[a]),D=x.c2p(y._yEnds[a]);h=T>=Math.min(z,D)&&T<=Math.max(z,D)?0:1/0}d=Math.sqrt(f*f+h*h),s=i[c]}}}else for(c=i.length-1;c>-1;c--)l=b[a=i[c]],u=_[a],f=m.c2p(l)-w,h=x.c2p(u)-T,(p=Math.sqrt(f*f+h*h))<L&&(L=d=p,s=a);return t.index=s,t.distance=L,t.dxy=d,void 0===s?[t]:[o(t,b,_,y)]},calcHover:o}},38983:function(t,e,r){\"use strict\";var n=r(64628);n.plot=r(89876),t.exports=n},89876:function(t,e,r){\"use strict\";var n=r(38540),i=r(13472),a=r(24544),o=r(23352),s=r(3400),l=r(72760).selectMode,u=r(5048),c=r(43028),f=r(14328),h=r(26768).styleTextSelection,p={};function d(t,e,r,n){var i=t._size,a=t.width*n,o=t.height*n,s=i.l*n,l=i.b*n,u=i.r*n,c=i.t*n,f=i.w*n,h=i.h*n;return[s+e.domain[0]*f,l+r.domain[0]*h,a-u-(1-e.domain[1])*f,o-c-(1-r.domain[1])*h]}(t.exports=function(t,e,r){if(r.length){var v,g,y=t._fullLayout,m=e._scene,x=e.xaxis,b=e.yaxis;if(m)if(u(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"],p)){var _=m.count,w=y._glcanvas.data()[0].regl;if(f(t,e,r),m.dirty){if(!m.line2d&&!m.error2d||m.scatter2d||m.fill2d||m.glText||w.clear({}),!0===m.error2d&&(m.error2d=a(w)),!0===m.line2d&&(m.line2d=i(w)),!0===m.scatter2d&&(m.scatter2d=n(w)),!0===m.fill2d&&(m.fill2d=i(w)),!0===m.glText)for(m.glText=new Array(_),v=0;v<_;v++)m.glText[v]=new o(w);if(m.glText){if(_>m.glText.length){var T=_-m.glText.length;for(v=0;v<T;v++)m.glText.push(new o(w))}else if(_<m.glText.length){var k=m.glText.length-_;m.glText.splice(_,k).forEach((function(t){t.destroy()}))}for(v=0;v<_;v++)m.glText[v].update(m.textOptions[v])}if(m.line2d&&(m.line2d.update(m.lineOptions),m.lineOptions=m.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),m.line2d.update(m.lineOptions)),m.error2d){var A=(m.errorXOptions||[]).concat(m.errorYOptions||[]);m.error2d.update(A)}m.scatter2d&&m.scatter2d.update(m.markerOptions),m.fillOrder=s.repeat(null,_),m.fill2d&&(m.fillOptions=m.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,u=m.lineOptions[e],c=[];s._ownfill&&c.push(e),s._nexttrace&&c.push(e+1),c.length&&(m.fillOrder[e]=c);var f,h,p=[],d=u&&u.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,t.splitNull=!0,a=0;a<d.length;a+=2)(isNaN(d[a])||isNaN(d[a+1]))&&((p=p.concat(d.slice(i,a))).push(d[i],d[i+1]),p.push(null,null),i=a+2);p=p.concat(d.slice(i)),i&&p.push(d[i],d[i+1])}else{var v=s._nexttrace;if(v){var g=m.lineOptions[e+1];if(g){var y=g.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=v.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=m.lineOptions[e-1].positions,w=p.length/2,T=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(T.push(a/2+w+1),i=a+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),m.fill2d.update(m.fillOptions))}var M=y.dragmode,S=l(M),E=y.clickmode.indexOf(\"select\")>-1;for(v=0;v<_;v++){var L=r[v][0],C=L.trace,P=L.t,O=P.index,I=C._length,z=P.x,D=P.y;if(C.selectedpoints||S||E){if(S||(S=!0),C.selectedpoints){var R=m.selectBatch[O]=s.selIndices2selPoints(C),F={};for(g=0;g<R.length;g++)F[R[g]]=1;var B=[];for(g=0;g<I;g++)F[g]||B.push(g);m.unselectBatch[O]=B}var N=P.xpx=new Array(I),j=P.ypx=new Array(I);for(g=0;g<I;g++)N[g]=x.c2p(z[g]),j[g]=b.c2p(D[g])}else P.xpx=P.ypx=null}if(S){if(m.select2d||(m.select2d=n(y._glcanvas.data()[1].regl)),m.scatter2d){var U=new Array(_);for(v=0;v<_;v++)U[v]=m.selectBatch[v].length||m.unselectBatch[v].length?m.markerUnselectedOptions[v]:{};m.scatter2d.update(U)}m.select2d&&(m.select2d.update(m.markerOptions),m.select2d.update(m.markerSelectedOptions)),m.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};c.hasText(e)&&h(t)}))}else m.scatter2d&&m.scatter2d.update(m.markerOptions);var V={viewport:d(y,x,b,t._context.plotGlPixelRatio),range:[(x._rl||x.range)[0],(b._rl||b.range)[0],(x._rl||x.range)[1],(b._rl||b.range)[1]]},q=s.repeat(V,m.count);m.fill2d&&m.fill2d.update(q),m.line2d&&m.line2d.update(q),m.error2d&&m.error2d.update(q.concat(q)),m.scatter2d&&m.scatter2d.update(q),m.select2d&&m.select2d.update(q),m.glText&&m.glText.forEach((function(t){t.update(V)}))}else m.init()}}).reglPrecompiled=p},74588:function(t,e,r){\"use strict\";var n=r(3400);t.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,u=r.selectBatch,c=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(c[f].length){var h=n.repeat([],r.count);h[f]=c[f],o.draw(h)}else 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n=r(49084),i=r(29736).axisHoverFormat,a=r(21776).Ks,o=r(52948),s=r(45464),l=r(92880).extendFlat,u={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},starts:{x:{valType:\"data_array\",editType:\"calc\"},y:{valType:\"data_array\",editType:\"calc\"},z:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"},maxdisplayed:{valType:\"integer\",min:0,dflt:1e3,editType:\"calc\"},sizeref:{valType:\"number\",editType:\"calc\",min:0,dflt:1},text:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"tubex\",\"tubey\",\"tubez\",\"tubeu\",\"tubev\",\"tubew\",\"norm\",\"divergence\"]}),uhoverformat:i(\"u\",1),vhoverformat:i(\"v\",1),whoverformat:i(\"w\",1),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),showlegend:l({},s.showlegend,{dflt:!1})};l(u,n(\"\",{colorAttr:\"u/v/w 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L=function(){m=0,M=[],S=[],E=[]};(!m||m<M.length*S.length*E.length)&&L();var C=function(t){return\"x\"===t?v:\"y\"===t?g:y},P=function(t){return\"x\"===t?M:\"y\"===t?S:E},O=function(t){return t[m-1]<t[0]?-1:1},I=C(A[1]),z=C(A[3]),D=C(A[5]),R=P(A[1]).length,F=P(A[3]).length,B=P(A[5]).length,N=!1,j=function(t,e,r){return R*(F*t+e)+r},U=O(C(A[1])),V=O(C(A[3])),q=O(C(A[5]));for(e=0;e<B-1;e++){for(r=0;r<F-1;r++){for(i=0;i<R-1;i++){var H=j(e,r,i),G=j(e,r,i+1),W=j(e,r+1,i),Y=j(e+1,r,i);if(I[H]*U<I[G]*U&&z[H]*V<z[W]*V&&D[H]*q<D[Y]*q||(N=!0),N)break}if(N)break}if(N)break}return N&&(n.warn(\"Encountered arbitrary coordinates! 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y=n[c];r.xMax=Math.max(r.xMax,y),r.xMin=Math.min(r.xMin,y);var m=o[c];r.yMax=Math.max(r.yMax,m),r.yMin=Math.min(r.yMin,m);var x=l[c];r.zMax=Math.max(r.zMax,x),r.zMin=Math.min(r.zMin,x)}e._slen=u,e._normMax=f,e._xbnds=[r.xMin,r.xMax],e._ybnds=[r.yMin,r.yMax],e._zbnds=[r.zMin,r.zMax]},filter:s,processGrid:a}},25668:function(t,e,r){\"use strict\";var n=r(67792).gl_streamtube3d,i=n.createTubeMesh,a=r(3400),o=r(33040).parseColorScale,s=r(8932).extractOpts,l=r(52094),u={xaxis:0,yaxis:1,zaxis:2};function c(t,e){this.scene=t,this.uid=e,this.mesh=null,this.data=null}var f=c.prototype;function h(t){var e=t.length;return e>2?t.slice(1,e-1):2===e?[(t[0]+t[1])/2]:t}function p(t){var e=t.length;return 1===e?[.5,.5]:[t[1]-t[0],t[e-1]-t[e-2]]}function d(t,e){var r=t.fullSceneLayout,i=t.dataScale,c=e._len,f={};function d(t,e){var n=r[e],o=i[u[e]];return a.simpleMap(t,(function(t){return 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n=r(45464),i=r(21776).Ks,a=r(21776).Gw,o=r(49084),s=r(86968).u,l=r(74996),u=r(27328),c=r(92880).extendFlat,f=r(98192).c;t.exports={labels:{valType:\"data_array\",editType:\"calc\"},parents:{valType:\"data_array\",editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},branchvalues:{valType:\"enumerated\",values:[\"remainder\",\"total\"],dflt:\"remainder\",editType:\"calc\"},count:{valType:\"flaglist\",flags:[\"branches\",\"leaves\"],dflt:\"leaves\",editType:\"calc\"},level:{valType:\"any\",editType:\"plot\",anim:!0},maxdepth:{valType:\"integer\",editType:\"plot\",dflt:-1},marker:c({colors:{valType:\"data_array\",editType:\"calc\"},line:{color:c({},l.marker.line.color,{dflt:null}),width:c({},l.marker.line.width,{dflt:1}),editType:\"calc\"},pattern:f,editType:\"calc\"},o(\"marker\",{colorAttr:\"colors\",anim:!1})),leaf:{opacity:{valType:\"number\",editType:\"style\",min:0,max:1},editType:\"plot\"},text:l.text,textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"current 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u=n.select(this),f=s.ensureSingle(u,\"path\",\"surface\",(function(t){t.style(\"pointer-events\",h?\"none\":\"all\")}));i.rpx0=H(i.y0),i.rpx1=H(i.y1),i.xmid=(i.x0+i.x1)/2,i.pxmid=G(i.rpx1,i.xmid),i.midangle=-(i.xmid-Math.PI/2),i.startangle=-(i.x0-Math.PI/2),i.stopangle=-(i.x1-Math.PI/2),i.halfangle=.5*Math.min(s.angleDelta(i.x0,i.x1)||Math.PI,Math.PI),i.ring=1-i.rpx0/i.rpx1,i.rInscribed=function(t){return 0===t.rpx0&&s.isFullCircle([t.x0,t.x1])?1:Math.max(0,Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2))}(i),_?f.transition().attrTween(\"d\",(function(t){var e=function(t){var e,r=F[b.getPtId(t)],n={x0:t.x0,x1:t.x1,rpx0:t.rpx0,rpx1:t.rpx1};if(r)e=r;else if(R)if(t.parent)if(Z){var i=(t.x1>Z?2*Math.PI:0)+V;e={x0:i,x1:i}}else e={rpx0:I,rpx1:I},s.extendFlat(e,$(t));else e={rpx0:0,rpx1:0};else e={x0:V,x1:V};return a(e,n)}(t);return function(t){return W(e(t))}})):f.attr(\"d\",W),u.call(m,S,t,r,{eventDataKeys:x.eventDataKeys,transitionTime:x.CLICK_TRANSITION_TIME,transitionEasing:x.CLICK_TRANSITION_EASING}).call(b.setSliceCursor,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:t._transitioning}),f.call(g,i,A,t);var p=s.ensureSingle(u,\"g\",\"slicetext\"),w=s.ensureSingle(p,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),T=s.ensureUniformFontSize(t,b.determineTextFont(A,i,y.font));w.text(e.formatSliceLabel(i,S,A,r,y)).classed(\"slicetext\",!0).attr(\"text-anchor\",\"middle\").call(o.font,T).call(l.convertToTspans,t);var M=o.bBox(w.node());i.transform=v(M,i,k),i.transform.targetX=Y(i),i.transform.targetY=X(i);var E=function(t,e){var r=t.transform;return d(r,e),r.fontSize=T.size,c(A.type,r,y),s.getTextTransform(r)};_?w.transition().attrTween(\"transform\",(function(t){var e=function(t){var e,r=F[b.getPtId(t)],n=t.transform;if(r)e=r;else if(e={rpx1:t.rpx1,transform:{textPosAngle:n.textPosAngle,scale:0,rotate:n.rotate,rCenter:n.rCenter,x:n.x,y:n.y}},R)if(t.parent)if(Z){var i=t.x1>Z?2*Math.PI:0;e.x0=e.x1=i}else s.extendFlat(e,$(t));else e.x0=e.x1=V;else e.x0=e.x1=V;var o=a(e.transform.textPosAngle,t.transform.textPosAngle),l=a(e.rpx1,t.rpx1),u=a(e.x0,t.x0),f=a(e.x1,t.x1),h=a(e.transform.scale,n.scale),p=a(e.transform.rotate,n.rotate),d=0===n.rCenter?3:0===e.transform.rCenter?1/3:1,v=a(e.transform.rCenter,n.rCenter);return function(t){var e=l(t),r=u(t),i=f(t),a=function(t){return v(Math.pow(t,d))}(t),s={pxmid:G(e,(r+i)/2),rpx1:e,transform:{textPosAngle:o(t),rCenter:a,x:n.x,y:n.y}};return c(A.type,n,y),{transform:{targetX:Y(s),targetY:X(s),scale:h(t),rotate:p(t),rCenter:a}}}}(t);return function(t){return E(e(t),M)}})):w.attr(\"transform\",E(i,M))}))}function w(t){return e=t.rpx1,r=t.transform.textPosAngle,[e*Math.sin(r),-e*Math.cos(r)];var e,r}e.plot=function(t,e,r,i){var a,o,s=t._fullLayout,l=s._sunburstlayer,u=!r,c=!s.uniformtext.mode&&b.hasTransition(r);f(\"sunburst\",s),(a=l.selectAll(\"g.trace.sunburst\").data(e,(function(t){return t[0].trace.uid}))).enter().append(\"g\").classed(\"trace\",!0).classed(\"sunburst\",!0).attr(\"stroke-linejoin\",\"round\"),a.order(),c?(i&&(o=i()),n.transition().duration(r.duration).ease(r.easing).each(\"end\",(function(){o&&o()})).each(\"interrupt\",(function(){o&&o()})).each((function(){l.selectAll(\"g.trace\").each((function(e){_(t,e,this,r)}))}))):(a.each((function(e){_(t,e,this,r)})),s.uniformtext.mode&&y(t,s._sunburstlayer.selectAll(\".trace\"),\"sunburst\")),u&&a.exit().remove()},e.formatSliceLabel=function(t,e,r,n,i){var a=r.texttemplate,o=r.textinfo;if(!(a||o&&\"none\"!==o))return\"\";var l=i.separators,u=n[0],c=t.data.data,f=u.hierarchy,h=b.isHierarchyRoot(t),p=b.getParent(f,t),d=b.getValue(t);if(!a){var v,g=o.split(\"+\"),y=function(t){return-1!==g.indexOf(t)},m=[];if(y(\"label\")&&c.label&&m.push(c.label),c.hasOwnProperty(\"v\")&&y(\"value\")&&m.push(b.formatValue(c.v,l)),!h){y(\"current path\")&&m.push(b.getPath(t.data));var x=0;y(\"percent parent\")&&x++,y(\"percent entry\")&&x++,y(\"percent root\")&&x++;var _=x>1;if(x){var w,T=function(t){v=b.formatPercent(w,l),_&&(v+=\" of \"+t),m.push(v)};y(\"percent parent\")&&!h&&(w=d/b.getValue(p),T(\"parent\")),y(\"percent entry\")&&(w=d/b.getValue(e),T(\"entry\")),y(\"percent root\")&&(w=d/b.getValue(f),T(\"root\"))}}return y(\"text\")&&(v=s.castOption(r,c.i,\"text\"),s.isValidTextValue(v)&&m.push(v)),m.join(\"<br>\")}var k=s.castOption(r,c.i,\"texttemplate\");if(!k)return\"\";var A={};c.label&&(A.label=c.label),c.hasOwnProperty(\"v\")&&(A.value=c.v,A.valueLabel=b.formatValue(c.v,l)),A.currentPath=b.getPath(t.data),h||(A.percentParent=d/b.getValue(p),A.percentParentLabel=b.formatPercent(A.percentParent,l),A.parent=b.getPtLabel(p)),A.percentEntry=d/b.getValue(e),A.percentEntryLabel=b.formatPercent(A.percentEntry,l),A.entry=b.getPtLabel(e),A.percentRoot=d/b.getValue(f),A.percentRootLabel=b.formatPercent(A.percentRoot,l),A.root=b.getPtLabel(f),c.hasOwnProperty(\"color\")&&(A.color=c.color);var M=s.castOption(r,c.i,\"text\");return(s.isValidTextValue(M)||\"\"===M)&&(A.text=M),A.customdata=s.castOption(r,c.i,\"customdata\"),s.texttemplateString(k,A,i._d3locale,A,r._meta||{})}},85676:function(t,e,r){\"use strict\";var n=r(33428),i=r(76308),a=r(3400),o=r(82744).resizeText,s=r(60404);function l(t,e,r,n){var o=e.data.data,l=!e.children,u=o.i,c=a.castOption(r,u,\"marker.line.color\")||i.defaultLine,f=a.castOption(r,u,\"marker.line.width\")||0;t.call(s,e,r,n).style(\"stroke-width\",f).call(i.stroke,c).style(\"opacity\",l?r.leaf.opacity:null)}t.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each((function(e){var r=n.select(this),i=e[0].trace;r.style(\"opacity\",i.opacity),r.selectAll(\"path.surface\").each((function(e){n.select(this).call(l,e,i,t)}))}))},styleOne:l}},16716:function(t,e,r){\"use strict\";var n=r(76308),i=r(49084),a=r(29736).axisHoverFormat,o=r(21776).Ks,s=r(45464),l=r(92880).extendFlat,u=r(67824).overrideAll;function c(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var f=t.exports=u(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:c(),y:c(),z:c()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},_deprecated:{zauto:l({},i.zauto,{}),zmin:l({},i.zmin,{}),zmax:l({},i.zmax,{})},hoverinfo:l({},s.hoverinfo),showlegend:l({},s.showlegend,{dflt:!1})}),\"calc\",\"nested\");f.x.editType=f.y.editType=f.z.editType=\"calc+clearAxisTypes\",f.transforms=void 0},56576:function(t,e,r){\"use strict\";var n=r(47128);t.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},79164:function(t,e,r){\"use strict\";var n=r(67792).gl_surface3d,i=r(67792).ndarray,a=r(67792).ndarray_linear_interpolate.d2,o=r(70448),s=r(11240),l=r(3400).isArrayOrTypedArray,u=r(33040).parseColorScale,c=r(43080),f=r(8932).extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){null!=t.dataCoordinate[a]&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var o=this.data.hovertext||this.data.text;return l(o)&&o[i]&&void 0!==o[i][n]?t.textLabel=o[i][n]:t.textLabel=o||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function v(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function g(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(v(t,n))}return e}function y(t){for(var e=g(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function m(t,e){if(!(t<1||e<1)){for(var r=g(t),n=g(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var u=0;u<s;u++)r(i,[l,u],n),t.set(l,u,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=m(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=y(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,u=1+a+1,c=i(new Float32Array(l*u),[l,u]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(c,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,c,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=u(t),v=l.dataScale,g=t.z[0].length,y=t._ylength,m=l.contourLevels;this.data=t;var 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A=[!0,!0,!0],M=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=m[e],p.highlightColor[e]=w.contourColor[e]=c(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=c(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,\"lighting\"in 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m=\"contours.\"+y[c],x=h(m+\".show\"),b=h(m+\".highlight\");if(x||b)for(f=0;f<3;++f)h(m+\".project.\"+y[f]);x&&(h(m+\".color\"),h(m+\".width\"),h(m+\".usecolormap\")),b&&(h(m+\".highlightcolor\"),h(m+\".highlightwidth\")),h(m+\".start\"),h(m+\".end\"),h(m+\".size\")}g||(l(t,\"zmin\",\"cmin\"),l(t,\"zmax\",\"cmax\"),l(t,\"zauto\",\"cauto\")),a(t,e,u,h,{prefix:\"\",cLetter:\"c\"}),s(0,e,0,h),e._length=null}},opacityscaleDefaults:s}},91304:function(t,e,r){\"use strict\";t.exports={attributes:r(16716),supplyDefaults:r(60192).supplyDefaults,colorbar:{min:\"cmin\",max:\"cmax\"},calc:r(56576),plot:r(79164),moduleType:\"trace\",name:\"surface\",basePlotModule:r(12536),categories:[\"gl3d\",\"2dMap\",\"showLegend\"],meta:{}}},60520:function(t,e,r){\"use strict\";var n=r(13916),i=r(92880).extendFlat,a=r(67824).overrideAll,o=r(25376),s=r(86968).u,l=r(29736).descriptionOnlyNumbers;(t.exports=a({domain:s({name:\"table\",trace:!0}),columnwidth:{valType:\"number\",arrayOk:!0,dflt:null},columnorder:{valType:\"data_array\"},header:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[],description:l(\"cell value\")},prefix:{valType:\"string\",arrayOk:!0,dflt:null},suffix:{valType:\"string\",arrayOk:!0,dflt:null},height:{valType:\"number\",dflt:28},align:i({},n.align,{arrayOk:!0}),line:{width:{valType:\"number\",arrayOk:!0,dflt:1},color:{valType:\"color\",arrayOk:!0,dflt:\"grey\"}},fill:{color:{valType:\"color\",arrayOk:!0,dflt:\"white\"}},font:i({},o({arrayOk:!0}))},cells:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[],description:l(\"cell 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\",cn:{table:\"table\",tableControlView:\"table-control-view\",scrollBackground:\"scroll-background\",yColumn:\"y-column\",columnBlock:\"column-block\",scrollAreaClip:\"scroll-area-clip\",scrollAreaClipRect:\"scroll-area-clip-rect\",columnBoundary:\"column-boundary\",columnBoundaryClippath:\"column-boundary-clippath\",columnBoundaryRect:\"column-boundary-rect\",columnCells:\"column-cells\",columnCell:\"column-cell\",cellRect:\"cell-rect\",cellText:\"cell-text\",cellTextHolder:\"cell-text-holder\",scrollbarKit:\"scrollbar-kit\",scrollbar:\"scrollbar\",scrollbarSlider:\"scrollbar-slider\",scrollbarGlyph:\"scrollbar-glyph\",scrollbarCaptureZone:\"scrollbar-capture-zone\"}}},55992:function(t,e,r){\"use strict\";var n=r(23536),i=r(92880).extendFlat,a=r(38248),o=r(38116).isTypedArray,s=r(38116).isArrayOrTypedArray;function l(t){if(s(t)){for(var e=0,r=0;r<t.length;r++)e=Math.max(e,l(t[r]));return e}return t}function u(t,e){return t+e}function c(t){var e,r=t.slice(),n=1/0,i=0;for(e=0;e<r.length;e++)o(r[e])?r[e]=Array.from(r[e]):s(r[e])||(r[e]=[r[e]]),n=Math.min(n,r[e].length),i=Math.max(i,r[e].length);if(n!==i)for(e=0;e<r.length;e++){var a=i-r[e].length;a&&(r[e]=r[e].concat(f(a)))}return r}function f(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=\"\";return e}function h(t){return t.calcdata.columns.reduce((function(e,r){return r.xIndex<t.xIndex?e+r.columnWidth:e}),0)}function p(t,e){return Object.keys(t).map((function(r){return i({},t[r],{auxiliaryBlocks:e})}))}function d(t,e){for(var r,n={},i=0,a=0,o={firstRowIndex:null,lastRowIndex:null,rows:[]},s=0,l=0,u=0;u<t.length;u++)r=t[u],o.rows.push({rowIndex:u,rowHeight:r}),((a+=r)>=e||u===t.length-1)&&(n[i]=o,o.key=l++,o.firstRowIndex=s,o.lastRowIndex=u,o={firstRowIndex:null,lastRowIndex:null,rows:[]},i+=a,s=u+1,a=0);return n}t.exports=function(t,e){var r=c(e.cells.values),o=function(t){return 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32-Math.clz32(t)}:a.prototype._countBits=function(t){var e=t,r=0;return e>=4096&&(r+=13,e>>>=13),e>=64&&(r+=7,e>>>=7),e>=8&&(r+=4,e>>>=4),e>=2&&(r+=2,e>>>=2),r+e},a.prototype._zeroBits=function(t){if(0===t)return 26;var e=t,r=0;return 0==(8191&e)&&(r+=13,e>>>=13),0==(127&e)&&(r+=7,e>>>=7),0==(15&e)&&(r+=4,e>>>=4),0==(3&e)&&(r+=2,e>>>=2),0==(1&e)&&r++,r},a.prototype.bitLength=function(){var t=this.words[this.length-1],e=this._countBits(t);return 26*(this.length-1)+e},a.prototype.zeroBits=function(){if(this.isZero())return 0;for(var t=0,e=0;e<this.length;e++){var r=this._zeroBits(this.words[e]);if(t+=r,26!==r)break}return t},a.prototype.byteLength=function(){return Math.ceil(this.bitLength()/8)},a.prototype.toTwos=function(t){return 0!==this.negative?this.abs().inotn(t).iaddn(1):this.clone()},a.prototype.fromTwos=function(t){return this.testn(t-1)?this.notn(t).iaddn(1).ineg():this.clone()},a.prototype.isNeg=function(){return 0!==this.negative},a.prototype.neg=function(){return this.clone().ineg()},a.prototype.ineg=function(){return this.isZero()||(this.negative^=1),this},a.prototype.iuor=function(t){for(;this.length<t.length;)this.words[this.length++]=0;for(var e=0;e<t.length;e++)this.words[e]=this.words[e]|t.words[e];return this.strip()},a.prototype.ior=function(t){return n(0==(this.negative|t.negative)),this.iuor(t)},a.prototype.or=function(t){return this.length>t.length?this.clone().ior(t):t.clone().ior(this)},a.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},a.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},a.prototype.iand=function(t){return n(0==(this.negative|t.negative)),this.iuand(t)},a.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},a.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},a.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},a.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},a.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i<e;i++)this.words[i]=67108863&~this.words[i];return r>0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var d=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,u=0,c=0|o[0],f=8191&c,h=c>>>13,p=0|o[1],d=8191&p,v=p>>>13,g=0|o[2],y=8191&g,m=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,W=0|s[2],Y=8191&W,X=W>>>13,Z=0|s[3],K=8191&Z,J=Z>>>13,$=0|s[4],Q=8191&$,tt=$>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ft=8191&ct,ht=ct>>>13,pt=0|s[9],dt=8191&pt,vt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;u=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(v,U)|0,a=Math.imul(v,V);var yt=(u+(n=n+Math.imul(f,H)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,H)|0))<<13)|0;u=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(y,U),i=(i=Math.imul(y,V))+Math.imul(m,U)|0,a=Math.imul(m,V),n=n+Math.imul(d,H)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(v,H)|0,a=a+Math.imul(v,G)|0;var mt=(u+(n=n+Math.imul(f,Y)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,Y)|0))<<13)|0;u=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(y,H)|0,i=(i=i+Math.imul(y,G)|0)+Math.imul(m,H)|0,a=a+Math.imul(m,G)|0,n=n+Math.imul(d,Y)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(v,Y)|0,a=a+Math.imul(v,X)|0;var xt=(u+(n=n+Math.imul(f,K)|0)|0)+((8191&(i=(i=i+Math.imul(f,J)|0)+Math.imul(h,K)|0))<<13)|0;u=((a=a+Math.imul(h,J)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(y,Y)|0,i=(i=i+Math.imul(y,X)|0)+Math.imul(m,Y)|0,a=a+Math.imul(m,X)|0,n=n+Math.imul(d,K)|0,i=(i=i+Math.imul(d,J)|0)+Math.imul(v,K)|0,a=a+Math.imul(v,J)|0;var bt=(u+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;u=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,Y)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,Y)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(y,K)|0,i=(i=i+Math.imul(y,J)|0)+Math.imul(m,K)|0,a=a+Math.imul(m,J)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(v,Q)|0,a=a+Math.imul(v,tt)|0;var _t=(u+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;u=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,H)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,Y)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,Y)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,K)|0,i=(i=i+Math.imul(b,J)|0)+Math.imul(_,K)|0,a=a+Math.imul(_,J)|0,n=n+Math.imul(y,Q)|0,i=(i=i+Math.imul(y,tt)|0)+Math.imul(m,Q)|0,a=a+Math.imul(m,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0;var wt=(u+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;u=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,H)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,H)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,Y)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,Y)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,K)|0,i=(i=i+Math.imul(T,J)|0)+Math.imul(k,K)|0,a=a+Math.imul(k,J)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0;var Tt=(u+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ut)|0)+Math.imul(h,lt)|0))<<13)|0;u=((a=a+Math.imul(h,ut)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(O,H)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,H)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,Y)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,Y)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(M,K)|0,i=(i=i+Math.imul(M,J)|0)+Math.imul(S,K)|0,a=a+Math.imul(S,J)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ut)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ut)|0;var kt=(u+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;u=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,H)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,Y)|0,i=(i=i+Math.imul(O,X)|0)+Math.imul(I,Y)|0,a=a+Math.imul(I,X)|0,n=n+Math.imul(L,K)|0,i=(i=i+Math.imul(L,J)|0)+Math.imul(C,K)|0,a=a+Math.imul(C,J)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(v,ft)|0,a=a+Math.imul(v,ht)|0;var At=(u+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,vt)|0)+Math.imul(h,dt)|0))<<13)|0;u=((a=a+Math.imul(h,vt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(D,Y)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,Y)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(O,K)|0,i=(i=i+Math.imul(O,J)|0)+Math.imul(I,K)|0,a=a+Math.imul(I,J)|0,n=n+Math.imul(L,Q)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,Q)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(y,ft)|0,i=(i=i+Math.imul(y,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(u+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,vt)|0)+Math.imul(v,dt)|0))<<13)|0;u=((a=a+Math.imul(v,vt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Y),i=(i=Math.imul(B,X))+Math.imul(N,Y)|0,a=Math.imul(N,X),n=n+Math.imul(D,K)|0,i=(i=i+Math.imul(D,J)|0)+Math.imul(R,K)|0,a=a+Math.imul(R,J)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(u+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,vt)|0)+Math.imul(m,dt)|0))<<13)|0;u=((a=a+Math.imul(m,vt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,K),i=(i=Math.imul(B,J))+Math.imul(N,K)|0,a=Math.imul(N,J),n=n+Math.imul(D,Q)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(u+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,vt)|0)+Math.imul(_,dt)|0))<<13)|0;u=((a=a+Math.imul(_,vt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(u+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,vt)|0)+Math.imul(k,dt)|0))<<13)|0;u=((a=a+Math.imul(k,vt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(u+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,vt)|0)+Math.imul(S,dt)|0))<<13)|0;u=((a=a+Math.imul(S,vt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ut)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ut)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var Pt=(u+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,vt)|0)+Math.imul(C,dt)|0))<<13)|0;u=((a=a+Math.imul(C,vt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(u+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,vt)|0)+Math.imul(I,dt)|0))<<13)|0;u=((a=a+Math.imul(I,vt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(u+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,vt)|0)+Math.imul(R,dt)|0))<<13)|0;u=((a=a+Math.imul(R,vt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var zt=(u+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,vt))+Math.imul(N,dt)|0))<<13)|0;return u=((a=Math.imul(N,vt))+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=gt,l[1]=yt,l[2]=mt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=zt,0!==u&&(l[19]=u,r.length++),r};function v(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),u=Math.max(0,a-t.length+1);u<=l;u++){var c=a-u,f=(0|t.words[c])*(0|e.words[u]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):v(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),u=Math.sin(2*Math.PI/s),c=0;c<i;c+=s)for(var f=l,h=u,p=0;p<o;p++){var d=r[c+p],v=n[c+p],g=r[c+p+o],y=n[c+p+o],m=f*g-h*y;y=f*y+h*g,g=m,r[c+p]=d+g,n[c+p]=v+y,r[c+p+o]=d-g,n[c+p+o]=v-y,p!==s&&(m=l*f-u*h,h=l*h+u*f,f=m)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),u=new Array(n),c=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,u,n),this.transform(o,a,s,l,n,i),this.transform(u,a,c,f,n,i);for(var p=0;p<n;p++){var d=s[p]*c[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*c[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),v(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,u=0;u<this.length;u++)this.words[u]=this.words[u+o];else this.words[0]=0,this.length=1;var c=0;for(u=this.length-1;u>=0&&(0!==c||u>=i);u--){var f=0|this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r||!(this.words[r]&i))},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var u=0;u<s.length;u++)s.words[u]=0}var c=n.clone()._ishlnsubmul(i,1,l);0===c.negative&&(n=c,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,v=1;0==(r.words[0]&v)&&d<26;++d,v<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(u)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var u=0,c=1;0==(e.words[0]&c)&&u<26;++u,c<<=1);if(u>0)for(e.iushrn(u);u-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},i(x,m),x.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i<n;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];for(e.words[e.length++]=a&r,i=10;i<t.length;i++){var o=0|t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}a>>>=22,t.words[i-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(b,m),i(_,m),i(w,m),w.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(y[t])return y[t];var e;if(\"k256\"===t)e=new x;else if(\"p224\"===t)e=new b;else if(\"p192\"===t)e=new _;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new w}return y[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},T.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),u=this.m.subn(1).iushrn(1),c=this.m.bitLength();for(c=new a(2*c*c).toRed(this);0!==this.pow(c,u).cmp(l);)c.redIAdd(l);for(var f=this.pow(c,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var v=p,g=0;0!==v.cmp(s);g++)v=v.redSqr();n(g<d);var y=this.pow(f,new a(1).iushln(d-g-1));h=h.redMul(y),f=y.redSqr(),p=p.redMul(f),d=g}return h},T.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},T.prototype.pow=function(t,e){if(e.isZero())return new a(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var u=e.words[n],c=l-1;c>=0;c--){var f=u>>c&1;i!==r[0]&&(i=this.sqr(i)),0!==f||0!==o?(o<<=1,o|=f,(4==++s||0===n&&0===c)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},T.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},T.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new k(t)},i(k,T),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var 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if(h.right===s){if(!(d=p.left)||0!==d._color){p._color=0,p.right=h.left,h._color=1,h.left=p,l[f-2]=h,l[f-1]=s,i(p),i(h),f>=3&&((v=l[f-3]).right===p?v.right=h:v.left=h);break}h._color=1,p.left=n(1,d),p._color=0,f-=1}else{var d;if(!(d=p.left)||0!==d._color){var v;h.left=s.right,p._color=0,p.right=s.left,s._color=1,s.right=h,s.left=p,l[f-2]=s,l[f-1]=h,i(p),i(h),i(s),f>=3&&((v=l[f-3]).right===p?v.right=s:v.left=s);break}h._color=1,p.left=n(1,d),p._color=0,f-=1}}return l[0]._color=1,new a(o,l[0])},o.forEach=function(t,e,r){if(this.root)switch(arguments.length){case 1:return s(t,this.root);case 2:return l(e,this._compare,t,this.root);case 3:if(this._compare(e,r)>=0)return;return u(e,r,this._compare,t,this.root)}},Object.defineProperty(o,\"begin\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.left;return new c(this,t)}}),Object.defineProperty(o,\"end\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.right;return new c(this,t)}}),o.at=function(t){if(t<0)return new c(this,[]);for(var e=this.root,r=[];;){if(r.push(e),e.left){if(t<e.left._count){e=e.left;continue}t-=e.left._count}if(!t)return new c(this,r);if(t-=1,!e.right)break;if(t>=e.right._count)break;e=e.right}return new c(this,[])},o.ge=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<=0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new c(this,n)},o.gt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new c(this,n)},o.lt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new c(this,n)},o.le=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>=0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new c(this,n)},o.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var i=e(t,r.key);if(n.push(r),0===i)return new c(this,n);r=i<=0?r.left:r.right}return new c(this,[])},o.remove=function(t){var e=this.find(t);return e?e.remove():this},o.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var f=c.prototype;function h(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function p(t,e){return t<e?-1:t>e?1:0}Object.defineProperty(f,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(f,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),f.clone=function(){return new c(this.tree,this._stack.slice())},f.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var o=new Array(t.length),s=t[t.length-1];o[o.length-1]=new e(s._color,s.key,s.value,s.left,s.right,s._count);for(var l=t.length-2;l>=0;--l)(s=t[l]).left===t[l+1]?o[l]=new e(s._color,s.key,s.value,o[l+1],s.right,s._count):o[l]=new e(s._color,s.key,s.value,s.left,o[l+1],s._count);if((s=o[o.length-1]).left&&s.right){var u=o.length;for(s=s.left;s.right;)o.push(s),s=s.right;var c=o[u-1];for(o.push(new e(s._color,c.key,c.value,s.left,s.right,s._count)),o[u-1].key=s.key,o[u-1].value=s.value,l=o.length-2;l>=u;--l)s=o[l],o[l]=new e(s._color,s.key,s.value,s.left,o[l+1],s._count);o[u-1].left=o[u]}if(0===(s=o[o.length-1])._color){var f=o[o.length-2];for(f.left===s?f.left=null:f.right===s&&(f.right=null),o.pop(),l=0;l<o.length;++l)o[l]._count--;return new a(this.tree._compare,o[0])}if(s.left||s.right){for(s.left?h(s,s.left):s.right&&h(s,s.right),s._color=1,l=0;l<o.length-1;++l)o[l]._count--;return new a(this.tree._compare,o[0])}if(1===o.length)return new a(this.tree._compare,null);for(l=0;l<o.length;++l)o[l]._count--;var p=o[o.length-2];return function(t){for(var e,a,o,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((a=t[l-1]).left===e){if((o=a.right).right&&0===o.right._color)return s=(o=a.right=r(o)).right=r(o.right),a.right=o.left,o.left=a,o.right=s,o._color=a._color,e._color=1,a._color=1,s._color=1,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),void(t[l-1]=o);if(o.left&&0===o.left._color)return s=(o=a.right=r(o)).left=r(o.left),a.right=s.left,o.left=s.right,s.left=a,s.right=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).left===a?u.left=s:u.right=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.right=n(0,o));a.right=n(0,o);continue}o=r(o),a.right=o.left,o.left=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),t[l-1]=o,t[l]=a,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((o=a.left).left&&0===o.left._color)return s=(o=a.left=r(o)).left=r(o.left),a.left=o.right,o.right=a,o.left=s,o._color=a._color,e._color=1,a._color=1,s._color=1,i(a),i(o),l>1&&((u=t[l-2]).right===a?u.right=o:u.left=o),void(t[l-1]=o);if(o.right&&0===o.right._color)return s=(o=a.left=r(o)).right=r(o.right),a.left=s.right,o.right=s.left,s.right=a,s.left=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).right===a?u.right=s:u.left=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.left=n(0,o));a.left=n(0,o);continue}var u;o=r(o),a.left=o.right,o.right=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).right===a?u.right=o:u.left=o),t[l-1]=o,t[l]=a,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(o),p.left===s?p.left=null:p.right=null,new a(this.tree._compare,o[0])},Object.defineProperty(f,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(f,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(f,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),f.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),f.update=function(t){var r=this._stack;if(0===r.length)throw new Error(\"Can't update empty node!\");var n=new Array(r.length),i=r[r.length-1];n[n.length-1]=new e(i._color,i.key,t,i.left,i.right,i._count);for(var o=r.length-2;o>=0;--o)(i=r[o]).left===r[o+1]?n[o]=new e(i._color,i.key,i.value,n[o+1],i.right,i._count):n[o]=new e(i._color,i.key,i.value,i.left,n[o+1],i._count);return new a(this.tree._compare,n[0])},f.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},3837:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=new c(t);return r.update(e),r};var n=r(4935),i=r(501),a=r(5304),o=r(6429),s=r(6444),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function u(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function c(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickFontStyle=[\"normal\",\"normal\",\"normal\"],this.tickFontWeight=[\"normal\",\"normal\",\"normal\"],this.tickFontVariant=[\"normal\",\"normal\",\"normal\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.labelFontStyle=[\"normal\",\"normal\",\"normal\"],this.labelFontWeight=[\"normal\",\"normal\",\"normal\"],this.labelFontVariant=[\"normal\",\"normal\",\"normal\"],this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=c.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),u=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),c=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t)for(r=t.ticks,c=!0,this.autoTicks=!1,p=0;p<3;++p)this.tickSpacing[p]=0;else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,c=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),c=!0),c){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?c=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(c=!0),l(\"tickFontStyle\")&&(c=!0),l(\"tickFontWeight\")&&(c=!0),l(\"tickFontVariant\")&&(c=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),u(\"tickColor\");var v=l(\"labels\");l(\"labelFont\")&&(v=!0),l(\"labelFontStyle\")&&(v=!0),l(\"labelFontWeight\")&&(v=!0),l(\"labelFontVariant\")&&(v=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),u(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),u(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),u(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),u(\"gridColor\"),o(\"zeroEnable\"),u(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),u(\"backgroundColor\");var g=[{family:this.labelFont[0],style:this.labelFontStyle[0],weight:this.labelFontWeight[0],variant:this.labelFontVariant[0]},{family:this.labelFont[1],style:this.labelFontStyle[1],weight:this.labelFontWeight[1],variant:this.labelFontVariant[1]},{family:this.labelFont[2],style:this.labelFontStyle[2],weight:this.labelFontWeight[2],variant:this.labelFontVariant[2]}],y=[{family:this.tickFont[0],style:this.tickFontStyle[0],weight:this.tickFontWeight[0],variant:this.tickFontVariant[0]},{family:this.tickFont[1],style:this.tickFontStyle[1],weight:this.tickFontWeight[1],variant:this.tickFontVariant[1]},{family:this.tickFont[2],style:this.tickFontStyle[2],weight:this.tickFontWeight[2],variant:this.tickFontVariant[2]}];this._text?this._text&&(v||c)&&this._text.update(this.bounds,this.labels,g,this.ticks,y):this._text=n(this.gl,this.bounds,this.labels,g,this.ticks,y),this._lines&&c&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;c<3;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<<c&&(f=s,h=a,p=l,d=o),f[c]=r[0][c],h[c]=r[1][c],i[c]>0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}var v=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var y=[0,0,0],m=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,c=o(r,n,i,a,s),f=c.cubeEdges,h=c.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E,L,C=v;for(A=0;A<3;++A)this.backgroundEnable[A]?C[A]=h[A]:C[A]=0;for(this._background.draw(r,n,i,a,C,this.backgroundColor),this._lines.bind(r,n,i,this),A=0;A<3;++A){var P=[0,0,0];h[A]>0?P[A]=a[1][A]:P[A]=a[0][A];for(var O=0;O<2;++O){var I=(A+1+O)%3,z=(A+1+(1^O))%3;this.gridEnable[I]&&this._lines.drawGrid(I,z,this.bounds,P,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(O=0;O<2;++O)I=(A+1+O)%3,z=(A+1+(1^O))%3,this.zeroEnable[z]&&Math.min(a[0][z],a[1][z])<=0&&Math.max(a[0][z],a[1][z])>=0&&this._lines.drawZero(I,z,this.bounds,P,this.zeroLineColor[z],this.zeroLineWidth[z]*this.pixelRatio)}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var D=u(y,M[A].primalMinor),R=u(m,M[A].mirrorMinor),F=this.lineTickLength;for(O=0;O<3;++O){var B=k/r[5*O];D[O]*=F[O]*B,R[O]*=F[O]*B}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,D,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,R,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}function N(t){(L=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio),A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,q=u(x,M[A].primalOffset);for(O=0;O<3;++O)this.lineTickEnable[A]&&(q[O]+=k*U[O]*Math.max(this.lineTickLength[O],0)/r[5*O]);var H=[0,0,0];if(H[A]=1,this.tickEnable[A]){for(-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,E=1,\"auto\"===(S=[this.tickAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),L=[0,0,0],j(A,U,V),O=0;O<3;++O)q[O]+=k*U[O]*this.tickPad[O]/r[5*O];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],q,this.tickColor[A],H,L,S)}if(this.labelEnable[A]){for(E=0,L=[0,0,0],this.labels[A].length>4&&(N(A),E=1),\"auto\"===(S=[this.labelAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),O=0;O<3;++O)q[O]+=k*U[O]*this.labelPad[O]/r[5*O];q[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],q,this.labelColor[A],[0,0,0],L,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},5304:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[u]=d;for(var v=-1;v<=1;v+=2)f[c]=v,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=u;u=c,c=g}var y=n(t,new Float32Array(e)),m=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:y,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:y,type:t.FLOAT,size:3,offset:12,stride:24}],m),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,y,x,b)};var n=r(2762),i=r(8116),a=r(1879).bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},6429:function(t,e,r){\"use strict\";t.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var m=0,x=0;x<2;++x){c[2]=a[x][2];for(var b=0;b<2;++b){c[1]=a[b][1];for(var _=0;_<2;++_)c[0]=a[_][0],h(l[m],c,s),m+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)u[x][k]=l[x][k]/T;p&&(u[x][2]*=-1),T<0&&(w<0||u[x][2]<u[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);o(u[I],u[P],u[O],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);var I,z=d([l[I],l[P],l[O],l[I+(1<<M)+(1<<S)]]);C?E=z:L=z}L>E&&(w|=1<<A)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||u[R][1]>u[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x)(N=R^1<<x)!==w&&N!==D&&(F<0&&(F=N),(S=u[N])[0]<u[F][0]&&(F=N));var B=-1;for(x=0;x<3;++x){var N;(N=R^1<<x)!==w&&N!==D&&N!==F&&(B<0&&(B=N),(S=u[N])[0]>u[B][0]&&(B=N))}var j=v;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,q=w;for(A=0;A<3;++A)V[A]=q&1<<A?-1:1;return y};var n=r(8828),i=r(6760),a=r(5202),o=r(3250),s=new Array(16),l=new Array(8),u=new Array(8),c=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],u[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],u=s[0]/s[3]-n,c=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(u*h-c*f)}return o}var v=[1,1,1],g=[0,0,0],y={cubeEdges:v,axis:g}},501:function(t,e,r){\"use strict\";t.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var v=+r[f][d].x;o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1)}var g=o.length/3|0;s[f]=h,l[f]=g-h,h=o.length/3|0;for(var y=0;y<r[f].length;++y)v=+r[f][y].x,o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1);g=o.length/3|0,u[f]=h,c[f]=g-h}var m=n(t,new Float32Array(o)),x=i(t,[{buffer:m,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,m,x,b,l,s,c,u)};var n=r(2762),i=r(8116),a=r(1879).n,o=[0,0,0],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,c[0]=this.gl.drawingBufferWidth,c[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=c,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,c=h(u,r);c[t]+=e[0][t],this.shader.uniforms.offset=c,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var c=f(s);c[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=c;var p=h(u,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var v=f(l);v[t]=1,this.shader.uniforms.screenAxis=v,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var c=h(u,n);c[t]+=r[0][t],this.shader.uniforms.offset=c;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},1879:function(t,e,r){\"use strict\";var n=r(3236),i=r(9405),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);e.n=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);e.Q=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);e.bg=function(t){return i(t,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},4935:function(t,e,r){\"use strict\";t.exports=function(t,e,r,n,o,l){var u=i(t),f=a(t,[{buffer:u,size:3}]),h=s(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,n,o,l),p};var i=r(2762),a=r(8116),o=r(4359),s=r(1879).Q,l=window||n.global||{},u=l.__TEXT_CACHE||{};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}l.__TEXT_CACHE={};var f=c.prototype,h=[0,0];f.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},f.unbind=function(){this.vao.unbind()},f.update=function(t,e,r,n,i){var a=[];function s(t,e,r,n,i,s){var l=[r.style,r.weight,r.variant,r.family].join(\"_\"),c=u[l];c||(c=u[l]={});var f=c[e];f||(f=c[e]=function(t,e){try{return o(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r.family,fontStyle:r.style,fontWeight:r.weight,fontVariant:r.variant,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var h=(n||12)/12,p=f.positions,d=f.cells,v=0,g=d.length;v<g;++v)for(var y=d[v],m=2;m>=0;--m){var x=p[y[m]];a.push(h*x[0],-h*x[1],t)}}for(var l=[0,0,0],c=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=a.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(a.length/3|0)-f[d],l[d]=a.length/3|0;for(var v=0;v<n[d].length;++v)if(n[d][v].text){var g={family:n[d][v].font||i[d].family,style:i[d].fontStyle||i[d].style,weight:i[d].fontWeight||i[d].weight,variant:i[d].fontVariant||i[d].variant};s(n[d][v].x,n[d][v].text,g,n[d][v].fontSize||12,1.25,p)}c[d]=(a.length/3|0)-l[d]}this.buffer.update(a),this.tickOffset=l,this.tickCount=c,this.labelOffset=f,this.labelCount=h},f.drawTicks=function(t,e,r,n,i,a,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},f.drawLabel=function(t,e,r,n,i,a,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},f.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}},6444:function(t,e){\"use strict\";function r(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u|=0);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var f=\"\"+u;f.length<i;)f=\"0\"+f;return c+\".\"+f}return c}e.create=function(t,e){for(var n=[],i=0;i<3;++i){for(var a=[],o=(t[0][i],t[1][i],0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:r(e[i],o)});for(o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:r(e[i],o)});n.push(a)}return n},e.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}},5445:function(t,e,r){\"use strict\";t.exports=function(t,e,r,l,f){var h=e.model||u,p=e.view||u,y=e.projection||u,m=e._ortho||!1,x=t.bounds,b=(f=f||a(h,p,y,x,m)).axis;o(c,p,h),o(c,y,c);for(var _=v,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var T=n(s(c,c));s(c,c);for(var k=0;k<3;++k){var A=(k+1)%3,M=(k+2)%3,S=g;t:for(w=0;w<2;++w){var E=[];if(b[k]<0!=!!w){S[k]=x[w][k];for(var L=0;L<2;++L){S[A]=x[L^w][A];for(var C=0;C<2;++C)S[M]=x[C^L^w][M],E.push(S.slice())}var P=m?5:4;for(L=P;L===P;++L){if(0===E.length)continue t;E=i.positive(E,T[L])}for(L=0;L<E.length;++L){M=E[L];var O=d(g,c,M,r,l);for(C=0;C<3;++C)_[C].lo=Math.min(_[C].lo,M[C]),_[C].hi=Math.max(_[C].hi,M[C]),C!==k&&(_[C].pixelsPerDataUnit=Math.min(_[C].pixelsPerDataUnit,Math.abs(O[C])))}}}}return _};var n=r(5033),i=r(5202),a=r(6429),o=r(6760),s=r(5665),l=r(5352),u=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),c=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,u=0;u<3;++u)s[u]=o[u]=r[u];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var c=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(c*c+f*f)}return t}var v=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],g=[0,0,0]},2762:function(t,e,r){\"use strict\";var n=r(1888),i=r(5298),a=r(9618),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function u(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function c(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER&&(r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\"),r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=u(this.gl,this.type,this.length,this.usage,t.data,e):this.length=u(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=u(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?c(t,\"uint16\"):c(t,\"float32\"),this.length=u(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=u(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},t.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},6405:function(t,e,r){\"use strict\";var n=r(2931);t.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,p=null,d=null,v=[],g=1/0,y=!1,m=\"raw\"===t.coneSizemode,x=0;x<r.length;x++){var b=r[x];s=Math.min(b[0],s),l=Math.max(b[0],l),u=Math.min(b[1],u),c=Math.max(b[1],c),f=Math.min(b[2],f),h=Math.max(b[2],h);var _=i[x];if(n.length(_)>o&&(o=n.length(_)),x&&!m){var w=2*n.distance(p,b)/(n.length(d)+n.length(_));w?(g=Math.min(g,w),y=!1):y=!0}y||(p=b,d=_),v.push(_)}var T=[s,u,f],k=[l,c,h];e&&(e[0]=T,e[1]=k),0===o&&(o=1);var A=1/o;isFinite(g)||(g=1),a.vectorScale=g;var M=t.coneSize||(m?1:.5);t.absoluteConeSize&&(M=t.absoluteConeSize*A),a.coneScale=M,x=0;for(var S=0;x<r.length;x++)for(var E=(b=r[x])[0],L=b[1],C=b[2],P=v[x],O=n.length(P)*A,I=0;I<8;I++){a.positions.push([E,L,C,S++]),a.positions.push([E,L,C,S++]),a.positions.push([E,L,C,S++]),a.positions.push([E,L,C,S++]),a.positions.push([E,L,C,S++]),a.positions.push([E,L,C,S++]),a.vectors.push(P),a.vectors.push(P),a.vectors.push(P),a.vectors.push(P),a.vectors.push(P),a.vectors.push(P),a.vertexIntensity.push(O,O,O),a.vertexIntensity.push(O,O,O);var z=a.positions.length;a.cells.push([z-6,z-5,z-4],[z-3,z-2,z-1])}return a};var i=r(614);t.exports.createMesh=r(9060),t.exports.createConeMesh=function(e,r){return t.exports.createMesh(e,r,{shaders:i,traceType:\"cone\"})}},9060:function(t,e,r){\"use strict\";var n=r(9405),i=r(2762),a=r(8116),o=r(7766),s=r(6760),l=r(7608),u=r(9618),c=r(6729),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,u,c){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=u,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=c,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=c({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,v=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],v=+t.vertexIntensityBounds[1];else for(var g=0;g<p.length;++g){var y=p[g];d=Math.min(d,y),v=Math.max(v,y)}else for(g=0;g<n.length;++g)y=n[g][2],d=Math.min(d,y),v=Math.max(v,y);for(this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],g=0;g<n.length;++g)for(var m=n[g],x=0;x<3;++x)!isNaN(m[x])&&isFinite(m[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],m[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],m[x]));var b=0;t:for(g=0;g<r.length;++g){var _=r[g];if(3===_.length){for(x=0;x<3;++x){m=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(m[w])||!isFinite(m[w]))continue t}for(x=0;x<3;++x){var T;m=n[T=_[2-x]],a.push(m[0],m[1],m[2],m[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(v-d),0]:[(m[2]-d)/(v-d),0],l.push(A[0],A[1]),f.push(g)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var u={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};u.inverseModel=l(u.inverseModel,u.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(s(c,u.view,u.model),s(c,u.projection,c),l(c,c),o=0;o<3;++o)u.eyePosition[o]=c[12+o]/c[15];var h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];u.lightPosition[o]=p/h}if(this.triangleCount>0){var v=this.triShader;v.bind(),v.uniforms=u,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},t.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),c=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),f=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));f.generateMipmap(),f.minFilter=t.LINEAR_MIPMAP_LINEAR,f.magFilter=t.LINEAR;var p=i(t),d=i(t),v=i(t),g=i(t),y=i(t),m=new h(t,f,l,c,p,d,y,v,g,a(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||\"cone\");return m.update(e),m}},614:function(t,e,r){var n=r(3236),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},737:function(t){t.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},5171:function(t,e,r){var 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worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  gl_FragColor = opacity * fragColor;\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},2260:function(t,e,r){\"use strict\";var n=r(7766);t.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var u=t.getExtension(\"WEBGL_draw_buffers\");if(!l&&u&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(a=n;a<r;++a)i[a]=t.NONE;l[n]=i}}(t,u),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var c=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(e<0||e>c||r<0||r>c)throw new 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c(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function f(t){switch(t){case i:throw new Error(\"gl-fbo: Framebuffer unsupported\");case a:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case o:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case s:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function h(t,e,r,i,a,o){if(!i)return null;var s=n(t,e,r,a,i);return s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var v=this,g=[0|e,0|r];Object.defineProperties(g,{0:{get:function(){return v._shape[0]},set:function(t){return v.width=t}},1:{get:function(){return v._shape[1]},set:function(t){return v.height=t}}}),this._shapeVector=g,function(t){var e=u(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,v=t._useDepth,g=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var y=0;y<o;++y)t.color[y]=h(r,i,a,g,r.RGBA,r.COLOR_ATTACHMENT0+y);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var m=r.getExtension(\"WEBGL_depth_texture\");m?d?t.depth=h(r,i,a,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):v&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),y=0;y<t.color.length;++y)t.color[y].dispose(),t.color[y]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),c(r,e),f(x)}c(r,e)}(this)}var v=d.prototype;function g(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=u(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),c(n,a),f(s)),c(n,a)}}Object.defineProperties(v,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return g(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return g(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,g(this,this._shape[0],t),t},enumerable:!1}}),v.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},v.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},2992:function(t,e,r){var n=r(3387).sprintf,i=r(5171),a=r(1848),o=r(1085);t.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var u=n(\"Error compiling %s shader %s:\\n\",l,s),c=n(\"%s%s\",u,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var v=parseInt(d.split(\":\")[2]);if(isNaN(v))throw new Error(n(\"Could not parse error: %s\",d));h[v]=d}}var g=o(e).split(\"\\n\");for(p=0;p<g.length;p++)if((h[p+3]||h[p+2]||h[p+1])&&(u+=g[p]+\"\\n\",h[p+1])){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),u+=n(\"^^^ %s\\n\\n\",y)}return{long:u.trim(),short:c.trim()}}},2510:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=t.gl,n=new u(t,o(r,l.vertex,l.fragment),o(r,l.pickVertex,l.pickFragment),s(r),s(r),s(r),s(r));return n.update(e),t.addObject(n),n};var n=r(2478),i=r(7762),a=r(1888),o=r(9405),s=r(2762),l=r(6768);function u(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var c,f=u.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(c=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],u=a[3]-a[1];c[0]=2*o/l,c[4]=2*s/u,c[6]=2*(r[0]-a[0])/l-1,c[7]=2*(r[1]-a[1])/u-1,e.bind();var f=e.uniforms;f.viewTransform=c,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,u=a[2]-a[0],c=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*u/f,t[4]=2*c/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var v=i.attributes;return this.positionBuffer.bind(),v.position.pointer(),this.weightBuffer.bind(),v.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),v.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var u,c,f,p,d=t.colorLevels||[0],v=t.colorValues||[0,0,0,1],g=d.length,y=this.bounds;l?(u=y[0]=r[0],c=y[1]=o[0],f=y[2]=r[r.length-1],p=y[3]=o[o.length-1]):(u=y[0]=r[0]+(r[1]-r[0])/2,c=y[1]=o[0]+(o[1]-o[0])/2,f=y[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=y[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var m=1/(f-u),x=1/(p-c),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,O;l?(P=x*(o[C]-c),O=x*(o[C+1]-c)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-c):x*(o[C]-(o[C]-o[C-1])/2-c),O=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-c):x*(o[C]+(o[C]-o[C-1])/2-c));for(var I=0;I<E;++I){var z,D;l?(z=m*(r[I]-u),D=m*(r[I+1]-u)):(z=I<b-1?m*(r[I]-(r[I+1]-r[I])/2-u):m*(r[I]-(r[I]-r[I-1])/2-u),D=I<b-1?m*(r[I]+(r[I+1]-r[I])/2-u):m*(r[I]+(r[I]-r[I-1])/2-u));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],q=s[l?(C+V)*b+(I+U):C*b+I],H=n.le(d,q);if(H<0)F=v[0],B=v[1],N=v[2],j=v[3];else if(H===g-1)F=v[4*g-4],B=v[4*g-3],N=v[4*g-2],j=v[4*g-1];else{var G=(q-d[H])/(d[H+1]-d[H]),W=1-G,Y=4*H,X=4*(H+1);F=W*v[Y]+G*v[X],B=W*v[Y+1]+G*v[X+1],N=W*v[Y+2]+G*v[X+2],j=W*v[Y+3]+G*v[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*z+.5*D,k[2*S+1]=.5*P+.5*O,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+I,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},6768:function(t,e,r){\"use strict\";var n=r(3236);t.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},7319:function(t,e,r){var n=r(3236),i=r(9405),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},5714:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),c=u(new Array(1024),[256,1,4]),p=0;p<1024;++p)c.data[p]=255;var d=a(e,c);d.wrap=e.REPEAT;var v=new y(e,r,o,s,l,d);return v.update(t),v};var n=r(2762),i=r(8116),a=r(7766),o=new Uint8Array(4),s=new Float32Array(o.buffer),l=r(2478),u=r(9618),c=r(7319),f=c.createShader,h=c.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function v(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function y(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=y.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var 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r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return(r=Math.sqrt(r))+(a=Math.sqrt(a))<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(c,e),y=0;for(f=0;f<3;++f){if(g[f]<-.001||g[f]>1.0001)return null;y+=g[f]}return Math.abs(y-1)>.001?null:[h,s(t,g),g]}},840:function(t,e,r){var n=r(3236),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.pointShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},e.pickShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},e.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},7201:function(t,e,r){\"use strict\";var n=r(9405),i=r(2762),a=r(8116),o=r(7766),s=r(8406),l=r(6760),u=r(7608),c=r(9618),f=r(6729),h=r(7765),p=r(1888),d=r(840),v=r(7626),g=d.meshShader,y=d.wireShader,m=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=v,this.edgeVAO=m,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var u=r[l],c=0;c<2;++c){var f=u[0];2===u.length&&(f=u[c]);for(var d=n[f][0],v=n[f][1],g=i[f],y=1-g,m=this.positions[d],x=this.positions[v],b=0;b<3;++b)o[s++]=g*m[b]+y*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return c(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],u=[],h=[],p=[],d=[],v=[],g=[],y=[],m=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,O=t.cellUVs,I=t.cellIntensity,z=1/0,D=-1/0;if(!C&&!O)if(P)if(t.vertexIntensityBounds)z=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];z=Math.min(z,F),D=Math.max(D,F)}else if(I)if(t.cellIntensityBounds)z=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<I.length;++R)F=I[R],z=Math.min(z,F),D=Math.max(D,F);else for(R=0;R<n.length;++R)F=n[R][2],z=Math.min(z,F),D=Math.max(D,F);this.intensity=P||I||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.pickVertex=!(I||E);var B=t.pointSizes,N=t.pointSize||1;for(this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[Y=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;y.push(j[0],j[1],j[2]),X=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[Y]-z)/(D-z),this.opacityscale)):3===X.length?m.push(X[0],X[1],X[2],this.opacity):(m.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[Y]:P?[(P[Y]-z)/(D-z),0]:O?O[R]:I?[(I[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],x.push(Z[0],Z[1]),B?b.push(B[Y]):b.push(N),_.push(R),H+=1;break;case 2:for(U=0;U<2;++U){j=n[Y=G[U]];for(var W=0;W<3;++W)if(isNaN(j[W])||!isFinite(j[W]))continue t}for(U=0;U<2;++U)j=n[Y=G[U]],p.push(j[0],j[1],j[2]),X=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[Y]-z)/(D-z),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[Y]:P?[(P[Y]-z)/(D-z),0]:O?O[R]:I?[(I[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],v.push(Z[0],Z[1]),g.push(R);q+=1;break;case 3:for(U=0;U<3;++U)for(j=n[Y=G[U]],W=0;W<3;++W)if(isNaN(j[W])||!isFinite(j[W]))continue t;for(U=0;U<3;++U){var Y,X,Z,K;j=n[Y=G[2-U]],i.push(j[0],j[1],j[2]),(X=S?S[Y]:E?E[R]:L)?this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[Y]-z)/(D-z),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=C?C[Y]:P?[(P[Y]-z)/(D-z),0]:O?O[R]:I?[(I[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],u.push(Z[0],Z[1]),K=w?w[Y]:T[R],l.push(K[0],K[1],K[2]),h.push(R)}V+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=V,this.pointPositions.update(y),this.pointColors.update(m),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(v),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(u),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=u(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(l(c,s.view,s.model),l(c,s.projection,c),u(c,c),o=0;o<3;++o)s.eyePosition[o]=c[12+o]/c[15];var f,h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],u=this.positions[r[1]],c=this.positions[r[2]],f=[(l[0]+u[0]+c[0])/3,(l[1]+u[1]+c[1])/3,(l[2]+u[2]+c[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=v(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},t.exports=function(t,e){if(1===arguments.length&&(t=(e=t).gl),!(t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\")))throw new Error(\"derivatives not supported\");var r=function(t){var e=n(t,g.vertex,g.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}(t),s=function(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}(t),l=M(t),u=S(t),f=E(t),h=L(t),p=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),v=i(t),m=i(t),x=i(t),b=i(t),_=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:b,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:x,type:t.FLOAT,size:3}]),w=i(t),k=i(t),A=i(t),C=i(t),P=a(t,[{buffer:w,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:k,type:t.FLOAT,size:4},{buffer:A,type:t.FLOAT,size:2}]),O=i(t),I=i(t),z=i(t),D=i(t),R=i(t),F=a(t,[{buffer:O,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:I,type:t.FLOAT,size:4},{buffer:z,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=new T(t,p,r,s,l,u,f,h,d,b,v,m,x,_,w,C,k,A,P,O,R,I,z,D,F,B,a(t,[{buffer:B,type:t.FLOAT,size:3}]));return N.update(e),N}},8120:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new o(t,n(e,[0,0,0,1,1,0,1,1]),i(e,a.boxVert,a.lineFrag))};var n=r(2762),i=r(9405),a=r(3603);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,u=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},1913:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new s(t,n(e),i(e,o.gridVert,o.gridFrag),i(e,o.tickVert,o.gridFrag))};var n=r(2762),i=r(9405),a=r(2478),o=r(3603);function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var u,c,f,h,p,d=s.prototype;d.draw=(u=[0,0],c=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,v=0;v<2;++v){var g=a[v],y=a[v+2]-g,m=.5*(o[v+2]+o[v]),x=o[v+2]-o[v];c[v]=2*y/x,u[v]=2*(g-m)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=u,r.uniforms.dataScale=c;var b=0;for(v=0;v<2;++v){f[0]=f[1]=0,f[v]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[v]/(s[v+2]-s[v])*d,r.uniforms.color=h[v];var _=6*n[v].length;p[v]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,v=s.viewBox,g=s.pixelRatio,y=s.screenBox,m=y[2]-y[0],x=y[3]-y[1],b=v[2]-v[0],_=v[3]-v[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/m,t[0]*=b/m,e[1]*=_/x,t[1]*=_/x,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var S=c.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,O=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),I=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),z=0+6*O,D=6*Math.max(0,I-O),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(v[0]-E[1])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[1]*g/m,o[1]=L[1]*g/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[1]-E[0])/x-1,o[0]=L[0]*g/m,o[1]=E[0]*g/x,D&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D)),i[0]=2*(v[2]+E[3])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[3]*g/m,o[1]=L[3]*g/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[3]+E[2])/x-1,o[0]=L[2]*g/m,o[1]=E[2]*g/x,D&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],u=r[o],c=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-u)/(c-u);s.push(d);for(var v=0;v<6;++v)n[i++]=d,n[i++]=h[v],n[i++]=p[v]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},4747:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new o(t,n(e,[-1,-1,-1,1,1,-1,1,1]),i(e,a.lineVert,a.lineFrag))};var n=r(2762),i=r(9405),a=r(3603);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,u=this.shader,c=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,u.uniforms.start=s,u.uniforms.end=l,u.uniforms.width=i*o.pixelRatio,u.uniforms.color=a,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},3603:function(t,e,r){\"use strict\";var n=r(3236),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);t.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},2142:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new l(t,n(e),i(e,s.textVert,s.textFrag))};var n=r(2762),i=r(9405),a=r(529),o=r(2478),s=r(3603);function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var u,c,f,h,p,d,v=l.prototype;v.drawTicks=(u=[0,0],c=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,v=e.tickPad,g=e.tickColor,y=e.tickAngle,m=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);u[0]=u[1]=0,u[t]=1,c[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];c[1^t]=M*s[1^t]-1,d[t]&&(c[1^t]-=M*p*v[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t],r.uniforms.angle=y[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t]&&T&&(c[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),c[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(c[1^t]+=M*p*v[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t+2],r.uniforms.angle=y[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t+2]&&T&&(c[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),v.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),v.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,u=.5*(n[o+2]+n[o]),c=n[o+2]-n[o],f=a[o],v=a[o+2]-f,g=i[o],y=i[o+2]-g;p[o]=2*l/c*v/y,h[o]=2*(s-u)/c*v/y}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),v.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,u=t.bounds;for(o=0;o<2;++o){var c=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,v=p.text,g=p.font||\"sans-serif\",y=p.fontStyle||\"normal\",m=p.fontWeight||\"normal\",x=p.fontVariant||\"normal\";i=p.fontSize||12;for(var b=1/(u[o+2]-u[o]),_=u[o],w=v.split(\"\\n\"),T=0;T<w.length;T++)for(n=a(g,w[T],{fontStyle:y,fontWeight:m,fontVariant:x}).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-T*i*1.2,(d-_)*b);c.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=c,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{fontStyle:t.labelFontStyle[o],fontWeight:t.labelFontWeight[o],fontVariant:t.labelFontVariant[o],textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title,{fontStyle:t.titleFontStyle,fontWeight:t.titleFontWeight,fontVariant:t.titleFontVariant}).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},v.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},1850:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=new l(e,n(e,[e.drawingBufferWidth,e.drawingBufferHeight]));return r.grid=i(r),r.text=a(r),r.line=o(r),r.box=s(r),r.update(t),r};var n=r(3589),i=r(1913),a=r(2142),o=r(4747),s=r(8120);function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var u=l.prototype;function c(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}u.setDirty=function(){this.dirty=this.pickDirty=!0},u.setOverlayDirty=function(){this.dirty=!0},u.nextDepthValue=function(){return this._depthCounter++/65536},u.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var v=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(v,e[1],v,e[3],p[d],h[d]):o.drawLine(e[0],v,e[2],v,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var g=this.borderLineEnable,y=this.borderLineWidth,m=this.borderLineColor;for(g[1]&&o.drawLine(r[0],r[1]-.5*y[1]*i,r[0],r[3]+.5*y[3]*i,y[1],m[1]),g[0]&&o.drawLine(r[0]-.5*y[0]*i,r[1],r[2]+.5*y[2]*i,r[1],y[0],m[0]),g[3]&&o.drawLine(r[2],r[1]-.5*y[1]*i,r[2],r[3]+.5*y[3]*i,y[3],m[3]),g[2]&&o.drawLine(r[0]-.5*y[0]*i,r[3],r[2]+.5*y[2]*i,r[3],y[2],m[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},u.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},u.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){var f=u[c].pick(a,o,l);if(f)return f}return null}},u.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},u.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},u.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},u.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]),this.screenBox,this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=c(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=c(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=c(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=c(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=c(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=c(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],labelFontStyle:t.labelFontStyle||[\"normal\",\"normal\"],labelFontWeight:t.labelFontWeight||[\"normal\",\"normal\"],labelFontVariant:t.labelFontVariant||[\"normal\",\"normal\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\",titleFontStyle:t.titleFontStyle||\"normal\",titleFontWeight:t.titleFontWeight||\"normal\",titleFontVariant:t.titleFontVariant||\"normal\"}),this.static=!!t.static,this.setDirty()},u.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();for(this.objects.length=0,t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},u.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},u.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},u.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},u.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},4437:function(t,e,r){\"use strict\";t.exports=function(t,e){t=t||document.body;var r=[.01,1/0];\"distanceLimits\"in(e=e||{})&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),\"zoomMin\"in e&&(r[0]=e.zoomMin),\"zoomMax\"in e&&(r[1]=e.zoomMax);var u=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),c=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:u,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:u.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;u.idle(e-r),u.recalcMatrix(i),u.flush(e-(100+2*r));for(var a=!0,o=u.computedMatrix,s=0;s<16;++s)a=a&&c[s]===o[s],c[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(u.computedRadius[0]),!0)},lookAt:function(t,e,r){u.lookAt(u.lastT(),t,e,r)},rotate:function(t,e,r){u.rotate(u.lastT(),t,e,r)},pan:function(t,e,r){u.pan(u.lastT(),t,e,r)},translate:function(t,e,r){u.translate(u.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return u.computedMatrix},set:function(t){return u.setMatrix(u.lastT(),t),u.computedMatrix},enumerable:!0},mode:{get:function(){return u.getMode()},set:function(t){var e=u.computedUp.slice(),r=u.computedEye.slice(),i=u.computedCenter.slice();if(u.setMode(t),\"turntable\"===t){var a=n();u._active.lookAt(a,r,i,e),u._active.lookAt(a+500,r,i,[0,0,1]),u._active.flush(a)}return u.getMode()},enumerable:!0},center:{get:function(){return u.computedCenter},set:function(t){return u.lookAt(u.lastT(),null,t),u.computedCenter},enumerable:!0},eye:{get:function(){return u.computedEye},set:function(t){return u.lookAt(u.lastT(),t),u.computedEye},enumerable:!0},up:{get:function(){return u.computedUp},set:function(t){return u.lookAt(u.lastT(),null,null,t),u.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return u.setDistance(u.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return u.getDistanceLimits(r)},set:function(t){return u.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,c=\"zoom\"===o,h=!!a.control,p=!!a.alt,v=!!a.shift,g=!!(1&e),y=!!(2&e),m=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&g&&!h&&!p&&!v||g&&!h&&!p&&v)&&u.rotate(A,w*k*b,-T*k*_,0),(l&&g&&!h&&!p&&!v||y||g&&h&&!p&&!v)&&u.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),c&&g&&!h&&!p&&!v||m||g&&!h&&p&&!v)){var M=-d.zoomSpeed*_/window.innerHeight*(A-u.lastT())*100;u.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))u.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-u.lastT())/20;u.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=r(3025),i=r(6296),a=r(351),o=r(8512),s=r(24),l=r(7520)},799:function(t,e,r){var n=r(3236),i=r(9405),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},4100:function(t,e,r){\"use strict\";var n=r(4437),i=r(3837),a=r(5445),o=r(4449),s=r(3589),l=r(2260),u=r(7169),c=r(351),f=r(4772),h=r(4040),p=r(799),d=r(9216)({tablet:!0,featureDetect:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}return e>0?(r=Math.round(Math.pow(10,e)),Math.ceil(t/r)*r):Math.ceil(t)}function y(t){return\"boolean\"!=typeof t||t}t.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;e||(e=document.createElement(\"canvas\"),t.container?t.container.appendChild(e):document.body.appendChild(e));var r=t.gl;if(r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d})),!r)throw new Error(\"webgl not supported\");var m=t.bounds||[[-10,-10,-10],[10,10,10]],x=new v,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],O=!0,I=!0,z={view:null,projection:new Array(16),model:new Array(16),_ortho:!1},D=(I=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),R=t.cameraObject||n(e,T),F={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:R,axes:A,axesPixels:null,spikes:S,bounds:m,objects:E,shape:D,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:z,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,I=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},B=[r.drawingBufferWidth/F.pixelRatio|0,r.drawingBufferHeight/F.pixelRatio|0];function N(){if(!F._stopped&&F.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*F.pixelRatio),a=0|Math.ceil(n*F.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",O=!0}}}function j(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,D);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function U(){if(F.contextLost)return!0;r.isContextLost()&&(F.contextLost=!0,F.mouseListener.enabled=!1,F.selection.object=null,F.oncontextloss&&F.oncontextloss())}F.autoResize&&N(),window.addEventListener(\"resize\",N),F.update=function(t){F._stopped||(t=t||{},O=!0,I=!0)},F.add=function(t){F._stopped||(t.axes=A,E.push(t),L.push(-1),O=!0,I=!0,j())},F.remove=function(t){if(!F._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),O=!0,I=!0,j())}},F.dispose=function(){if(!F._stopped&&(F._stopped=!0,window.removeEventListener(\"resize\",N),e.removeEventListener(\"webglcontextlost\",U),F.mouseListener.enabled=!1,!F.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();for(b.dispose(),t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},F._mouseRotating=!1,F._prevButtons=0,F.enableMouseListeners=function(){F.mouseListener=c(e,(function(t,e,r){if(!F._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&F._prevButtons)F._mouseRotating=!0;else{F._mouseRotating&&(I=!0),F._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,B[1]-r-1,F.pickRadius);if(l){if(l.distance>x.distance)continue;for(var u=0;u<i;++u){var c=E[u];if(L[u]===s){var f=c.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=c,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),O=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),O=!0),(o=o||x.object!==a)&&F.onselect&&F.onselect(x),1&t&&!(1&F._prevButtons)&&F.onclick&&F.onclick(x),F._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",U);var V=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],q=[V[0].slice(),V[1].slice()];function H(){if(!U()){N();var t=F.camera.tick();z.view=F.camera.matrix,O=O||t,I=I||t,A.pixelRatio=F.pixelRatio,S.pixelRatio=F.pixelRatio;var e=E.length,n=V[0],i=V[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=F.pixelRatio,C.axes=F.axes,O=O||!!C.dirty,I=I||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],c=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],c[p])}var d=F.bounds;if(F.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var v=.05*(i[p]-n[p]);n[p]=n[p]-v,i[p]=i[p]+v}d[0][p]=n[p],d[1][p]=i[p]}var y=!1;for(p=0;p<3;++p)y=y||q[0][p]!==d[0][p]||q[1][p]!==d[1][p],q[0][p]=d[0][p],q[1][p]=d[1][p];if(I=I||y,O=O||y){if(y){var m=[0,0,0];for(o=0;o<3;++o)m[o]=g((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:m}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;for(D[0]=T,D[1]=k,B[0]=0|Math.max(T/F.pixelRatio,1),B[1]=0|Math.max(k/F.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,u=t.zFar,c=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,u),n._ortho=!0):(f(i,c,p,l,u),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var v=0;for(d=0;d<3;++d)v=Math.max(v,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/v,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(F,w),o=0;o<e;++o)(C=E[o]).axesBounds=d,F.clipToBounds&&(C.clipBounds=d);x.object&&(F.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),I&&(I=!1,function(){if(!U()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=B,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(z))}i.end()}}}()),F.axesPixels=a(F.axes,z,T,k),F.onrender&&F.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),F.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;for(A.enable&&(M=M||A.isTransparent(),A.draw(z)),S.axes=A,x.object&&S.draw(z),r.disable(r.CULL_FACE),o=0;o<e;++o)(C=E[o]).axes=A,C.pixelRatio=F.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(z),C.isTransparent&&C.isTransparent()&&(M=!0);if(M){for(b.shape=D,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(z),o=0;o<e;++o)(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(z);for(r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(z),o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(z)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,u(r),r.disable(r.BLEND)}for(O=!1,o=0;o<e;++o)E[o].dirty=!1}}}return F.enableMouseListeners(),function t(){F._stopped||F.contextLost||(H(),requestAnimationFrame(t))}(),F.redraw=function(){F._stopped||(O=!0,H())},F},createCamera:n}},6640:function(t,e,r){var n=r(3236);e.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),e.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),e.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),e.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},4696:function(t,e,r){\"use strict\";var n=r(9405),i=r(2762),a=r(1888),o=r(6640);function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}t.exports=function(t,e){var r=t.gl,a=new s(t,i(r),i(r),n(r,o.pointVertex,o.pointFragment),n(r,o.pickVertex,o.pickFragment));return a.update(e),t.addObject(a),a};var l,u,c=s.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),u=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)u[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(u),i||a.free(l),o||a.free(u),this.pointCount=n,this.pickOffset=0},c.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],u=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),c=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=c<5,r.uniforms.pointSize=c,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(u[0]=255&t,u[1]=t>>8&255,u[2]=t>>16&255,u[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=u,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},783:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],f=e[2],h=e[3],p=r[0],d=r[1],v=r[2],g=r[3];return(a=u*p+c*d+f*v+h*g)<0&&(a=-a,p=-p,d=-d,v=-v,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*p,t[1]=s*c+l*d,t[2]=s*f+l*v,t[3]=s*h+l*g,t}},5964:function(t){\"use strict\";t.exports=function(t){return t||0===t?t.toString():\"\"}},9366:function(t,e,r){\"use strict\";var n=r(4359);t.exports=function(t,e,r){var a=[e.style,e.weight,e.variant,e.family].join(\"_\"),o=i[a];if(o||(o=i[a]={}),t in o)return o[t];var s={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e.family,fontStyle:e.style,fontWeight:e.weight,fontVariant:e.variant,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},l=n(t,s);s.triangles=!1;var u,c,f=n(t,s);if(r&&1!==r){for(u=0;u<l.positions.length;++u)for(c=0;c<l.positions[u].length;++c)l.positions[u][c]/=r;for(u=0;u<f.positions.length;++u)for(c=0;c<f.positions[u].length;++c)f.positions[u][c]/=r}var h=[[1/0,1/0],[-1/0,-1/0]],p=f.positions.length;for(u=0;u<p;++u){var d=f.positions[u];for(c=0;c<2;++c)h[0][c]=Math.min(h[0][c],d[c]),h[1][c]=Math.max(h[1][c],d[c])}return o[t]=[l,f,h]};var i={}},1283:function(t,e,r){var n=r(9405),i=r(3236),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),u=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},v={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};function y(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}e.createPerspective=function(t){return y(t,f)},e.createOrtho=function(t){return y(t,h)},e.createProject=function(t){return y(t,p)},e.createPickPerspective=function(t){return y(t,d)},e.createPickOrtho=function(t){return y(t,v)},e.createPickProject=function(t){return y(t,g)}},8418:function(t,e,r){\"use strict\";var n=r(5219),i=r(2762),a=r(8116),o=r(1888),s=r(6760),l=r(1283),u=r(9366),c=r(5964),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function v(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,u,c,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=u,this.pickOrthoShader=c,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}t.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),u=l.createPickOrtho(e),c=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),v=new g(e,r,n,o,f,h,p,d,a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),s,u,c);return v.update(t),v};var y=g.prototype;y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},y.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var m=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function C(t,e,r,n,i,a,o){var l=r.gl;if((a===r.projectHasAlpha||o)&&function(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,u=r.model||f,c=r.view||f,h=r.projection||f,d=e.axesBounds,v=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],m[0]=2/o.drawingBufferWidth,m[1]=2/o.drawingBufferHeight,t.bind(),l.view=c,l.projection=h,l.screenSize=m,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=v,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var y=T,L=0;L<16;++L)y[L]=0;for(L=0;L<4;++L)y[5*L]=1;y[5*g]=0,i[g]<0?y[12+g]=d[0][g]:y[12+g]=d[1][g],s(y,u,y),l.model=y;var C=(g+1)%3,P=(g+2)%3,O=M(x),I=M(b);O[C]=1,I[P]=1;var z=p(0,0,0,S(_,O)),D=p(0,0,0,S(w,I));if(Math.abs(z[1])>Math.abs(D[1])){var R=z;z=D,D=R,R=O,O=I,I=R;var F=C;C=P,P=F}z[0]<0&&(O[C]=-1),D[1]>0&&(I[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(u[4*C+L],2),N+=Math.pow(u[4*P+L],2);O[C]/=Math.sqrt(B),I[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(k,v[0],g,-1e8),l.fragClipBounds[1]=E(k,v[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}(e,r,n,i),a===r.hasAlpha||o){t.bind();var u=t.uniforms;u.model=n.model||f,u.view=n.view||f,u.projection=n.projection||f,m[0]=2/l.drawingBufferWidth,m[1]=2/l.drawingBufferHeight,u.screenSize=m,u.highlightId=r.highlightId,u.highlightScale=r.highlightScale,u.fragClipBounds=L,u.clipBounds=r.axes.bounds,u.opacity=r.opacity,u.pickGroup=r.pickId/255,u.pixelRatio=i,r.vao.bind(),r.vao.draw(l.TRIANGLES,r.vertexCount),r.lineWidth>0&&(l.lineWidth(r.lineWidth*i),r.vao.draw(l.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=c(a);var 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float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting 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* cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},7815:function(t,e,r){\"use strict\";var n=r(2931),i=r(9970),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},s=function(t,e,r){return t<e?e:t>r?r:t},l=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};t.exports=function(t,e){var r=t.startingPositions,u=t.maxLength||1e3,c=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,l=t[0],u=t[1],c=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=o(a[0],l),v=o(a[1],u),g=o(a[2],c),y=d+1,m=v+1,x=g+1;if(d=s(d,0,f-1),y=s(y,0,f-1),v=s(v,0,h-1),m=s(m,0,h-1),g=s(g,0,p-1),x=s(x,0,p-1),d<0||v<0||g<0||y>f-1||m>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][y],E=a[1][v],L=a[1][m],C=a[2][g],P=(l-M)/(S-M),O=(u-E)/(L-E),I=(c-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(O)||(O=.5),isFinite(I)||(I=.5),r.reversedX&&(d=f-1-d,y=f-1-y),r.reversedY&&(v=h-1-v,m=h-1-m),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 5:k=g,A=x,w=v*p,T=m*p,b=d*p*h,_=y*p*h;break;case 4:k=g,A=x,b=d*p,_=y*p,w=v*p*f,T=m*p*f;break;case 3:w=v,T=m,k=g*h,A=x*h,b=d*h*p,_=y*h*p;break;case 2:w=v,T=m,b=d*h,_=y*h,k=g*h*f,A=x*h*f;break;case 1:b=d,_=y,k=g*f,A=x*f,w=v*f*p,T=m*f*p;break;default:b=d,_=y,w=v*f,T=m*f,k=g*f*h,A=x*f*h}var z=i[b+w+k],D=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(V,z,B,P),n.lerp(q,D,N,P),n.lerp(H,R,j,P),n.lerp(G,F,U,P);var W=n.create(),Y=n.create();n.lerp(W,V,H,O),n.lerp(Y,q,G,O);var X=n.create();return n.lerp(X,W,Y,I),X}(e,t,p)},v=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},g=[],y=e[0][0],m=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<y||e>b||r<m||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/u,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,u=0;u<s;u++){var c=t[u],f=c[0],h=c[1],p=c[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=l(e),v=l(r),g=l(n),y=Math.min(d,v,g);return isFinite(y)?y:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],O=[],I=d(C),z=C;O.push(I);var D=[],R=v(C,I),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),g.push({points:P,velocities:O,divergences:D});for(var B=0;B<100*u&&P.length<u&&T(C);){B++;var N=n.clone(I),j=n.squaredLength(N);if(0===j)break;j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),I=d(N),n.squaredDistance(z,N)-A>-1e-4*A&&(P.push(N),z=N,O.push(I),R=v(N,I),F=n.length(R),isFinite(F)&&F>S&&(S=F),D.push(F)),C=N}}var U=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,u=0;u<l.length;u++)o=Math.max(o,n.length(l[u]));var c=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,u=[],c=[],f=[],h=[],p=[],d=[],v=0,g=0,y=i.create(),m=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),g=n.length(_)/a,y=i.create(),n.copy(y,_),y[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;u.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(m,y,y,y,m,m),d.push(v,g,g,g,v,v);var A=u.length;c.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=m;m=y,y=S;var E=v;v=g,g=E}return{positions:u,cells:c,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<c.length;s++){var v=c[s],g=f.length;for(f=f.concat(v.positions),p=p.concat(v.vectors),d=d.concat(v.vertexIntensity),u=0;u<v.cells.length;u++){var y=v.cells[u],m=[];h.push(m);for(var x=0;x<y.length;x++)m.push(y[x]+g)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}}(g,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*c*M/S),U};var u=r(6740),c=r(6405).createMesh;t.exports.createTubeMesh=function(t,e){return c(t,e,{shaders:u,traceType:\"streamtube\"})}},990:function(t,e,r){var n=r(9405),i=r(3236),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color — in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);e.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},e.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},9499:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=m(e),n=b(e),s=x(e),l=_(e),u=i(e),c=a(e,[{buffer:u,size:4,stride:w,offset:0},{buffer:u,size:3,stride:w,offset:16},{buffer:u,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),v=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);v.minFilter=e.LINEAR,v.magFilter=e.LINEAR;var g=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,u,c,v,s,l,f,h,p,d,[0,0,0]),y={levels:[[],[],[]]};for(var T in t)y[T]=t[T];return y.colormap=y.colormap||\"jet\",g.update(y),g};var n=r(8828),i=r(2762),a=r(8116),o=r(7766),s=r(1888),l=r(6729),u=r(5298),c=r(9994),f=r(9618),h=r(3711),p=r(6760),d=r(7608),v=r(2478),g=r(6199),y=r(990),m=y.createShader,x=y.createContourShader,b=y.createPickShader,_=y.createPickContourShader,w=40,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],k=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,u,c,h,p,d,v,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=v,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.genColormap=function(t,e){var r=!1,n=c([l({colormap:t,nshades:S,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return u.divseq(n,255),this.hasAlphaScale=r,n},L.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},L.isOpaque=function(){return!this.isTransparent()},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var u=P.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var I={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},z=T.slice(),D=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=D,n.vertexColor=this.vertexColor;var s=z;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var u=s[12+i];for(o=0;o<3;++o)u+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=u/l}var c=O(n,this);if(c.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=c.projections[i],this._shader.uniforms.clipBounds=c.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(c.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=c.projections[i],f.uniforms.clipBounds=c.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=A[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var v=0;v<this.contourLevels[o].length;++v)v===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==v&&v-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][v]&&(f.uniforms.height=this.contourLevels[o][v],h.draw(r.LINES,this._contourCounts[o][v],this._contourOffsets[o][v]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=A[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=c.projections[o],f.uniforms.clipBounds=c.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}L.draw=function(t){return R.call(this,t,!1)},L.drawTransparent=function(t){return R.call(this,t,!0)};var F={model:T,view:T,projection:T,inverseModel:T,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function B(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function N(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function j(t){if(Array.isArray(t)){if(Array.isArray(t))return[N(t[0]),N(t[1]),N(t[2])];var e=N(t);return[e.slice(),e.slice(),e.slice()]}}L.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=F;r.model=t.model||T,r.view=t.view||T,r.projection=t.projection||T,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=D;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=O(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=A[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=A[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var u=0;u<this.contourLevels[a].length;++u)this._contourCounts[a][u]&&(s.uniforms.height=this.contourLevels[a][u],l.draw(e.LINES,this._contourCounts[a][u],this._contourOffsets[a][u]))}l.unbind()}},L.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var f=c?a:1-a,h=0;h<2;++h)for(var p=i+c,d=s+h,g=f*(h?l:1-l),y=0;y<3;++y)u[y]+=this._field[y].get(p,d)*g;for(var m=this._pickResult.level,x=0;x<3;++x)if(m[x]=v.le(this.contourLevels[x],u[x]),m[x]<0)this.contourLevels[x].length>0&&(m[x]=0);else if(m[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][m[x]],_=this.contourLevels[x][m[x]+1];Math.abs(b-u[x])>Math.abs(_-u[x])&&(m[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();u.assign(t.lo(1,1).hi(r[0],r[1]),e),u.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),u.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),u.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),u.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var u=l[o];for(y=0;y<2;++y)if(u.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],u)}}else if(t.ticks){var c=t.ticks;if(!Array.isArray(c)||2!==c.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=c[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var v=[0,0];v[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],v,0)}this._field[0].set(0,0,0);for(var y=0;y<a[0];++y)this._field[0].set(y+1,0,y);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),y=0;y<a[1];++y)this._field[1].set(0,y+1,y);this._field[1].set(0,a[1]+1,a[1]-1)}var m=this._field,x=f(s.mallocFloat(3*m[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)g(x.pick(o),m[o],\"mirror\");var b=f(s.mallocFloat(3*m[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(y=0;y<a[1]+2;++y){var _=x.get(0,o,y,0),w=x.get(0,o,y,1),T=x.get(1,o,y,0),A=x.get(1,o,y,1),M=x.get(2,o,y,0),S=x.get(2,o,y,1),E=T*S-A*M,L=M*w-S*_,C=_*A-w*T,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,y,0,E*P),b.set(o,y,1,L*P),b.set(o,y,2,C*P)}s.free(x.data);var O=[1/0,1/0,1/0],I=[-1/0,-1/0,-1/0],z=1/0,D=-1/0,R=(a[0]-1)*(a[1]-1)*6,F=s.mallocFloat(n.nextPow2(10*R)),N=0,U=0;for(o=0;o<a[0]-1;++o)t:for(y=0;y<a[1]-1;++y){for(var V=0;V<2;++V)for(var q=0;q<2;++q)for(var H=0;H<3;++H){var G=this._field[H].get(1+o+V,1+y+q);if(isNaN(G)||!isFinite(G))continue t}for(H=0;H<6;++H){var W=o+k[H][0],Y=y+k[H][1],X=this._field[0].get(W+1,Y+1),Z=this._field[1].get(W+1,Y+1);G=this._field[2].get(W+1,Y+1),E=b.get(W+1,Y+1,0),L=b.get(W+1,Y+1,1),C=b.get(W+1,Y+1,2),t.intensity&&(K=t.intensity.get(W,Y));var K=t.intensity?t.intensity.get(W,Y):G+this.objectOffset[2];F[N++]=W,F[N++]=Y,F[N++]=X,F[N++]=Z,F[N++]=G,F[N++]=0,F[N++]=K,F[N++]=E,F[N++]=L,F[N++]=C,O[0]=Math.min(O[0],X+this.objectOffset[0]),O[1]=Math.min(O[1],Z+this.objectOffset[1]),O[2]=Math.min(O[2],G+this.objectOffset[2]),z=Math.min(z,K),I[0]=Math.max(I[0],X+this.objectOffset[0]),I[1]=Math.max(I[1],Z+this.objectOffset[1]),I[2]=Math.max(I[2],G+this.objectOffset[2]),D=Math.max(D,K),U+=1}}for(t.intensityBounds&&(z=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<N;o+=10)F[o]=(F[o]-z)/(D-z);this._vertexCount=U,this._coordinateBuffer.update(F.subarray(0,N)),s.freeFloat(F),s.free(b.data),this.bounds=[O,I],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===z&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[z,D]}if(\"levels\"in t){var J=t.levels;for(J=Array.isArray(J[0])?J.slice():[[],[],J],o=0;o<3;++o)J[o]=J[o].slice(),J[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(y=0;y<J[o].length;++y)J[o][y]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(J[o].length!==this.contourLevels[o].length){r=!0;break}for(y=0;y<J[o].length;++y)if(J[o][y]!==this.contourLevels[o][y]){r=!0;break t}}this.contourLevels=J}if(r){m=this._field,a=this.shape;for(var $=[],Q=0;Q<3;++Q){var tt=this.contourLevels[Q],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[Q],tt[o]);et.push($.length/5|0),U=0;t:for(y=0;y<it.cells.length;++y){var at=it.cells[y];for(H=0;H<2;++H){var ot=it.positions[at[H]],st=ot[0],lt=0|Math.floor(st),ut=st-lt,ct=ot[1],ft=0|Math.floor(ct),ht=ct-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var vt=(Q+dt+1)%3;for(V=0;V<2;++V){var gt=V?ut:1-ut;for(W=0|Math.min(Math.max(lt+V,0),a[0]),q=0;q<2;++q){var yt=q?ht:1-ht;if(Y=0|Math.min(Math.max(ft+q,0),a[1]),G=dt<2?this._field[vt].get(W,Y):(this.intensity.get(W,Y)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var mt=gt*yt;nt[dt]+=mt*G}}}if(pt){if(H>0){for(var xt=0;xt<5;++xt)$.pop();U-=1}continue t}$.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var bt=s.mallocFloat($.length);for(o=0;o<$.length;++o)bt[o]=$[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,u=(o+2)%3,c=this._field[o],f=this._field[l],p=this._field[u],d=h(c,r[o]),v=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<v.length;++e)for(var y=v[e],m=0;m<2;++m){var x=g[y[m]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,O=T*L,I=T*E,z=C*f.get(_,M)+P*f.get(_,S)+O*f.get(w,M)+I*f.get(w,S),D=C*p.get(_,M)+P*p.get(_,S)+O*p.get(w,M)+I*p.get(w,S);if(isNaN(z)||isNaN(D)){m&&(n-=1);break}a[2*n+0]=z,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},7766:function(t,e,r){\"use strict\";var n=r(9618),i=r(5298),a=r(1888);t.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");if(o||function(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}(t),\"number\"==typeof arguments[1])return g(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return g(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return function(t,e,r,n,i,a){var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new h(t,o,r,n,i,a)}(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return function(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=d(o,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var f,p,g=0;if(2===o.length)g=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])g=t.ALPHA;else if(2===o[2])g=t.LUMINANCE_ALPHA;else if(3===o[2])g=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,l=!1);var y=e.size;if(l)f=0===e.offset&&e.data.length===y?e.data:e.data.subarray(e.offset,e.offset+y);else{var m=[o[2],o[2]*o[0],1];p=a.malloc(y,r);var x=n(p,o,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?i.assign(x,e):c(x,e),f=p.subarray(0,y)}var b=v(t);return t.texImage2D(t.TEXTURE_2D,0,g,o[0],o[1],0,g,u,f),l||a.free(p),new h(t,b,o[0],o[1],g,u)}(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var c=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function v(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function g(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return f(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return f(this,t|=0,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t|=0,f(this,this._shape[0],t),t}}}),p.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},p.dispose=function(){this.gl.deleteTexture(this.handle)},p.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},p.setPixels=function(t,e,r,o){var s=this.gl;this.bind(),Array.isArray(e)?(o=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),o=o||0;var l=u(t)?t:t.raw;if(l)this._mipLevels.indexOf(o)<0?(s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,this.type,l),this._mipLevels.push(o)):s.texSubImage2D(s.TEXTURE_2D,o,e,r,this.format,this.type,l);else{if(!(t.shape&&t.stride&&t.data))throw new Error(\"gl-texture2d: Unsupported data type\");if(t.shape.length<2||e+t.shape[1]>this._shape[1]>>>o||r+t.shape[0]>this._shape[0]>>>o||e<0||r<0)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");!function(t,e,r,o,s,l,u,f){var h=f.dtype,p=f.shape.slice();if(p.length<2||p.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var v=0,g=0,y=d(p,f.stride.slice());if(\"float32\"===h?v=t.FLOAT:\"float64\"===h?(v=t.FLOAT,y=!1,h=\"float32\"):\"uint8\"===h?v=t.UNSIGNED_BYTE:(v=t.UNSIGNED_BYTE,y=!1,h=\"uint8\"),2===p.length)g=t.LUMINANCE,p=[p[0],p[1],1],f=n(f.data,p,[f.stride[0],f.stride[1],1],f.offset);else{if(3!==p.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===p[2])g=t.ALPHA;else if(2===p[2])g=t.LUMINANCE_ALPHA;else if(3===p[2])g=t.RGB;else{if(4!==p[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}p[2]}if(g!==t.LUMINANCE&&g!==t.ALPHA||s!==t.LUMINANCE&&s!==t.ALPHA||(g=s),g!==s)throw new Error(\"gl-texture2d: Incompatible texture format for setPixels\");var m=f.size,x=u.indexOf(o)<0;if(x&&u.push(o),v===l&&y)0===f.offset&&f.data.length===m?x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,f.data):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,f.data):x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,f.data.subarray(f.offset,f.offset+m)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,f.data.subarray(f.offset,f.offset+m));else{var b;b=l===t.FLOAT?a.mallocFloat32(m):a.mallocUint8(m);var 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i=this.computedMatrix,a=(Math.exp(this.computedRadius[0]),i[1]),o=i[5],s=i[9],l=u(a,o,s);a/=l,o/=l,s/=l;var c=i[0],f=i[4],h=i[8],p=c*a+f*o+h*s,d=u(c-=a*p,f-=o*p,h-=s*p),v=(c/=d)*e+a*r,g=(f/=d)*e+o*r,y=(h/=d)*e+s*r;this.center.move(t,v,g,y);var m=Math.exp(this.computedRadius[0]);m=Math.max(1e-4,m+n),this.radius.set(t,Math.log(m))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var a=1;\"number\"==typeof r&&(a=0|r),(a<0||a>3)&&(a=1);var o=(a+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[a],l=e[a+4],f=e[a+8];if(n){var h=Math.abs(s),p=Math.abs(l),d=Math.abs(f),v=Math.max(h,p,d);h===v?(s=s<0?-1:1,l=f=0):d===v?(f=f<0?-1:1,s=l=0):(l=l<0?-1:1,s=f=0)}else{var g=u(s,l,f);s/=g,l/=g,f/=g}var y,m,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*f,T=u(x-=s*w,b-=l*w,_-=f*w),k=l*(_/=T)-f*(b/=T),A=f*(x/=T)-s*_,M=s*b-l*x,S=u(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,H,G,W),this.radius.idle(t),this.up.jump(t,s,l,f),this.right.jump(t,x,b,_),2===a){var 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Sr=function(t,e){this.type=Xt,this.needle=t,this.haystack=e};Sr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Jt),n=e.parse(t[2],2,Jt);return r&&n?ae(r.type,[Xt,Yt,Wt,Gt,Jt])?new Sr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+re(r.type)+\" instead\"):null},Sr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!oe(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new xe(\"Expected first argument to be of type boolean, string, number or null, but found \"+re(ge(e))+\" instead.\");if(!oe(r,[\"string\",\"array\"]))throw new xe(\"Expected second argument to be of type array or string, but found \"+re(ge(r))+\" instead.\");return 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e={color:Zt,string:Yt,number:Wt,enum:Yt,boolean:Xt,formatted:Qt,resolvedImage:te};return\"array\"===t.type?ee(e[t.value]||Jt,t.length):e[t.type]}(e):void 0),n=r.parse(t,void 0,void 0,void 0,e&&\"string\"===e.type?{typeAnnotation:\"coerce\"}:void 0);return n?Xr(new un(n,e)):Zr(r.errors)}un.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._evaluator.globals=t,this._evaluator.feature=e,this._evaluator.featureState=r,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a,this.expression.evaluate(this._evaluator)},un.prototype.evaluate=function(t,e,r,n,i,a){this._evaluator.globals=t,this._evaluator.feature=e||null,this._evaluator.featureState=r||null,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a||null;try{var o=this.expression.evaluate(this._evaluator);if(null==o||\"number\"==typeof o&&o!=o)return this._defaultValue;if(this._enumValues&&!(o in this._enumValues))throw new xe(\"Expected value to be one of \"+Object.keys(this._enumValues).map((function(t){return JSON.stringify(t)})).join(\", \")+\", but found \"+JSON.stringify(o)+\" instead.\");return o}catch(t){return this._warningHistory[t.message]||(this._warningHistory[t.message]=!0,\"undefined\"!=typeof console&&console.warn(t.message)),this._defaultValue}};var hn=function(t,e){this.kind=t,this._styleExpression=e,this.isStateDependent=\"constant\"!==t&&!Xe(e.expression)};hn.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},hn.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)};var pn=function(t,e,r,n){this.kind=t,this.zoomStops=r,this._styleExpression=e,this.isStateDependent=\"camera\"!==t&&!Xe(e.expression),this.interpolationType=n};function dn(t,e){if(\"error\"===(t=fn(t,e)).result)return t;var r=t.value.expression,n=Ye(r);if(!n&&!Kr(e))return Zr([new qt(\"\",\"data expressions not supported\")]);var i=Ze(r,[\"zoom\"]);if(!i&&!Jr(e))return Zr([new qt(\"\",\"zoom expressions not supported\")]);var a=gn(r);if(!a&&!i)return Zr([new qt(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.')]);if(a instanceof qt)return Zr([a]);if(a instanceof wr&&!$r(e))return Zr([new qt(\"\",'\"interpolate\" expressions cannot be used with this property')]);if(!a)return Xr(new hn(n?\"constant\":\"source\",t.value));var o=a instanceof wr?a.interpolation:void 0;return Xr(new pn(n?\"camera\":\"composite\",t.value,a.labels,o))}pn.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},pn.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)},pn.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?wr.interpolationFactor(this.interpolationType,t,e,r):0};var vn=function(t,e){this._parameters=t,this._specification=e,jt(this,rn(this._parameters,this._specification))};function gn(t){var e=null;if(t instanceof Ar)e=gn(t.result);else if(t instanceof kr)for(var r=0,n=t.args;r<n.length;r+=1){var i=n[r];if(e=gn(i))break}else(t instanceof tr||t instanceof wr)&&t.input instanceof Ee&&\"zoom\"===t.input.name&&(e=t);return e instanceof qt||t.eachChild((function(t){var r=gn(t);r instanceof qt?e=r:!e&&r?e=new qt(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.'):e&&r&&e!==r&&(e=new qt(\"\",'Only one zoom-based \"step\" or \"interpolate\" subexpression may be used in an expression.'))})),e}function yn(t){var e=t.key,r=t.value,n=t.valueSpec||{},i=t.objectElementValidators||{},a=t.style,o=t.styleSpec,s=[],l=Qr(r);if(\"object\"!==l)return[new Bt(e,r,\"object expected, \"+l+\" found\")];for(var u in r){var c=u.split(\".\")[0],f=n[c]||n[\"*\"],h=void 0;if(i[c])h=i[c];else if(n[c])h=Hn;else if(i[\"*\"])h=i[\"*\"];else{if(!n[\"*\"]){s.push(new Bt(e,r[u],'unknown property \"'+u+'\"'));continue}h=Hn}s=s.concat(h({key:(e?e+\".\":e)+u,value:r[u],valueSpec:f,style:a,styleSpec:o,object:r,objectKey:u},r))}for(var p in n)i[p]||n[p].required&&void 0===n[p].default&&void 0===r[p]&&s.push(new Bt(e,r,'missing required property \"'+p+'\"'));return s}function mn(t){var e=t.value,r=t.valueSpec,n=t.style,i=t.styleSpec,a=t.key,o=t.arrayElementValidator||Hn;if(\"array\"!==Qr(e))return[new Bt(a,e,\"array expected, \"+Qr(e)+\" found\")];if(r.length&&e.length!==r.length)return[new Bt(a,e,\"array length \"+r.length+\" expected, length \"+e.length+\" found\")];if(r[\"min-length\"]&&e.length<r[\"min-length\"])return[new Bt(a,e,\"array length at least \"+r[\"min-length\"]+\" expected, length \"+e.length+\" found\")];var s={type:r.value,values:r.values};i.$version<7&&(s.function=r.function),\"object\"===Qr(r.value)&&(s=r.value);for(var l=[],u=0;u<e.length;u++)l=l.concat(o({array:e,arrayIndex:u,value:e[u],valueSpec:s,style:n,styleSpec:i,key:a+\"[\"+u+\"]\"}));return l}function xn(t){var e=t.key,r=t.value,n=t.valueSpec,i=Qr(r);return\"number\"===i&&r!=r&&(i=\"NaN\"),\"number\"!==i?[new Bt(e,r,\"number expected, \"+i+\" found\")]:\"minimum\"in n&&r<n.minimum?[new Bt(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Bt(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function bn(t){var e,r,n,i=t.valueSpec,a=Ut(t.value.type),o={},s=\"categorical\"!==a&&void 0===t.value.property,l=!s,u=\"array\"===Qr(t.value.stops)&&\"array\"===Qr(t.value.stops[0])&&\"object\"===Qr(t.value.stops[0][0]),c=yn({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===a)return[new Bt(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;return e=e.concat(mn({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:f})),\"array\"===Qr(r)&&0===r.length&&e.push(new Bt(t.key,r,\"array must have at least one stop\")),e},default:function(t){return Hn({key:t.key,value:t.value,valueSpec:i,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===a&&s&&c.push(new Bt(t.key,t.value,'missing required property \"property\"')),\"identity\"===a||t.value.stops||c.push(new Bt(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===a&&t.valueSpec.expression&&!$r(t.valueSpec)&&c.push(new Bt(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!Kr(t.valueSpec)?c.push(new Bt(t.key,t.value,\"property functions not supported\")):s&&!Jr(t.valueSpec)&&c.push(new Bt(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!u||void 0!==t.value.property||c.push(new Bt(t.key,t.value,'\"property\" property is required')),c;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==Qr(a))return[new Bt(s,a,\"array expected, \"+Qr(a)+\" found\")];if(2!==a.length)return[new Bt(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(u){if(\"object\"!==Qr(a[0]))return[new Bt(s,a,\"object expected, \"+Qr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new Bt(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new Bt(s,a,\"object stop key must have value\")];if(n&&n>Ut(a[0].zoom))return[new Bt(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Ut(a[0].zoom)!==n&&(n=Ut(a[0].zoom),r=void 0,o={}),e=e.concat(yn({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:xn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return cn(Vt(a[1]))?e.concat([new Bt(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(Hn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=Qr(t.value),l=Ut(t.value),u=null!==t.value?t.value:n;if(e){if(s!==e)return[new Bt(t.key,u,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Bt(t.key,u,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var c=\"number expected, \"+s+\" found\";return Kr(i)&&void 0===a&&(c+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Bt(t.key,u,c)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new Bt(t.key,u,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new Bt(t.key,u,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Bt(t.key,u,\"integer expected, found \"+l)]}}function _n(t){var e=(\"property\"===t.expressionContext?dn:fn)(Vt(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new Bt(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new Bt(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!Xe(r))return[new Bt(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!Xe(r))return[new Bt(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!Ze(r,[\"zoom\",\"feature-state\"]))return[new Bt(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!Ye(r))return[new Bt(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function wn(t){var e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Ut(r))&&i.push(new Bt(e,r,\"expected one of [\"+n.values.join(\", \")+\"], \"+JSON.stringify(r)+\" found\")):-1===Object.keys(n.values).indexOf(Ut(r))&&i.push(new Bt(e,r,\"expected one of [\"+Object.keys(n.values).join(\", \")+\"], \"+JSON.stringify(r)+\" found\")),i}function Tn(t){if(!0===t||!1===t)return!0;if(!Array.isArray(t)||0===t.length)return!1;switch(t[0]){case\"has\":return t.length>=2&&\"$id\"!==t[1]&&\"$type\"!==t[1];case\"in\":return t.length>=3&&(\"string\"!=typeof t[1]||Array.isArray(t[2]));case\"!in\":case\"!has\":case\"none\":return!1;case\"==\":case\"!=\":case\">\":case\">=\":case\"<\":case\"<=\":return 3!==t.length||Array.isArray(t[1])||Array.isArray(t[2]);case\"any\":case\"all\":for(var e=0,r=t.slice(1);e<r.length;e+=1){var n=r[e];if(!Tn(n)&&\"boolean\"!=typeof n)return!1}return!0;default:return!0}}vn.deserialize=function(t){return new vn(t._parameters,t._specification)},vn.serialize=function(t){return{_parameters:t._parameters,_specification:t._specification}};var kn={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function An(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};Tn(t)||(t=En(t));var e=fn(t,kn);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:Sn(t)}}function Mn(t,e){return t<e?-1:t>e?1:0}function Sn(t){if(!Array.isArray(t))return!1;if(\"within\"===t[0])return!0;for(var e=1;e<t.length;e++)if(Sn(t[e]))return!0;return!1}function En(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?Ln(t[1],t[2],\"==\"):\"!=\"===r?On(Ln(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?Ln(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(En))):\"all\"===r?[\"all\"].concat(t.slice(1).map(En)):\"none\"===r?[\"all\"].concat(t.slice(1).map(En).map(On)):\"in\"===r?Cn(t[1],t.slice(2)):\"!in\"===r?On(Cn(t[1],t.slice(2))):\"has\"===r?Pn(t[1]):\"!has\"===r?On(Pn(t[1])):\"within\"!==r||t}function Ln(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function Cn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(Mn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function Pn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function On(t){return[\"!\",t]}function In(t){return Tn(Vt(t.value))?_n(jt({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):zn(t)}function zn(t){var e=t.value,r=t.key;if(\"array\"!==Qr(e))return[new Bt(r,e,\"array expected, \"+Qr(e)+\" found\")];var n,i=t.styleSpec,a=[];if(e.length<1)return[new Bt(r,e,\"filter array must have at least 1 element\")];switch(a=a.concat(wn({key:r+\"[0]\",value:e[0],valueSpec:i.filter_operator,style:t.style,styleSpec:t.styleSpec})),Ut(e[0])){case\"<\":case\"<=\":case\">\":case\">=\":e.length>=2&&\"$type\"===Ut(e[1])&&a.push(new Bt(r,e,'\"$type\" cannot be use with operator \"'+e[0]+'\"'));case\"==\":case\"!=\":3!==e.length&&a.push(new Bt(r,e,'filter array for operator \"'+e[0]+'\" must have 3 elements'));case\"in\":case\"!in\":e.length>=2&&\"string\"!==(n=Qr(e[1]))&&a.push(new Bt(r+\"[1]\",e[1],\"string expected, \"+n+\" found\"));for(var o=2;o<e.length;o++)n=Qr(e[o]),\"$type\"===Ut(e[1])?a=a.concat(wn({key:r+\"[\"+o+\"]\",value:e[o],valueSpec:i.geometry_type,style:t.style,styleSpec:t.styleSpec})):\"string\"!==n&&\"number\"!==n&&\"boolean\"!==n&&a.push(new Bt(r+\"[\"+o+\"]\",e[o],\"string, number, or boolean expected, \"+n+\" found\"));break;case\"any\":case\"all\":case\"none\":for(var s=1;s<e.length;s++)a=a.concat(zn({key:r+\"[\"+s+\"]\",value:e[s],style:t.style,styleSpec:t.styleSpec}));break;case\"has\":case\"!has\":n=Qr(e[1]),2!==e.length?a.push(new Bt(r,e,'filter array for \"'+e[0]+'\" operator must have 2 elements')):\"string\"!==n&&a.push(new Bt(r+\"[1]\",e[1],\"string expected, \"+n+\" found\"));break;case\"within\":n=Qr(e[1]),2!==e.length?a.push(new Bt(r,e,'filter array for \"'+e[0]+'\" operator must have 2 elements')):\"object\"!==n&&a.push(new Bt(r+\"[1]\",e[1],\"object expected, \"+n+\" found\"))}return a}function Dn(t,e){var r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return Hn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var u,c=t.valueSpec||s[o];if(!c)return[new Bt(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Qr(a)&&Kr(c)&&!c.tokens&&(u=/^{([^}]+)}$/.exec(a)))return[new Bt(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(u[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new Bt(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&tn(Vt(a))&&\"identity\"===Ut(a.type)&&f.push(new Bt(r,a,'\"text-font\" does not support identity 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h=i.sources&&i.sources[r.source],p=h&&Ut(h.type);h?\"vector\"===p&&\"raster\"===s?e.push(new Bt(n,r.source,'layer \"'+r.id+'\" requires a raster source')):\"raster\"===p&&\"raster\"!==s?e.push(new Bt(n,r.source,'layer \"'+r.id+'\" requires a vector source')):\"vector\"!==p||r[\"source-layer\"]?\"raster-dem\"===p&&\"hillshade\"!==s?e.push(new Bt(n,r.source,\"raster-dem source can only be used with layer type 'hillshade'.\")):\"line\"!==s||!r.paint||!r.paint[\"line-gradient\"]||\"geojson\"===p&&h.lineMetrics||e.push(new Bt(n,r,'layer \"'+r.id+'\" specifies a line-gradient, which requires a GeoJSON source with `lineMetrics` enabled.')):e.push(new Bt(n,r,'layer \"'+r.id+'\" must specify a \"source-layer\"')):e.push(new Bt(n,r.source,'source \"'+r.source+'\" not found'))}else e.push(new Bt(n,r,'missing required property \"source\"'));return 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Arrows\"](t)&&(t>=11026&&t<=11055||t>=11088&&t<=11097||t>=11192&&t<=11243)||pi[\"CJK Symbols and Punctuation\"](t)||pi.Katakana(t)||pi[\"Private Use Area\"](t)||pi[\"CJK Compatibility Forms\"](t)||pi[\"Small Form Variants\"](t)||pi[\"Halfwidth and Fullwidth Forms\"](t)||8734===t||8756===t||8757===t||t>=9984&&t<=10087||t>=10102&&t<=10131||65532===t||65533===t)}(t))}function yi(t){return pi.Arabic(t)||pi[\"Arabic Supplement\"](t)||pi[\"Arabic Extended-A\"](t)||pi[\"Arabic Presentation Forms-A\"](t)||pi[\"Arabic Presentation Forms-B\"](t)}function mi(t){return t>=1424&&t<=2303||pi[\"Arabic Presentation Forms-A\"](t)||pi[\"Arabic Presentation Forms-B\"](t)}function xi(t,e){return!(!e&&mi(t)||t>=2304&&t<=3583||t>=3840&&t<=4255||pi.Khmer(t))}function bi(t){for(var e=0,r=t;e<r.length;e+=1)if(mi(r[e].charCodeAt(0)))return!0;return!1}var _i=\"deferred\",wi=\"loading\",Ti=\"loaded\",ki=\"error\",Ai=null,Mi=\"unavailable\",Si=null,Ei=function(t){t&&\"string\"==typeof t&&t.indexOf(\"NetworkError\")>-1&&(Mi=ki),Ai&&Ai(t)};function Li(){Ci.fire(new zt(\"pluginStateChange\",{pluginStatus:Mi,pluginURL:Si}))}var Ci=new Rt,Pi=function(){return Mi},Oi=function(){if(Mi!==_i||!Si)throw new Error(\"rtl-text-plugin cannot be downloaded unless a pluginURL is specified\");Mi=wi,Li(),Si&&Mt({url:Si},(function(t){t?Ei(t):(Mi=Ti,Li())}))},Ii={applyArabicShaping:null,processBidirectionalText:null,processStyledBidirectionalText:null,isLoaded:function(){return Mi===Ti||null!=Ii.applyArabicShaping},isLoading:function(){return Mi===wi},setState:function(t){Mi=t.pluginStatus,Si=t.pluginURL},isParsed:function(){return null!=Ii.applyArabicShaping&&null!=Ii.processBidirectionalText&&null!=Ii.processStyledBidirectionalText},getPluginURL:function(){return Si}},zi=function(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new hi,this.transition={})};zi.prototype.isSupportedScript=function(t){return function(t,e){for(var r=0,n=t;r<n.length;r+=1)if(!xi(n[r].charCodeAt(0),e))return!1;return!0}(t,Ii.isLoaded())},zi.prototype.crossFadingFactor=function(){return 0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},zi.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var Di=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(tn(t))return new vn(t,e);if(cn(t)){var r=dn(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=ue.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};Di.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},Di.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var Ri=function(t){this.property=t,this.value=new Di(t,void 0)};Ri.prototype.transitioned=function(t,e){return new Bi(this.property,this.value,e,p({},t.transition,this.transition),t.now)},Ri.prototype.untransitioned=function(){return new Bi(this.property,this.value,null,{},0)};var Fi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};Fi.prototype.getValue=function(t){return w(this._values[t].value.value)},Fi.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new Ri(this._values[t].property)),this._values[t].value=new Di(this._values[t].property,null===e?void 0:w(e))},Fi.prototype.getTransition=function(t){return w(this._values[t].transition)},Fi.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new Ri(this._values[t].property)),this._values[t].transition=w(e)||void 0},Fi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},Fi.prototype.transitioned=function(t,e){for(var r=new Ni(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},Fi.prototype.untransitioned=function(){for(var t=new Ni(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var Bi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};Bi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var Ni=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};Ni.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Vi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},Ni.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var ji=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};ji.prototype.getValue=function(t){return w(this._values[t].value)},ji.prototype.setValue=function(t,e){this._values[t]=new Di(this._values[t].property,null===e?void 0:w(e))},ji.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},ji.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Vi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var Ui=function(t,e,r){this.property=t,this.value=e,this.parameters=r};Ui.prototype.isConstant=function(){return\"constant\"===this.value.kind},Ui.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},Ui.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var Vi=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};Vi.prototype.get=function(t){return this._values[t]};var qi=function(t){this.specification=t};qi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},qi.prototype.interpolate=function(t,e,r){var n=rr[this.specification.type];return n?n(t,e,r):t};var Hi=function(t,e){this.specification=t,this.overrides=e};Hi.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new Ui(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new Ui(this,t.expression,e)},Hi.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new Ui(this,{kind:\"constant\",value:void 0},t.parameters);var n=rr[this.specification.type];return n?new Ui(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Hi.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var Gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new Ui(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new Ui(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new Ui(this,{kind:\"constant\",value:s},e)}return new Ui(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Hi),Wi=function(t){this.specification=t};Wi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return 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Vi(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate($n,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return x(t,Zi)?this._transitionablePaint.getTransition(t.slice(0,-11)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Jn,n,t,e,r))return!1}if(x(t,Zi))return this._transitionablePaint.setTransition(t.slice(0,-11),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),_(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&Qn(this,t.call(Zn,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Ft,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof Ui&&Kr(e.property.specification)&&(\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(Rt),Ji={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},$i=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Qi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function ta(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Ji[i].BYTES_PER_ELEMENT),o=r=ea(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:ea(r,Math.max(n,e)),alignment:e}}function ea(t,e){return Math.ceil(t/e)*e}Qi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Qi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Qi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Qi.prototype.clear=function(){this.length=0},Qi.prototype.resize=function(t){this.reserve(t),this.length=t},Qi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Qi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var ra=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Qi);ra.prototype.bytesPerElement=4,oi(\"StructArrayLayout2i4\",ra);var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new 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this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Qi);ia.prototype.bytesPerElement=12,oi(\"StructArrayLayout2i4i12\",ia);var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Qi);aa.prototype.bytesPerElement=8,oi(\"StructArrayLayout2i4ub8\",aa);var oa=function(t){function e(){t.apply(this,arguments)}return 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this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}($i);Ma.prototype.size=48;var Sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Ma(this,t)},e}(ga);oi(\"PlacedSymbolArray\",Sa);var Ea=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var 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r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return 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s=t;s<e;s++)this.paintVertexArray.emplace(s,r,n);this.maxValue=Math.max(this.maxValue,Math.abs(r),Math.abs(n))}},so.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},so.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},so.prototype.setUniform=function(t,e){var r=this.useIntegerZoom?Math.floor(e.zoom):e.zoom,n=f(this.expression.interpolationFactor(r,this.zoom,this.zoom+1),0,1);t.set(n)},so.prototype.getBinding=function(t,e,r){return new Ka(t,e)};var lo=function(t,e,r,n,i,a){this.expression=t,this.type=e,this.useIntegerZoom=r,this.zoom=n,this.layerId=a,this.zoomInPaintVertexArray=new i,this.zoomOutPaintVertexArray=new i};lo.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(t),this.zoomOutPaintVertexArray.resize(t),this._setPaintValues(n,t,e.patterns&&e.patterns[this.layerId],r)},lo.prototype.updatePaintArray=function(t,e,r,n,i){this._setPaintValues(t,e,r.patterns&&r.patterns[this.layerId],i)},lo.prototype._setPaintValues=function(t,e,r,n){if(n&&r){var i=r.min,a=r.mid,o=r.max,s=n[i],l=n[a],u=n[o];if(s&&l&&u)for(var c=t;c<e;c++)this.zoomInPaintVertexArray.emplace(c,l.tl[0],l.tl[1],l.br[0],l.br[1],s.tl[0],s.tl[1],s.br[0],s.br[1],l.pixelRatio,s.pixelRatio),this.zoomOutPaintVertexArray.emplace(c,l.tl[0],l.tl[1],l.br[0],l.br[1],u.tl[0],u.tl[1],u.br[0],u.br[1],l.pixelRatio,u.pixelRatio)}},lo.prototype.upload=function(t){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=t.createVertexBuffer(this.zoomInPaintVertexArray,Fa.members,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=t.createVertexBuffer(this.zoomOutPaintVertexArray,Fa.members,this.expression.isStateDependent))},lo.prototype.destroy=function(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()};var uo=function(t,e,r){this.binders={},this._buffers=[];var n=[];for(var i in t.paint._values)if(r(i)){var a=t.paint.get(i);if(a instanceof Ui&&Kr(a.property.specification)){var o=fo(i,t.type),s=a.value,l=a.property.specification.type,u=a.property.useIntegerZoom,c=a.property.specification[\"property-type\"],f=\"cross-faded\"===c||\"cross-faded-data-driven\"===c;if(\"constant\"===s.kind)this.binders[i]=f?new ao(s.value,o):new io(s.value,o,l),n.push(\"/u_\"+i);else if(\"source\"===s.kind||f){var h=ho(i,l,\"source\");this.binders[i]=f?new lo(s,l,u,e,h,t.id):new oo(s,o,l,h),n.push(\"/a_\"+i)}else{var p=ho(i,l,\"composite\");this.binders[i]=new so(s,o,l,u,e,p),n.push(\"/z_\"+i)}}}this.cacheKey=n.sort().join(\"\")};uo.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof oo||e instanceof so?e.maxValue:0},uo.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a in this.binders){var o=this.binders[a];(o instanceof oo||o instanceof so||o instanceof lo)&&o.populatePaintArray(t,e,r,n,i)}},uo.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders){var n=this.binders[r];n instanceof ao&&n.setConstantPatternPositions(t,e)}},uo.prototype.updatePaintArrays=function(t,e,r,n,i){var a=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var u=l[s],c=r.feature(u.index);for(var f in this.binders){var h=this.binders[f];if((h instanceof oo||h instanceof so||h instanceof lo)&&!0===h.expression.isStateDependent){var p=n.paint.get(f);h.expression=p.value,h.updatePaintArray(u.start,u.end,c,t[o],i),a=!0}}}return a},uo.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof io||r instanceof ao)&&t.push.apply(t,r.uniformNames.map((function(t){return\"#define HAS_UNIFORM_\"+t})))}return t},uo.prototype.getBinderAttributes=function(){var t=[];for(var e in this.binders){var r=this.binders[e];if(r instanceof oo||r instanceof so)for(var n=0;n<r.paintVertexAttributes.length;n++)t.push(r.paintVertexAttributes[n].name);else if(r instanceof lo)for(var i=0;i<Fa.members.length;i++)t.push(Fa.members[i].name)}return t},uo.prototype.getBinderUniforms=function(){var t=[];for(var e in this.binders){var r=this.binders[e];if(r instanceof io||r instanceof ao||r instanceof so)for(var n=0,i=r.uniformNames;n<i.length;n+=1){var a=i[n];t.push(a)}}return t},uo.prototype.getPaintVertexBuffers=function(){return this._buffers},uo.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var i=this.binders[n];if(i instanceof io||i instanceof ao||i instanceof so)for(var a=0,o=i.uniformNames;a<o.length;a+=1){var s=o[a];if(e[s]){var l=i.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},uo.prototype.setUniforms=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.name,l=o.property,u=o.binding;this.binders[l].setUniform(u,n,r.get(l),s)}},uo.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof lo){var 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u=t.readVarint();n=7&u,i=u>>3}if(i--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new a(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},Ys.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,u=-1/0;t.pos<e;){if(n<=0){var c=t.readVarint();r=7&c,n=c>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>u&&(u=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,u]},Ys.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),u=Ys.types[this.type];function c(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];c(l=f);break;case 2:for(n=0;n<l.length;n++)c(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=Zs(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}return r&&i.push(r),i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)c(l[n][i])}1===l.length?l=l[0]:u=\"Multi\"+u;var h={type:\"Feature\",geometry:{type:u,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var Ks=Js;function Js(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields($s,this,e),this.length=this._features.length}function $s(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){for(var e=null,r=t.readVarint()+t.pos;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Qs(t,e,r){if(3===t){var n=new Ks(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Js.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new Ws(this._pbf,e,this.extent,this._keys,this._values)};var tl={VectorTile:function(t,e){this.layers=t.readFields(Qs,{},e)},VectorTileFeature:Ws,VectorTileLayer:Ks},el=tl.VectorTileFeature.types,rl=Math.pow(2,13);function nl(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*rl)+o,i*rl*2,a*rl*2,Math.round(s))}var il=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new ia,this.indexArray=new va,this.programConfigurations=new co(t.layers,t.zoom),this.segments=new Da,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function al(t,e){return t.x===e.x&&(t.x<0||t.x>po)||t.y===e.y&&(t.y<0||t.y>po)}il.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=Ns(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,u=a.sourceLayerIndex,c=this.layers[0]._featureFilter.needGeometry,f=mo(o,c);if(this.layers[0]._featureFilter.filter(new zi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:u,index:l,geometry:c?f.geometry:yo(o),properties:o.properties,type:o.type,patterns:{}};this.hasPattern?this.features.push(js(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,u,this.index,!0)}}},il.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},il.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},il.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},il.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},il.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Gs),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},il.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},il.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=Fs(e,500);a<o.length;a+=1){for(var s=o[a],l=0,u=0,c=s;u<c.length;u+=1)l+=c[u].length;for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!((O=d).every((function(t){return t.x<0}))||O.every((function(t){return t.x>po}))||O.every((function(t){return t.y<0}))||O.every((function(t){return t.y>po}))))for(var v=0,g=0;g<d.length;g++){var y=d[g];if(g>=1){var m=d[g-1];if(!al(y,m)){f.vertexLength+4>Da.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=y.sub(m)._perp()._unit(),b=m.dist(y);v+b>32768&&(v=0),nl(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,v),nl(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,v),v+=b,nl(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,0,v),nl(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,1,v);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>Da.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===el[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];nl(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=as(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}var O;this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},oi(\"FillExtrusionBucket\",il,{omit:[\"layers\",\"features\"]});var ol={paint:new Xi({\"fill-extrusion-opacity\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Hi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new Gi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Hi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Hi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new qi(Ft[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},sl=function(t){function e(e){t.call(this,e,ol)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new il(t)},e.prototype.queryRadius=function(){return Io(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s,l){var u=zo(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),c=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var i=[],o=0,s=t;o<s.length;o+=1){var l=s[o],u=[l.x,l.y,n,1];qo(u,u,e),i.push(new a(u[0]/u[3],u[1]/u[3]))}return i}(u,l,0,0),p=function(t,e,r,n){for(var i=[],o=[],s=n[8]*e,l=n[9]*e,u=n[10]*e,c=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,v=0,g=t;v<g.length;v+=1){for(var y=[],m=[],x=0,b=g[v];x<b.length;x+=1){var _=b[x],w=_.x,T=_.y,k=n[0]*w+n[4]*T+n[12],A=n[1]*w+n[5]*T+n[13],M=n[2]*w+n[6]*T+n[14],S=n[3]*w+n[7]*T+n[15],E=M+u,L=S+c,C=k+f,P=A+h,O=M+p,I=S+d,z=new a((k+s)/L,(A+l)/L);z.z=E/L,y.push(z);var D=new a(C/I,P/I);D.z=O/I,m.push(D)}i.push(y),o.push(m)}return[i,o]}(n,f,c,l);return function(t,e,r){var n=1/0;To(r,e)&&(n=ul(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],u=a[s+1],c=o[s],f=[l,u,o[s+1],c,l];_o(r,f)&&(n=Math.min(n,ul(r,f)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Ki);function ll(t,e){return t.x*e.x+t.y*e.y}function ul(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),u=o.sub(i),c=ll(s,s),f=ll(s,l),h=ll(l,l),p=ll(u,s),d=ll(u,l),v=c*h-f*f,g=(h*p-f*d)/v,y=(c*d-f*p)/v,m=1-g-y,x=i.z*m+r.z*g+a.z*y;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var cl=ta([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,fl=ta([{name:\"a_uv_x\",components:1,type:\"Float32\"},{name:\"a_split_index\",components:1,type:\"Float32\"}]).members,hl=tl.VectorTileFeature.types,pl=Math.cos(Math.PI/180*37.5),dl=Math.pow(2,14)/.5,vl=function(t){var e=this;this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.lineClipsArray=[],this.gradients={},this.layers.forEach((function(t){e.gradients[t.id]={}})),this.layoutVertexArray=new aa,this.layoutVertexArray2=new oa,this.indexArray=new va,this.programConfigurations=new co(t.layers,t.zoom),this.segments=new Da,this.maxLineLength=0,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};vl.prototype.populate=function(t,e,r){this.hasPattern=Ns(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,u=s.id,c=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p=mo(l,h);if(this.layers[0]._featureFilter.filter(new zi(this.zoom),p,r)){var d=n?n.evaluate(p,{},r):void 0,v={id:u,properties:l.properties,type:l.type,sourceLayerIndex:f,index:c,geometry:h?p.geometry:yo(l),patterns:{},sortKey:d};i.push(v)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,y=i;g<y.length;g+=1){var m=y[g],x=m,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=js(\"line\",this.layers,m,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(m,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},vl.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},vl.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},vl.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},vl.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},vl.prototype.upload=function(t){this.uploaded||(0!==this.layoutVertexArray2.length&&(this.layoutVertexBuffer2=t.createVertexBuffer(this.layoutVertexArray2,fl)),this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,cl),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},vl.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},vl.prototype.lineFeatureClips=function(t){if(t.properties&&t.properties.hasOwnProperty(\"mapbox_clip_start\")&&t.properties.hasOwnProperty(\"mapbox_clip_end\"))return{start:+t.properties.mapbox_clip_start,end:+t.properties.mapbox_clip_end}},vl.prototype.addFeature=function(t,e,r,n,i){var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),u=a.get(\"line-round-limit\");this.lineClips=this.lineFeatureClips(t);for(var c=0,f=e;c<f.length;c+=1){var h=f[c];this.addLine(h,t,o,s,l,u)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},vl.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,this.lineClips){this.lineClipsArray.push(this.lineClips);for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance(),this.maxLineLength=Math.max(this.maxLineLength,this.totalDistance)}for(var s=\"Polygon\"===hl[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var u=0;u<l-1&&t[u].equals(t[u+1]);)u++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var c,f=this.overscaling<=16?15*po/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,v=void 0,g=void 0;this.e1=this.e2=-1,s&&(c=t[l-2],g=t[u].sub(c)._unit()._perp());for(var y=u;y<l;y++)if(!(d=y===l-1?s?t[u+1]:void 0:t[y+1])||!t[y].equals(d)){g&&(v=g),c&&(p=c),c=t[y],g=d?d.sub(c)._unit()._perp():v;var m=(v=v||g).add(g);0===m.x&&0===m.y||m._unit();var x=v.x*g.x+v.y*g.y,b=m.x*g.x+m.y*g.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<pl&&p&&d,k=v.x*g.y-v.y*g.x>0;if(T&&y>u){var A=c.dist(p);if(A>2*f){var M=c.sub(c.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,v,0,0,h),p=M}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,c),\"miter\"===E)m._mult(_),this.addCurrentVertex(c,m,0,0,h);else if(\"flipbevel\"===E){if(_>100)m=g.mult(-1);else{var L=_*v.add(g).mag()/v.sub(g).mag();m._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(c,m,0,0,h),this.addCurrentVertex(c,m.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,O=k?0:C;if(p&&this.addCurrentVertex(c,v,P,O,h),\"fakeround\"===E)for(var I=Math.round(180*w/Math.PI/20),z=1;z<I;z++){var D=z/I;if(.5!==D){var R=D-.5;D+=D*R*(D-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=g.sub(v)._mult(D)._add(v)._unit()._mult(k?-1:1);this.addHalfVertex(c,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(c,g,-P,-O,h)}else if(\"butt\"===E)this.addCurrentVertex(c,m,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(c,m,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(c,v,0,0,h),this.addCurrentVertex(c,v,1,1,h,!0)),d&&(this.addCurrentVertex(c,g,-1,-1,h,!0),this.addCurrentVertex(c,g,0,0,h)));if(T&&y<l-1){var N=c.dist(d);if(N>2*f){var j=c.add(d.sub(c)._mult(f/N)._round());this.updateDistance(c,j),this.addCurrentVertex(j,g,0,0,h),c=j}}}}},vl.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var 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e=Fl(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==Il.Bytes)return t.push(this.readFixed64());var e=Fl(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==Il.Bytes)return t.push(this.readSFixed64());var e=Fl(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===Il.Varint)for(;this.buf[this.pos++]>127;);else if(e===Il.Bytes)this.pos=this.readVarint()+this.pos;else if(e===Il.Fixed32)this.pos+=4;else{if(e!==Il.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return this.length=this.pos,this.pos=0,this.buf.subarray(0,this.length)},writeFixed32:function(t){this.realloc(4),Kl(this.buf,t,this.pos),this.pos+=4},writeSFixed32:function(t){this.realloc(4),Kl(this.buf,t,this.pos),this.pos+=4},writeFixed64:function(t){this.realloc(8),Kl(this.buf,-1&t,this.pos),Kl(this.buf,Math.floor(t*Dl),this.pos+4),this.pos+=8},writeSFixed64:function(t){this.realloc(8),Kl(this.buf,-1&t,this.pos),Kl(this.buf,Math.floor(t*Dl),this.pos+4),this.pos+=8},writeVarint:function(t){(t=+t||0)>268435455||t<0?function(t,e){var r,n;if(t>=0?(r=t%4294967296|0,n=t/4294967296|0):(n=~(-t/4294967296),4294967295^(r=~(-t%4294967296))?r=r+1|0:(r=0,n=n+1|0)),t>=0x10000000000000000||t<-0x10000000000000000)throw new Error(\"Given varint doesn't fit into 10 bytes\");e.realloc(10),function(t,e,r){r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos]=127&t}(r,0,e),function(t,e){var r=(7&t)<<4;e.buf[e.pos++]|=r|((t>>>=3)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t)))))}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&Nl(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),Pl(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),Pl(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&Nl(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,Il.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,jl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Ul,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,Hl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,Vl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,ql,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,Gl,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,Wl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,Yl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,Xl,e)},writeBytesField:function(t,e){this.writeTag(t,Il.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,Il.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,Il.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,Il.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,Il.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,Il.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,Il.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,Il.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,Il.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,Il.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var $l=3;function Ql(t,e,r){1===t&&r.readMessage(tu,e)}function tu(t,e,r){if(3===t){var n=r.readMessage(eu,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,u=n.top,c=n.advance;e.push({id:i,bitmap:new Jo({width:o+2*$l,height:s+2*$l},a),metrics:{width:o,height:s,left:l,top:u,advance:c}})}}function eu(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}var ru=$l;function nu(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,u=0,c=t;u<c.length;u+=1)for(var f=c[u],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else f.h===p.h?(p.x+=f.w,p.w-=f.w):f.w===p.w?(p.y+=f.h,p.h-=f.h):(o.push({x:p.x+f.w,y:p.y,w:p.w-f.w,h:f.h}),p.y+=f.h,p.h-=f.h);break}}return{w:s,h:l,fill:e/(s*l)||0}}var iu=1,au=function(t,e){var r=e.pixelRatio,n=e.version,i=e.stretchX,a=e.stretchY,o=e.content;this.paddedRect=t,this.pixelRatio=r,this.stretchX=i,this.stretchY=a,this.content=o,this.version=n},ou={tl:{configurable:!0},br:{configurable:!0},tlbr:{configurable:!0},displaySize:{configurable:!0}};ou.tl.get=function(){return[this.paddedRect.x+iu,this.paddedRect.y+iu]},ou.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-iu,this.paddedRect.y+this.paddedRect.h-iu]},ou.tlbr.get=function(){return this.tl.concat(this.br)},ou.displaySize.get=function(){return[(this.paddedRect.w-2*iu)/this.pixelRatio,(this.paddedRect.h-2*iu)/this.pixelRatio]},Object.defineProperties(au.prototype,ou);var su=function(t,e){var r={},n={};this.haveRenderCallbacks=[];var i=[];this.addImages(t,r,i),this.addImages(e,n,i);var a=nu(i),o=a.w,s=a.h,l=new $o({width:o||1,height:s||1});for(var u in t){var c=t[u],f=r[u].paddedRect;$o.copy(c.data,l,{x:0,y:0},{x:f.x+iu,y:f.y+iu},c.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,v=d.x+iu,g=d.y+iu,y=p.data.width,m=p.data.height;$o.copy(p.data,l,{x:0,y:0},{x:v,y:g},p.data),$o.copy(p.data,l,{x:0,y:m-1},{x:v,y:g-1},{width:y,height:1}),$o.copy(p.data,l,{x:0,y:0},{x:v,y:g+m},{width:y,height:1}),$o.copy(p.data,l,{x:y-1,y:0},{x:v-1,y:g},{width:1,height:m}),$o.copy(p.data,l,{x:0,y:0},{x:v+y,y:g},{width:1,height:m})}this.image=l,this.iconPositions=r,this.patternPositions=n};su.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2*iu,h:i.data.height+2*iu};r.push(a),e[n]=new au(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},su.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},su.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},oi(\"ImagePosition\",au),oi(\"ImageAtlas\",su);var lu={horizontal:1,vertical:2,horizontalOnly:3},uu=-17;var cu=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};cu.forText=function(t,e){var r=new cu;return r.scale=t||1,r.fontStack=e,r},cu.forImage=function(t){var e=new cu;return e.imageName=t,e};var fu=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function hu(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=fu.fromFeature(t,i);f===lu.vertical&&y.verticalizePunctuation();var m=Ii.processBidirectionalText,x=Ii.processStyledBidirectionalText;if(m&&1===y.sections.length){g=[];for(var b=0,_=m(y.toString(),bu(y,u,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new fu;T.text=w,T.sections=y.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);g.push(T)}}else if(x){g=[];for(var A=0,M=x(y.text,y.sectionIndex,bu(y,u,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new fu;E.text=S[0],E.sectionIndex=S[1],E.sections=y.sections,g.push(E)}}else g=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(y,bu(y,u,a,e,n,p,d));var L=[],C={positionedLines:L,text:y.toString(),top:c[1],bottom:c[1],left:c[0],right:c[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=0,p=uu,d=0,v=0,g=\"right\"===s?1:\"left\"===s?0:.5,y=0,m=0,x=i;m<x.length;m+=1){var b=x[m];b.trim();var _=b.getMaxScale(),w=(_-1)*Ll,T={positionedGlyphs:[],lineOffset:0};t.positionedLines[y]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,O=null,I=null,z=Ll,D=!(l===lu.horizontal||!c&&!vi(L)||c&&(pu[L]||yi(L)));if(S.imageName){var R=n[S.imageName];if(!R)continue;I=S.imageName,t.iconsInText=t.iconsInText||!0,O=R.paddedRect;var F=R.displaySize;S.scale=S.scale*Ll/f,P={width:F[0],height:F[1],left:iu,top:-ru,advance:D?F[1]:F[0]},C=w+(Ll-F[1]*S.scale),z=P.advance;var B=D?F[0]*S.scale-Ll*_:F[1]*S.scale-Ll*_;B>0&&B>A&&(A=B)}else{var N=r[S.fontStack],j=N&&N[L];if(j&&j.rect)O=j.rect,P=j.metrics;else{var U=e[S.fontStack],V=U&&U[L];if(!V)continue;P=V.metrics}C=(_-S.scale)*Ll}D?(t.verticalizable=!0,k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=z*S.scale+u):(k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=P.advance*S.scale+u)}if(0!==k.length){var q=h-u;d=Math.max(q,d),wu(k,0,k.length-1,g,A)}h=0;var H=a*_+A;T.lineOffset=Math.max(A,w),p+=H,v=Math.max(H,v),++y}else p+=a,++y}var G=p-uu,W=_u(o),Y=W.horizontalAlign,X=W.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var u=(e-r)*i,c=0;c=a!==o?-s*n-uu:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=0,d=h[f].positionedGlyphs;p<d.length;p+=1){var v=d[p];v.x+=u,v.y+=c}})(t.positionedLines,g,Y,X,d,v,a,G,i.length),t.top+=-X*G,t.bottom=t.top+G,t.left+=-Y*d,t.right=t.left+d}(C,e,r,n,g,o,s,l,f,u,h,v),!function(t){for(var e=0,r=t;e<r.length;e+=1)if(0!==r[e].positionedGlyphs.length)return!1;return!0}(L)&&C}fu.fromFeature=function(t,e){for(var r=new fu,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},fu.prototype.length=function(){return this.text.length},fu.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},fu.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},fu.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},fu.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;n&&gi(n)&&!El[t[r+1]]||i&&gi(i)&&!El[t[r-1]]||!El[t[r]]?e+=t[r]:e+=El[t[r]]}return e}(this.text)},fu.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&pu[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&pu[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},fu.prototype.substring=function(t,e){var r=new fu;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},fu.prototype.toString=function(){return this.text},fu.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce((function(e,r){return 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wu(t,e,r,n,i){if(n||i)for(var a=t[r],o=a.metrics.advance*a.scale,s=(t[r].x+o)*n,l=e;l<=r;l++)t[l].x-=s,t[l].y+=i}function Tu(t,e,r,n,i,a){var o,s=t.image;if(s.content){var l=s.content,u=s.pixelRatio||1;o=[l[0]/u,l[1]/u,s.displaySize[0]-l[2]/u,s.displaySize[1]-l[3]/u]}var c,f,h,p,d=e.left*a,v=e.right*a;\"width\"===r||\"both\"===r?(p=i[0]+d-n[3],f=i[0]+v+n[1]):f=(p=i[0]+(d+v-s.displaySize[0])/2)+s.displaySize[0];var g=e.top*a,y=e.bottom*a;return\"height\"===r||\"both\"===r?(c=i[1]+g-n[0],h=i[1]+y+n[2]):h=(c=i[1]+(g+y-s.displaySize[1])/2)+s.displaySize[1],{image:s,top:c,right:f,bottom:h,left:p,collisionPadding:o}}du[10]=!0,du[32]=!0,du[38]=!0,du[40]=!0,du[41]=!0,du[43]=!0,du[45]=!0,du[47]=!0,du[173]=!0,du[183]=!0,du[8203]=!0,du[8208]=!0,du[8211]=!0,du[8231]=!0;var ku=function(t){function e(e,r,n,i){t.call(this,e,r),this.angle=n,void 0!==i&&(this.segment=i)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.clone=function(){return new 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i=t.interpolationType,a=t.minZoom,o=t.maxZoom,s=i?f(wr.interpolationFactor(i,e,a,o),0,1):0;\"camera\"===t.kind?n=er(t.minSize,t.maxSize,s):r=s}return{uSizeT:r,uSize:n}}var Lu=Object.freeze({__proto__:null,getSizeData:Mu,evaluateSizeForFeature:Su,evaluateSizeForZoom:Eu,SIZE_PACK_FACTOR:Au});function Cu(t,e,r,n,i){if(void 0===e.segment)return!0;for(var a=e,o=e.segment+1,s=0;s>-r/2;){if(--o<0)return!1;s-=t[o].dist(a),a=t[o]}s+=t[o].dist(t[o+1]),o++;for(var l=[],u=0;s<r/2;){var c=t[o-1],f=t[o],h=t[o+1];if(!h)return!1;var p=c.angleTo(f)-f.angleTo(h);for(p=Math.abs((p+3*Math.PI)%(2*Math.PI)-Math.PI),l.push({distance:s,angleDelta:p}),u+=p;s-l[0].distance>n;)u-=l.shift().angleDelta;if(u>i)return!1;o++,s+=f.dist(h)}return!0}function Pu(t){for(var e=0,r=0;r<t.length-1;r++)e+=t[r].dist(t[r+1]);return e}function Ou(t,e,r){return t?.6*e*r:0}function Iu(t,e){return Math.max(t?t.right-t.left:0,e?e.right-e.left:0)}function zu(t,e,r,n,i,a){for(var 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a(0,0);c.push({tl:z,tr:D,bl:R,br:F,tex:y,writingMode:e.writingMode,glyphOffset:S,sectionIndex:g.sectionIndex,isSDF:x,pixelOffsetTL:Y,pixelOffsetBR:X,minFontScaleX:0,minFontScaleY:0})}}return c}(0,r,l,i,o,s,n,t.allowVerticalPlacement),y=t.textSizeData,m=null;\"source\"===y.kind?(m=[Au*i.layout.get(\"text-size\").evaluate(s,{})])[0]>ec&&k(t.layerIds[0]+': Value for \"text-size\" is >= '+tc+'. Reduce your \"text-size\".'):\"composite\"===y.kind&&((m=[Au*d.compositeTextSizes[0].evaluate(s,{},v),Au*d.compositeTextSizes[1].evaluate(s,{},v)])[0]>ec||m[1]>ec)&&k(t.layerIds[0]+': Value for \"text-size\" is >= '+tc+'. Reduce your \"text-size\".'),t.addSymbols(t.text,g,m,l,o,s,c,e,u.lineStartIndex,u.lineLength,p,v);for(var x=0,b=f;x<b.length;x+=1)h[b[x]]=t.text.placedSymbolArray.length-1;return 4*g.length}function nc(t){for(var e in t)return t[e];return null}function ic(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])<r)return!0}else i[e]=[];return i[e].push(n),!1}var ac=tl.VectorTileFeature.types,oc=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function sc(t,e,r,n,i,a,o,s,l,u,c,f,h){var p=s?Math.min(ec,Math.round(s[0])):0,d=s?Math.min(ec,Math.round(s[1])):0;t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,(p<<1)+(l?1:0),d,16*u,16*c,256*f,256*h)}function lc(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}function uc(t){for(var e=0,r=t.sections;e<r.length;e+=1)if(bi(r[e].text))return!0;return!1}var cc=function(t){this.layoutVertexArray=new la,this.indexArray=new va,this.programConfigurations=t,this.segments=new Da,this.dynamicLayoutVertexArray=new ua,this.opacityVertexArray=new ca,this.placedSymbolArray=new Sa};cc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},cc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,wl.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Tl.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,oc,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},cc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},oi(\"SymbolBuffers\",cc);var fc=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new Da,this.collisionVertexArray=new da};fc.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,kl.members,!0)},fc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},oi(\"CollisionBuffers\",fc);var hc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=Bo([]),this.placementViewportMatrix=Bo([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Mu(this.zoom,e[\"text-size\"]),this.iconSizeData=Mu(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.canOverlap=r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\"),this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&this.canOverlap,\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return lu[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};hc.prototype.createArrays=function(){this.text=new cc(new co(this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new cc(new co(this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new Ca,this.lineVertexArray=new Pa,this.symbolInstances=new La},hc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=El[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},hc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof he&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),u=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,c=i.get(\"symbol-sort-key\");if(this.features=[],l||u){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new zi(this.zoom),v=0,g=t;v<g.length;v+=1){var y=g[v],m=y.feature,x=y.id,b=y.index,_=y.sourceLayerIndex,w=n._featureFilter.needGeometry,T=mo(m,w);if(n._featureFilter.filter(d,T,r)){w||(T.geometry=yo(m));var k=void 0;if(l){var A=n.getValueAndResolveTokens(\"text-field\",T,r,p),M=he.factory(A);uc(M)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===Pi()||this.hasRTLText&&Ii.isParsed())&&(k=Sl(M,n,T))}var S=void 0;if(u){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof pe?E:pe.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?c.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:T.geometry,properties:m.properties,type:ac[m.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),O=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(lu.vertical)>=0;for(var I=0,z=k.sections;I<z.length;I+=1){var D=z[I];if(D.image)f[D.image.name]=!0;else{var R=di(k.toString()),F=D.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,O,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var u=0;u<t.length;u++){var c=t[u],f=c.geometry,h=c.text?c.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var v=s(p,d,f),g=o(p,d,n[v].geometry);delete e[p],delete r[d],r[l(h,n[g].geometry,!0)]=g,n[v].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(u),e[p]=i-1,r[d]=i-1)}else a(u)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},hc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},hc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},hc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},hc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},hc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},hc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},hc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var u=a[l];this.lineVertexArray.emplaceBack(u.x,u.y,u.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},hc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,this.canOverlap?a.sortKey:void 0),v=this.glyphOffsetArray.length,g=d.vertexLength,y=this.allowVerticalPlacement&&o===lu.vertical?Math.PI/2:0,m=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,O=b.sectionIndex,I=d.vertexLength,z=C[1];sc(p,s.x,s.y,_.x,z+_.y,A.x,A.y,r,P,M.x,M.y,E,L),sc(p,s.x,s.y,w.x,z+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),sc(p,s.x,s.y,T.x,z+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),sc(p,s.x,s.y,k.x,z+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),lc(t.dynamicLayoutVertexArray,s,y),h.emplaceBack(I,I+1,I+2),h.emplaceBack(I+1,I+2,I+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&O===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,m&&m[O])}t.placedSymbolArray.emplaceBack(s.x,s.y,v,this.glyphOffsetArray.length-v,g,l,u,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,c)},hc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},hc.prototype.addCollisionDebugVertices=function(t,e,r,n,i,o,s){var l=i.segments.prepareSegment(4,i.layoutVertexArray,i.indexArray),u=l.vertexLength,c=i.layoutVertexArray,f=i.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(c,f,o,h,p,new a(t,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,n)),this._addCollisionDebugVertex(c,f,o,h,p,new a(t,n)),l.vertexLength+=4;var d=i.indexArray;d.emplaceBack(u,u+1),d.emplaceBack(u+1,u+2),d.emplaceBack(u+2,u+3),d.emplaceBack(u+3,u),l.primitiveLength+=4},hc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,u=a.y2;this.addCollisionDebugVertices(o,s,l,u,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},hc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new fc(ha,Al.members,_a),this.iconCollisionBox=new fc(ha,Al.members,_a);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},hc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var u={},c=e;c<r;c++){var f=t.get(c);u.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},u.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);u.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},u.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var v=t.get(d);u.iconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},u.iconFeatureIndex=v.featureIndex;break}for(var g=s;g<l;g++){var y=t.get(g);u.verticalIconBox={x1:y.x1,y1:y.y1,x2:y.x2,y2:y.y2,anchorPointX:y.anchorPointX,anchorPointY:y.anchorPointY},u.verticalIconFeatureIndex=y.featureIndex;break}return u},hc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},hc.prototype.hasTextData=function(){return this.text.segments.get().length>0},hc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},hc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},hc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},hc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},hc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},hc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},hc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},hc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},oi(\"SymbolBucket\",hc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),hc.MAX_GLYPHS=65535,hc.addDynamicAttributes=lc;var pc=new Xi({\"symbol-placement\":new qi(Ft.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new qi(Ft.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new qi(Ft.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Hi(Ft.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new qi(Ft.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new qi(Ft.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new qi(Ft.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new qi(Ft.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new qi(Ft.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Hi(Ft.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new qi(Ft.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new qi(Ft.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Hi(Ft.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Hi(Ft.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new qi(Ft.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new qi(Ft.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Hi(Ft.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Hi(Ft.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new qi(Ft.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new qi(Ft.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new qi(Ft.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Hi(Ft.layout_symbol[\"text-field\"]),\"text-font\":new Hi(Ft.layout_symbol[\"text-font\"]),\"text-size\":new Hi(Ft.layout_symbol[\"text-size\"]),\"text-max-width\":new Hi(Ft.layout_symbol[\"text-max-width\"]),\"text-line-height\":new qi(Ft.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Hi(Ft.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Hi(Ft.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Hi(Ft.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new qi(Ft.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Hi(Ft.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new qi(Ft.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new qi(Ft.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Hi(Ft.layout_symbol[\"text-rotate\"]),\"text-padding\":new qi(Ft.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new qi(Ft.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Hi(Ft.layout_symbol[\"text-transform\"]),\"text-offset\":new Hi(Ft.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new qi(Ft.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new qi(Ft.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new qi(Ft.layout_symbol[\"text-optional\"])}),dc={paint:new Xi({\"icon-opacity\":new Hi(Ft.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Hi(Ft.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Hi(Ft.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Hi(Ft.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Hi(Ft.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new qi(Ft.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new qi(Ft.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Hi(Ft.paint_symbol[\"text-opacity\"]),\"text-color\":new Hi(Ft.paint_symbol[\"text-color\"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Hi(Ft.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Hi(Ft.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Hi(Ft.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new qi(Ft.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new qi(Ft.paint_symbol[\"text-translate-anchor\"])}),layout:pc},vc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Gt,this.defaultValue=t};vc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},vc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},vc.prototype.outputDefined=function(){return!1},vc.prototype.serialize=function(){return null},oi(\"FormatSectionOverride\",vc,{omit:[\"defaultValue\"]});var gc=function(t){function e(e){t.call(this,e,dc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||cn(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new hc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=dc.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i,a=this.paint.get(n),o=new vc(a),s=new un(o,a.property.specification);i=\"constant\"===a.value.kind||\"source\"===a.value.kind?new hn(\"source\",s):new pn(\"composite\",s,a.value.zoomStops,a.value._interpolationType),this.paint._values[n]=new Ui(a.property,i,a.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=dc.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof he)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof me&&ge(t.value)===Qt){var e=t.value;a(e.sections)}else t instanceof we?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Ki),yc={paint:new Xi({\"background-color\":new qi(Ft.paint_background[\"background-color\"]),\"background-pattern\":new Wi(Ft.paint_background[\"background-pattern\"]),\"background-opacity\":new qi(Ft.paint_background[\"background-opacity\"])})},mc=function(t){function e(e){t.call(this,e,yc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ki),xc={paint:new Xi({\"raster-opacity\":new qi(Ft.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new qi(Ft.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new qi(Ft.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new qi(Ft.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new qi(Ft.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new qi(Ft.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new qi(Ft.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new qi(Ft.paint_raster[\"raster-fade-duration\"])})},bc=function(t){function e(e){t.call(this,e,xc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ki);var _c=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Ki),wc={circle:Go,heatmap:es,hillshade:ns,fill:Hs,\"fill-extrusion\":sl,line:bl,symbol:gc,background:mc,raster:bc};var Tc=s.HTMLImageElement,kc=s.HTMLCanvasElement,Ac=s.HTMLVideoElement,Mc=s.ImageData,Sc=s.ImageBitmap,Ec=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Ec.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof Tc||t instanceof kc||t instanceof Ac||t instanceof Mc||Sc&&t instanceof Sc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},u=l.x,c=l.y;t instanceof Tc||t instanceof kc||t instanceof Ac||t instanceof Mc||Sc&&t instanceof Sc?s.texSubImage2D(s.TEXTURE_2D,0,u,c,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,u,c,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Ec.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Ec.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Ec.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Lc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};Lc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},Lc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Cc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},m([\"receive\",\"process\"],this),this.invoker=new Lc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=S()?t:s};function Pc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Cc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=C(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:ci(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Cc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else S()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Cc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Cc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(fi(e.error)):n(null,fi(e.data)))}else{var i=!1,a=C(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?ci(e):null,data:ci(n,a)},a)}:function(t){i=!0},s=null,l=fi(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var u=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,u[0],l.source)[u[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Cc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Oc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Oc.prototype.setNorthEast=function(t){return this._ne=t instanceof zc?new zc(t.lng,t.lat):zc.convert(t),this},Oc.prototype.setSouthWest=function(t){return this._sw=t instanceof zc?new zc(t.lng,t.lat):zc.convert(t),this},Oc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof zc)e=t,r=t;else{if(!(t instanceof Oc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Oc.convert(a))}var o=t;return this.extend(zc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new zc(e.lng,e.lat),this._ne=new zc(r.lng,r.lat)),this},Oc.prototype.getCenter=function(){return new zc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Oc.prototype.getSouthWest=function(){return this._sw},Oc.prototype.getNorthEast=function(){return this._ne},Oc.prototype.getNorthWest=function(){return new zc(this.getWest(),this.getNorth())},Oc.prototype.getSouthEast=function(){return new zc(this.getEast(),this.getSouth())},Oc.prototype.getWest=function(){return this._sw.lng},Oc.prototype.getSouth=function(){return this._sw.lat},Oc.prototype.getEast=function(){return this._ne.lng},Oc.prototype.getNorth=function(){return this._ne.lat},Oc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Oc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Oc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Oc.prototype.contains=function(t){var e=zc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Oc.convert=function(t){return!t||t instanceof Oc?t:new Oc(t)};var Ic=6371008.8,zc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};zc.prototype.wrap=function(){return new zc(h(this.lng,-180,180),this.lat)},zc.prototype.toArray=function(){return[this.lng,this.lat]},zc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},zc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Ic*Math.acos(Math.min(i,1))},zc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Oc(new zc(this.lng-r,this.lat-e),new zc(this.lng+r,this.lat+e))},zc.convert=function(t){if(t instanceof zc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new zc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new zc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Dc=2*Math.PI*Ic;function Rc(t){return Dc*Math.cos(t*Math.PI/180)}function Fc(t){return(180+t)/360}function Bc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Nc(t,e){return t/Rc(e)}function jc(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Uc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Uc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=zc.convert(t);return new Uc(Fc(r.lng),Bc(r.lat),Nc(e,r.lat))},Uc.prototype.toLngLat=function(){return new zc(360*this.x-180,jc(this.y))},Uc.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Rc(jc(e));var t,e},Uc.prototype.meterInMercatorCoordinateUnits=function(){return 1/Dc*(t=jc(this.y),1/Math.cos(t*Math.PI/180));var t};var Vc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=Gc(0,t,t,e,r)};Vc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Vc.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Pc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Pc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},Vc.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new a((t.x*e-this.x)*po,(t.y*e-this.y)*po)},Vc.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var qc=function(t,e){this.wrap=t,this.canonical=e,this.key=Gc(t,e.z,e.z,e.x,e.y)},Hc=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new Vc(r,+n,+i),this.key=Gc(e,t,r,n,i)};function Gc(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}Hc.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Hc.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Hc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Hc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Hc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?Gc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):Gc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Hc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Hc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Hc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Hc(e,this.wrap,e,r,n),new Hc(e,this.wrap,e,r+1,n),new Hc(e,this.wrap,e,r,n+1),new Hc(e,this.wrap,e,r+1,n+1)]},Hc.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Hc.prototype.wrapped=function(){return new Hc(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Hc.prototype.unwrapTo=function(t){return new Hc(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Hc.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Hc.prototype.toUnwrapped=function(){return new qc(this.wrap,this.canonical)},Hc.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},Hc.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new Uc(t.x-this.wrap,t.y))},oi(\"CanonicalTileID\",Vc),oi(\"OverscaledTileID\",Hc,{omit:[\"posMatrix\"]});var Wc=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return k('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};Wc.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},Wc.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},Wc.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Wc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Wc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Wc.prototype.getPixels=function(){return new $o({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Wc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,u=a;u<o;u++)for(var c=n;c<i;c++)this.data[this._idx(c,u)]=t.data[this._idx(c+s,u+l)]},oi(\"DEMData\",Wc);var Yc=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Yc.prototype.encode=function(t){return this._stringToNumber[t]},Yc.prototype.decode=function(t){return this._numberToString[t]};var Xc=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},Zc={geometry:{configurable:!0}};Zc.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},Zc.geometry.set=function(t){this._geometry=t},Xc.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Xc.prototype,Zc);var Kc=function(){this.state={},this.stateChanges={},this.deletedStates={}};Kc.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},p(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},Kc.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},Kc.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=p({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},Kc.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},Kc.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),p(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var u in this.deletedStates[o]){if(null===this.deletedStates[o][u])this.state[o][u]={};else for(var c=0,f=Object.keys(this.deletedStates[o][u]);c<f.length;c+=1){var h=f[c];delete this.state[o][u][h]}s[u]=this.state[o][u]}r[o]=r[o]||{},p(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t)t[d].setFeatureState(r,e)};var Jc=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new ti(po,16,0),this.grid3D=new ti(po,16,0),this.featureIndexArray=new Ia,this.promoteId=e};function $c(t,e,r,n,i){return b(t,(function(t,a){var o=e instanceof Vi?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function Qc(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function tf(t,e){return e-t}Jc.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var u=e[l],c=[1/0,1/0,-1/0,-1/0],f=0;f<u.length;f++){var h=u[f];c[0]=Math.min(c[0],h.x),c[1]=Math.min(c[1],h.y),c[2]=Math.max(c[2],h.x),c[3]=Math.max(c[3],h.y)}c[0]<po&&c[1]<po&&c[2]>=0&&c[3]>=0&&s.insert(o,c[0],c[1],c[2],c[3])}},Jc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new tl.VectorTile(new Ol(this.rawTileData)).layers,this.sourceLayerCoder=new Yc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Jc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=po/t.tileSize/t.scale,l=An(o.filter),u=t.queryGeometry,c=t.queryPadding*s,f=Qc(u),h=this.grid.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c),p=Qc(t.cameraQueryGeometry),d=0,v=this.grid3D.query(p.minX-c,p.minY-c,p.maxX+c,p.maxY+c,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&i>=l.y)return!0}var u=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var c=0,f=u;c<f.length;c+=1)if(Co(t,f[c]))return!0;for(var h=0;h<t.length-1;h++)if(Po(t[h],t[h+1],u))return!0;return!1}(t.cameraQueryGeometry,e-c,r-c,n+c,i+c)}));d<v.length;d+=1){var g=v[d];h.push(g)}h.sort(tf);for(var y,m={},x=function(a){var c=h[a];if(c!==y){y=c;var f=i.featureIndexArray.get(c),p=null;i.loadMatchingFeature(m,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=yo(e)),r.queryIntersectsFeature(u,e,n,p,i.z,t.transform,s,t.pixelPosMatrix)}))}},b=0;b<h.length;b++)x(b);return m},Jc.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,u,c){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),d=this.vtLayers[h].feature(n);if(i.needGeometry){var v=mo(d,!0);if(!i.filter(new zi(this.tileID.overscaledZ),v,this.tileID.canonical))return}else if(!i.filter(new zi(this.tileID.overscaledZ),d))return;for(var g=this.getId(d,h),y=0;y<f.length;y++){var m=f[y];if(!(a&&a.indexOf(m)<0)){var x=s[m];if(x){var b={};void 0!==g&&u&&(b=u.getState(x.sourceLayer||\"_geojsonTileLayer\",g));var _=p({},l[m]);_.paint=$c(_.paint,x.paint,d,b,o),_.layout=$c(_.layout,x.layout,d,b,o);var w=!c||c(d,x,b);if(w){var T=new Xc(d,this.z,this.x,this.y,g);T.layer=_;var k=t[m];void 0===k&&(k=t[m]=[]),k.push({featureIndex:n,feature:T,intersectionZ:w})}}}}}},Jc.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var u=An(i),c=0,f=t;c<f.length;c+=1){var h=f[c];this.loadMatchingFeature(l,r,n,h,u,a,o,s,e)}return l},Jc.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1)if(t===i[n])return!0;return!1},Jc.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},oi(\"FeatureIndex\",Jc,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var ef=function(t,e){this.tileID=t,this.uid=v(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};ef.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<N.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},ef.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},ef.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof hc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof hc&&o.hasRTLText){this.hasRTLText=!0,Ii.isLoading()||Ii.isLoaded()||\"deferred\"!==Pi()||Oi();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new Aa},ef.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},ef.prototype.getBucket=function(t){return this.buckets[t.id]},ef.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Ec(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Ec(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},ef.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},ef.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,u){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:u,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},ef.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=An(e&&e.filter),s=this.tileID.canonical,l=s.z,u=s.x,c=s.y,f={z:l,x:u,y:c},h=0;h<a.length;h++){var p=a.feature(h);if(o.needGeometry){var d=mo(p,!0);if(!o.filter(new zi(this.tileID.overscaledZ),d,this.tileID.canonical))continue}else if(!o.filter(new zi(this.tileID.overscaledZ),p))continue;var v=r.getId(p,i),g=new Xc(p,l,u,c,v);g.tile=f,t.push(g)}}},ef.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},ef.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},ef.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=E(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},ef.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},ef.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},ef.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},ef.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<N.now()},ef.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},ef.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=N.now()+t},ef.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1)r[i[n]]=!0;this.dependencies[t]=r},ef.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1)if(a[s[o]])return!0}return!1};var rf=s.performance,nf=function(t){this._marks={start:[t.url,\"start\"].join(\"#\"),end:[t.url,\"end\"].join(\"#\"),measure:t.url.toString()},rf.mark(this._marks.start)};nf.prototype.finish=function(){rf.mark(this._marks.end);var t=rf.getEntriesByName(this._marks.measure);return 0===t.length&&(rf.measure(this._marks.measure,this._marks.start,this._marks.end),t=rf.getEntriesByName(this._marks.measure),rf.clearMarks(this._marks.start),rf.clearMarks(this._marks.end),rf.clearMeasures(this._marks.measure)),t},t.Actor=Cc,t.AlphaImage=Jo,t.CanonicalTileID=Vc,t.CollisionBoxArray=Aa,t.Color=ue,t.DEMData=Wc,t.DataConstantProperty=qi,t.DictionaryCoder=Yc,t.EXTENT=po,t.ErrorEvent=Dt,t.EvaluationParameters=zi,t.Event=zt,t.Evented=Rt,t.FeatureIndex=Jc,t.FillBucket=Us,t.FillExtrusionBucket=il,t.ImageAtlas=su,t.ImagePosition=au,t.LineBucket=vl,t.LngLat=zc,t.LngLatBounds=Oc,t.MercatorCoordinate=Uc,t.ONE_EM=Ll,t.OverscaledTileID=Hc,t.Point=a,t.Point$1=a,t.Properties=Xi,t.Protobuf=Ol,t.RGBAImage=$o,t.RequestManager=W,t.RequestPerformance=nf,t.ResourceType=_t,t.SegmentVector=Da,t.SourceFeatureState=Kc,t.StructArrayLayout1ui2=wa,t.StructArrayLayout2f1f2i16=pa,t.StructArrayLayout2i4=ra,t.StructArrayLayout3ui6=va,t.StructArrayLayout4i8=na,t.SymbolBucket=hc,t.Texture=Ec,t.Tile=ef,t.Transitionable=Fi,t.Uniform1f=Ka,t.Uniform1i=Za,t.Uniform2f=Ja,t.Uniform3f=$a,t.Uniform4f=Qa,t.UniformColor=to,t.UniformMatrix4f=ro,t.UnwrappedTileID=qc,t.ValidationError=Bt,t.WritingMode=lu,t.ZoomHistory=hi,t.add=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t},t.addDynamicAttributes=lc,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,i=new Array(t.length),a=null;t.forEach((function(t,o){e(t,(function(t,e){t&&(a=t),i[o]=e,0==--n&&r(a,i)}))}))},t.bezier=u,t.bindAll=m,t.browser=N,t.cacheEntryPossiblyAdded=function(t){++xt>ht&&(t.getActor().send(\"enforceCacheSizeLimit\",ft),xt=0)},t.clamp=f,t.clearTileCache=function(t){var e=s.caches.delete(ct);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Fu,t.clone=function(t){var e=new Fo(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=w,t.clone$2=function(t){var e=new Fo(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=Ml,t.config=j,t.create=function(){var t=new Fo(16);return 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generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)rt(r,t.features[n],e,n);else\"Feature\"===t.type?rt(r,t,e):rt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=lt(t,1,-1-r,r,0,-1,2,e),a=lt(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=lt(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=gt(i,1).concat(n)),a&&(n=n.concat(gt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function kt(t,e,r){return 32*((1<<t)*r+e)+t}function At(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}V.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(H(t[l],l));this.trees[i+1]=new j(s,K,J,a,Float32Array),r&&console.timeEnd(o);for(var u=i;u>=n;u--){var c=+Date.now();s=this._cluster(s,u),this.trees[u]=new j(s,K,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",u,s.length,+Date.now()-c)}return r&&console.timeEnd(\"total time\"),this},V.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],u=[],c=0,f=l.range(Y(r),X(a),Y(i),X(n));c<f.length;c+=1){var h=f[c],p=l.points[h];u.push(p.numPoints?G(p):this.points[p.index])}return u},V.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,u=i.within(a.x,a.y,o);l<u.length;l+=1){var c=u[l],f=i.points[c];f.parentId===t&&s.push(f.numPoints?G(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},V.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},V.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,u=(r+1+s)/i,c={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,u),n.points,e,r,i,c),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,u),n.points,i,r,i,c),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,u),n.points,-1,r,i,c),c.features.length?c:null},V.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},V.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},V.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],u=l.numPoints,c={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:u?W(l):this.points[l.index].properties},f=void 0;u?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(c.id=f),a.features.push(c)}},V.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(+t,this.options.maxZoom+1))},V.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=n.minPoints,l=i/(a*Math.pow(2,e)),u=0;u<t.length;u++){var c=t[u];if(!(c.zoom<=e)){c.zoom=e;for(var f=this.trees[e+1],h=f.within(c.x,c.y,l),p=c.numPoints||1,d=p,v=0,g=h;v<g.length;v+=1){var y=g[v],m=f.points[y];m.zoom>e&&(d+=m.numPoints||1)}if(d>=s){for(var x=c.x*p,b=c.y*p,_=o&&p>1?this._map(c,!0):null,w=(u<<5)+(e+1)+this.points.length,T=0,k=h;T<k.length;T+=1){var A=k[T],M=f.points[A];if(!(M.zoom<=e)){M.zoom=e;var S=M.numPoints||1;x+=M.x*S,b+=M.y*S,M.parentId=w,o&&(_||(_=this._map(c,!0)),o(_,this._map(M)))}}c.parentId=w,r.push(q(x/d,b/d,w,d,_))}else if(r.push(c),d>1)for(var E=0,L=h;E<L.length;E+=1){var C=L[E],P=f.points[C];P.zoom<=e||(P.zoom=e,r.push(P))}}}return r},V.prototype._getOriginId=function(t){return t-this.points.length>>5},V.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},V.prototype._map=function(t,e){if(t.numPoints)return e?Z({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?Z({},n):n},Tt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},Tt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,u=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var c=1<<e,f=kt(e,r,n),h=this.tiles[f];if(!h&&(u>1&&console.time(\"creation\"),h=this.tiles[f]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),u)){u>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){u>1&&console.time(\"clipping\");var v,g,y,m,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;v=g=y=m=null,x=lt(t,c,r-_,r+T,0,h.minX,h.maxX,l),b=lt(t,c,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(v=lt(x,c,n-_,n+T,1,h.minY,h.maxY,l),g=lt(x,c,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(y=lt(b,c,n-_,n+T,1,h.minY,h.maxY,l),m=lt(b,c,n+w,n+k,1,h.minY,h.maxY,l),b=null),u>1&&console.timeEnd(\"clipping\"),s.push(v||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(m||[],e+1,2*r+1,2*n+1)}}},Tt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=kt(t,e=(e%o+o)%o,r);if(this.tiles[s])return mt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,u=t,c=e,f=r;!l&&u>0;)u--,c=Math.floor(c/2),f=Math.floor(f/2),l=this.tiles[kt(u,c,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",u,c,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,u,c,f,t,e,r),a>1&&console.timeEnd(\"drilling 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i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new Tt(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var u={};if(i){var c=i.finish();c&&(u.resourceTiming={},u.resourceTiming[n.source]=JSON.parse(JSON.stringify(c)))}r(null,u)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r.prototype.getClusterExpansionZoom=function(t,e){try{e(null,this._geoJSONIndex.getClusterExpansionZoom(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterChildren=function(t,e){try{e(null,this._geoJSONIndex.getChildren(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterLeaves=function(t,e){try{e(null,this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset))}catch(t){e(t)}},r}(l);var St=function(e){var r=this;this.self=e,this.actor=new t.Actor(e,this),this.layerIndexes={},this.availableImages={},this.workerSourceTypes={vector:l,geojson:Mt},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name \"'+t+'\" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isParsed())throw new Error(\"RTL text plugin already 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s=i([\"transform\",\"WebkitTransform\"]);r.setTransform=function(t,e){t.style[s]=e};var l=!1;try{var u=Object.defineProperty({},\"passive\",{get:function(){l=!0}});t.window.addEventListener(\"test\",u,u),t.window.removeEventListener(\"test\",u,u)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.addEventListener(e,r,n):t.addEventListener(e,r,n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.removeEventListener(e,r,n):t.removeEventListener(e,r,n.capture)};var c=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener(\"click\",c,!0)};function f(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener(\"click\",c,!0),t.window.setTimeout((function(){t.window.removeEventListener(\"click\",c,!0)}),0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect();return new t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!(t&&(4!==t.length||t[0]<0||e.data.width<t[0]||t[1]<0||e.data.height<t[1]||t[2]<0||e.data.width<t[2]||t[3]<0||e.data.height<t[3]||t[2]<t[0]||t[3]<t[1]))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,u=l.x+1,c=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:u,y:c-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:u-1,y:c},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u+h,y:c},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=g,d=g,v=1e20;function g(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(m(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(m(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function m(t,e,r,n,i){r[0]=0,n[0]=-v,n[1]=+v;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+v}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}g.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?v:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?v:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(y(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),y(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1)(0,o[i])(t,e);delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,u=o.glyph;(n[s]||(n[s]={}))[l]=u&&{id:u.id,bitmap:u.bitmap.clone(),metrics:u.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=\"-transition\",T=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,w)?this._transitionable.setTransition(n.slice(0,-11),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),k=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};k.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},k.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var u=t[l];i=s*r,a=(s+=u)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===u})}return n},k.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=void 0,d=i/r*(n+1);if(l.isDash){var v=n-Math.abs(d);p=Math.sqrt(h*h+v*v)}else p=n-Math.sqrt(h*h+d*d);this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=l.isDash?h:-h;this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var u={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,u},k.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var A=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function M(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}A.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},A.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},A.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},A.Actor=t.Actor;var S=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};S.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},S.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var E=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setSourceProperty=function(t){this._tileJSONRequest&&this._tileJSONRequest.cancel(),t(),this.map.style.sourceCaches[this.id].clearTiles(),this.load()},r.prototype.setTiles=function(t){var e=this;return this.setSourceProperty((function(){e._options.tiles=t})),this},r.prototype.setUrl=function(t){var e=this;return this.setSourceProperty((function(){e.url=t,e._options.url=t})),this},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),C=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(L),P=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,minPoints:Math.max(2,n.clusterMinPoints||2),extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties,filter:n.filter},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var u=i-r,c=a-n,f=Math.max(u,c),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var z=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),D=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(I),R={vector:E,raster:L,\"raster-dem\":C,geojson:P,video:z,image:I,canvas:D};function F(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function B(t,e,r,n,i,a){var o=function(t,e,r){if(t)for(var n=0,i=t;n<i.length;n+=1){var a=e[i[n]];if(a&&a.source===r&&\"fill-extrusion\"===a.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&\"fill-extrusion\"===s.type)return!0}return!1}(i&&i.layers,e,t.id),s=a.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(N);for(var u=[],c=0,f=l;c<f.length;c+=1){var h=f[c];u.push({wrappedTileID:h.tileID.wrapped().key,queryResults:h.tile.queryRenderedFeatures(e,r,t._state,h.queryGeometry,h.cameraQueryGeometry,h.scale,i,a,s,F(t.transform,h.tileID))})}var p=function(t){for(var e={},r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.queryResults,s=a.wrappedTileID,l=r[s]=r[s]||{};for(var u in o)for(var 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Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var St=7680,Et=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Et.disabled=new Et({func:519,mask:0},0,0,St,St,St);var Lt=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};Lt.Replace=[1,0],Lt.disabled=new Lt(Lt.Replace,t.Color.transparent,[!1,!1,!1,!1]),Lt.unblended=new Lt(Lt.Replace,t.Color.transparent,[!0,!0,!0,!0]),Lt.alphaBlended=new Lt([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Ct=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Ct.disabled=new Ct(!1,1029,2305),Ct.backCCW=new Ct(!0,1029,2305);var Pt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new G(this),this.clearDepth=new W(this),this.clearStencil=new Y(this),this.colorMask=new X(this),this.depthMask=new Z(this),this.stencilMask=new K(this),this.stencilFunc=new J(this),this.stencilOp=new $(this),this.stencilTest=new Q(this),this.depthRange=new tt(this),this.depthTest=new et(this),this.depthFunc=new rt(this),this.blend=new nt(this),this.blendFunc=new it(this),this.blendColor=new at(this),this.blendEquation=new ot(this),this.cullFace=new st(this),this.cullFaceSide=new lt(this),this.frontFace=new ut(this),this.program=new ct(this),this.activeTexture=new ft(this),this.viewport=new ht(this),this.bindFramebuffer=new pt(this),this.bindRenderbuffer=new dt(this),this.bindTexture=new vt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new yt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new mt(this),this.pixelStoreUnpack=new xt(this),this.pixelStoreUnpackPremultiplyAlpha=new bt(this),this.pixelStoreUnpackFlipY=new _t(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\"),this.maxTextureSize=t.getParameter(t.MAX_TEXTURE_SIZE)};Pt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Pt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Pt.prototype.createIndexBuffer=function(t,e){return new U(this,t,e)},Pt.prototype.createVertexBuffer=function(t,e,r){return new q(this,t,e,r)},Pt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Pt.prototype.createFramebuffer=function(t,e,r){return new At(this,t,e,r)},Pt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Pt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Pt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Pt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Pt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,Lt.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Pt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ot=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new R[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new j(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(zt(this._source.type)){for(var u={},c={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],v=this._tiles[p];if(v&&!(v.fadeEndTime&&v.fadeEndTime<=t.browser.now())){var g=this.findLoadedParent(d,o);g&&(this._addTile(g.tileID),u[g.tileID.key]=g.tileID),c[p]=d}}for(var y in this._retainLoadedChildren(c,a,s,l),u)l[y]||(this._coveredTiles[y]=!0,l[y]=u[y])}for(var m in l)this._tiles[m].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,u=t;l<u.length;l+=1){var c=u[l],f=this._addTile(c);n[c.key]=c,f.hasData()||e<this._source.maxzoom&&(s[c.key]=c)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],v=this._tiles[d.key];if(!v.hasData()){if(e+1>this._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var m=d.children(this._source.maxzoom);if(n[m[0].key]&&n[m[1].key]&&n[m[2].key]&&n[m[3].key])continue}for(var x=v.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(v=this.getTile(_))&&x&&(v=this._addTile(_)),v&&(n[_.key]=_,x=v.wasRequested(),v.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),u=s.map((function(t){return o.pointCoordinate(t)})),c=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,v=0,g=u;v<g.length;v+=1){var y=g[v];f=Math.min(f,y.x),h=Math.min(h,y.y),p=Math.max(p,y.x),d=Math.max(d,y.y)}for(var m=function(e){var n=i._tiles[c[e]];if(!n.holdingForFade()){var s=n.tileID,v=Math.pow(2,o.zoom-n.tileID.overscaledZ),g=r*n.queryPadding*t.EXTENT/n.tileSize/v,y=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(y[0].x-g<t.EXTENT&&y[0].y-g<t.EXTENT&&y[1].x+g>=0&&y[1].y+g>=0){var m=l.map((function(t){return s.getTilePoint(t)})),x=u.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:m,cameraQueryGeometry:x,scale:v})}}},x=0;x<c.length;x++)m(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(zt(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function zt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function Dt(){return new t.window.Worker(oa.workerUrl)}Ot.maxOverzooming=10,Ot.maxUnderzooming=3;var Rt=\"mapboxgl_preloaded_worker_pool\",Ft=function(){this.active={}};Ft.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Ft.workerCount;)this.workers.push(new Dt);return this.active[t]=!0,this.workers.slice()},Ft.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Ft.prototype.isPreloaded=function(){return!!this.active[Rt]},Ft.prototype.numActive=function(){return Object.keys(this.active).length};var Bt,Nt=Math.floor(t.browser.hardwareConcurrency/2);function jt(){return Bt||(Bt=new Ft),Bt}function Ut(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function Vt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Ut(t[n],e[t[n].ref]));return t}Ft.workerCount=Math.max(Math.min(Nt,6),1);var qt={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Ht(t,e,r){r.push({command:qt.addSource,args:[t,e[t]]})}function Gt(t,e,r){e.push({command:qt.removeSource,args:[t]}),r[t]=!0}function Wt(t,e,r,n){Gt(t,r,n),Ht(t,e,r)}function Yt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Xt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Zt(t){return t.id}function Kt(t,e){return t[e.id]=e,t}function Jt(e,r){if(!e)return[{command:qt.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:qt.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:qt.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:qt.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:qt.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:qt.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:qt.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:qt.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:qt.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:qt.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||Gt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Yt(e,r,a)?n.push({command:qt.setGeoJSONSourceData,args:[a,r[a].data]}):Wt(a,r,n,i)):Ht(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:qt.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,u,c,f=(e=e||[]).map(Zt),h=r.map(Zt),p=e.reduce(Kt,{}),d=r.reduce(Kt,{}),v=f.slice(),g=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:qt.removeLayer,args:[o]}),v.splice(v.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],v[v.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:qt.removeLayer,args:[o]}),v.splice(v.lastIndexOf(o,v.length-a),1)):a++,u=v[v.length-i],n.push({command:qt.addLayer,args:[d[o],u]}),v.splice(v.length-i,0,o),g[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!g[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(c in Xt(s.layout,l.layout,n,o,null,qt.setLayoutProperty),Xt(s.paint,l.paint,n,o,null,qt.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:qt.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:qt.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(c)&&\"layout\"!==c&&\"paint\"!==c&&\"filter\"!==c&&\"metadata\"!==c&&\"minzoom\"!==c&&\"maxzoom\"!==c&&(0===c.indexOf(\"paint.\")?Xt(s[c],l[c],n,o,c.slice(6),qt.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:qt.setLayerProperty,args:[o,c,l[c]]}));for(c in l)l.hasOwnProperty(c)&&!s.hasOwnProperty(c)&&\"layout\"!==c&&\"paint\"!==c&&\"filter\"!==c&&\"metadata\"!==c&&\"minzoom\"!==c&&\"maxzoom\"!==c&&(0===c.indexOf(\"paint.\")?Xt(s[c],l[c],n,o,c.slice(6),qt.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:qt.setLayerProperty,args:[o,c,l[c]]}))}else n.push({command:qt.removeLayer,args:[o]}),u=v[v.lastIndexOf(o)+1],n.push({command:qt.addLayer,args:[l,u]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:qt.setStyle,args:[r]}]}return n}var $t=function(t,e){this.reset(t,e)};$t.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},$t.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Qt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function te(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function ee(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function re(e,r){var n=[e.x,e.y,0,1];pe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ne(t,e){return.5+t/e*.5}function ie(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ae(e,r,n,i,a,o,s,l){var u=i?e.textSizeData:e.iconSizeData,c=t.evaluateSizeForZoom(u,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,v=n.transform.width/n.transform.height,g=!1,y=0;y<d.length;y++){var m=d.get(y);if(m.hidden||m.writingMode===t.WritingMode.vertical&&!g)he(m.numGlyphs,h);else{g=!1;var x=[m.anchorX,m.anchorY,0,1];if(t.transformMat4(x,x,r),ie(x,f)){var b=x[3],_=ne(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(u,c,m),T=s?w/_:w*_,k=new t.Point(m.anchorX,m.anchorY),A=re(k,a).point,M={},S=le(m,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v);g=S.useVertical,(S.notEnoughRoom||g||S.needsFlipping&&le(m,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v).notEnoughRoom)&&he(m.numGlyphs,h)}else he(m.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function oe(t,e,r,n,i,a,o,s,l,u,c){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),v=e.getoffsetX(f-1),g=ce(t*d,r,n,i,a,o,s.segment,h,p,l,u,c);if(!g)return null;var y=ce(t*v,r,n,i,a,o,s.segment,h,p,l,u,c);return y?{first:g,last:y}:null}function se(e,r,n,i){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function le(e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=r/24,y=e.lineOffsetX*g,m=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=oe(g,l,y,m,n,f,h,e,u,o,p);if(!w)return{notEnoughRoom:!0};var T=re(w.first.point,s).point,k=re(w.last.point,s).point;if(i&&!n){var A=se(e.writingMode,T,k,d);if(A)return A}v=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)v.push(ce(g*l.getoffsetX(M),y,m,n,f,h,e.segment,b,_,u,o,p));v.push(w.last)}else{if(i&&!n){var S=re(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(u.getx(E),u.gety(E)),C=re(L,a),P=C.signedDistanceFromCamera>0?C.point:ue(h,L,S,1,a),O=se(e.writingMode,S,P,d);if(O)return O}var I=ce(g*l.getoffsetX(e.glyphStartIndex),y,m,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,u,o,p);if(!I)return{notEnoughRoom:!0};v=[I]}for(var z=0,D=v;z<D.length;z+=1){var R=D[z];t.addDynamicAttributes(c,R.point,R.angle)}return{}}function ue(t,e,r,n,i){var a=re(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function ce(e,r,n,i,a,o,s,l,u,c,f,h){var p=i?e-r:e+r,d=p>0?1:-1,v=0;i&&(d*=-1,v=Math.PI),d<0&&(v+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,m=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)<l||g>=u)return null;if(m=y,w.push(y),void 0===(y=h[g])){var T=new t.Point(c.getx(g),c.gety(g)),k=re(T,f);if(k.signedDistanceFromCamera>0)y=h[g]=k.point;else{var A=g-d;y=ue(0===x?o:new t.Point(c.getx(A),c.gety(A)),T,m,_-x+1,f)}}x+=b,b=m.dist(y)}var M=(_-x)/b,S=y.sub(m),E=S.mult(M)._add(m);E._add(S._unit()._perp()._mult(n*d));var L=v+Math.atan2(y.y-m.y,y.x-m.x);return w.push(E),{point:E,angle:L,path:w}}Qt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Qt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Qt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Qt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Qt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var u=this.circles[3*l],c=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:u-f,y1:c-f,x2:u+f,y2:c+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Qt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var u=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,u,c,i),n?u.length>0:u},Qt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Qt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Qt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Qt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,u=this.boxCells[i];if(null!==u)for(var c=this.bboxes,f=0,h=u;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=c[d+2]&&e<=c[d+3]&&r>=c[d+0]&&n>=c[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:c[d],y1:c[d+1],x2:c[d+2],y2:c[d+3]})}}}var v=this.circleCells[i];if(null!==v)for(var g=this.circles,y=0,m=v;y<m.length;y+=1){var x=m[y];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(g[b],g[b+1],g[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=g[b],w=g[b+1],T=g[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Qt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,u=o.seenUids,c=this.boxCells[i];if(null!==c)for(var f=this.bboxes,h=0,p=c;h<p.length;h+=1){var d=p[h];if(!u.box[d]){u.box[d]=!0;var v=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[v+0],f[v+1],f[v+2],f[v+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var y=this.circles,m=0,x=g;m<x.length;m+=1){var b=x[m];if(!u.circle[b]){u.circle[b]=!0;var _=3*b;if(this._circlesCollide(y[_],y[_+1],y[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Qt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),u=this._convertToYCellCoord(e),c=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Qt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Qt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Qt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Qt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var u=(o-i)/2,c=Math.abs(e-(i+u));if(c>u+r)return!1;if(l<=s||c<=u)return!0;var f=l-s,h=c-u;return f*f+h*h<=r*r};var fe=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function he(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(fe,3*n)}}function pe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var de=100,ve=function(t,e,r){void 0===e&&(e=new Qt(t.width+200,t.height+200,25)),void 0===r&&(r=new Qt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+de,this.screenBottomBoundary=t.height+de,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function ge(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}ve.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,u=t.x2*o+a.point.x,c=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,u,c)||!e&&this.grid.hitTest(s,l,u,c,i)?{box:[],offscreen:!1}:{box:[s,l,u,c],offscreen:this.isOffscreen(s,l,u,c)}},ve.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,u,c,f,h,p){var d=[],v=new t.Point(r.anchorX,r.anchorY),g=re(v,o),y=ne(this.transform.cameraToCenterDistance,g.signedDistanceFromCamera),m=(c?a/y:a*y)/t.ONE_EM,x=re(v,s).point,b=oe(m,i,r.lineOffsetX*m,r.lineOffsetY*m,!1,x,v,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*y+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new $t,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var O=1;O<L.path.length;O++)C.push(L.path[O]);var I=2.5*k;if(l){var z=C.map((function(t){return re(t,l)}));C=z.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:z.map((function(t){return t.point}))}var D=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);D=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=D;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/I)+1;for(var q=0;q<V;q++){var H=q/Math.max(V-1,1),G=S.lerp(H),W=G.x+de,Y=G.y+de;d.push(W,Y,k,0);var X=W-k,Z=Y-k,K=W+k,J=Y+k;if(T=T&&this.isOffscreen(X,Z,K,J),w=w||this.isInsideGrid(X,Z,K,J),!e&&this.grid.hitTestCircle(W,Y,k,f)&&(_=!0,!u))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!u&&_||!w?[]:d,offscreen:T,collisionDetected:_}},ve.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var u=l[s],c=new t.Point(u.x+de,u.y+de);n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y),r.push(c)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var v=d[p],g=v.key;if(void 0===f[g.bucketInstanceId]&&(f[g.bucketInstanceId]={}),!f[g.bucketInstanceId][g.featureIndex]){var y=[new t.Point(v.x1,v.y1),new t.Point(v.x2,v.y1),new t.Point(v.x2,v.y2),new t.Point(v.x1,v.y2)];t.polygonIntersectsPolygon(r,y)&&(f[g.bucketInstanceId][g.featureIndex]=!0,void 0===h[g.bucketInstanceId]&&(h[g.bucketInstanceId]=[]),h[g.bucketInstanceId].push(g.featureIndex))}}return h},ve.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},ve.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},ve.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return pe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+de,(-i[1]/i[3]+1)/2*this.transform.height+de),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},ve.prototype.isOffscreen=function(t,e,r,n){return r<de||t>=this.screenRightBoundary||n<de||e>this.screenBottomBoundary},ve.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},ve.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var ye=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};ye.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var me=function(t,e,r,n,i){this.text=new ye(t?t.text:null,e,r,i),this.icon=new ye(t?t.icon:null,e,n,i)};me.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var xe=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},be=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},_e=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},we=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function Te(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point(s+u[0]*a,l+u[1]*a)}function ke(e,r,n,i,a,o){var s=e.x1,l=e.x2,u=e.y1,c=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:u+p.y,x2:l+p.x,y2:c+p.y,anchorPointX:f,anchorPointY:h}}we.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var Ae=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new ve(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new we(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Me(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}Ae.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,u=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),c=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=ge(n,1,this.transform.zoom),v=te(f,h,p,this.transform,d),g=null;if(h){var y=ee(f,h,p,this.transform,d);g=t.multiply([],this.transform.labelPlaneMatrix,y)}this.retainedQueryData[a.bucketInstanceId]=new _e(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var m={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:v,labelToScreenMatrix:g,scale:u,textPixelRatio:c,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:m})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:m})}},Ae.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=[f.textOffset0,f.textOffset1],y=Te(t,r,n,g,i),m=this.collisionIndex.placeCollisionBox(ke(e,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate);if(!d||0!==this.collisionIndex.placeCollisionBox(ke(d,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate).box.length)return m.box.length>0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(v=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:v},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:y,placedGlyphBoxes:m}):void 0},Ae.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,u=a.textLabelPlaneMatrix,c=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,v=a.collisionGroup,g=s.get(\"text-optional\"),y=s.get(\"icon-optional\"),m=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=m&&(x||!o.hasIconData()||y),A=x&&(m||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new xe(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,O=null,I=0,z=0,D=0;a.textFeatureIndex?I=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(I=e.featureIndex),a.verticalTextFeatureIndex&&(z=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length&&(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),!(L&&L.box&&L.box.length));i+=1);else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,u=e.textBoxScale,c=w&&!x?r:null,h={box:[],offscreen:!1},p=m?2*N.length:N.length,d=0;d<p;++d){var g=N[d%N.length],y=d>=N.length,k=i.attemptAnchorPlacement(g,t,a,s,u,b,_,f,l,v,y,e,o,n,c);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,m,f,l,v.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),W=t.evaluateSizeForFeature(o.textSizeData,d,G),Y=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(m,G,o.lineVertexArray,o.glyphOffsetArray,W,l,u,c,n,_,v.predicate,X,Y),T=m||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?ke(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,v.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(O=Z(a.verticalIconBox)).box.length>0:(O=Z(a.iconBox)).box.length>0,S=S&&O.offscreen}var K=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,J=y||0===e.numIconVertices;if(K||J?J?K||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&z?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,v.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID)),M&&O&&i.collisionIndex.insertCollisionBox(O.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,v.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID),n)){var $=o.bucketInstanceId,Q=i.collisionCircleArrays[$];void 0===Q&&(Q=i.collisionCircleArrays[$]=new be);for(var tt=0;tt<P.circles.length;tt+=4)Q.circles.push(P.circles[tt+0]),Q.circles.push(P.circles[tt+1]),Q.circles.push(P.circles[tt+2]),Q.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new xe(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},Ae.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var u=l[s];u>=0&&(e.text.placedSymbolArray.get(u).crossTileID=a>=0&&u!==a?0:n.crossTileID)}},Ae.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},Ae.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],u=i[s];u?(this.opacities[s]=new me(u,n,l.text,l.icon),r=r||l.text!==u.text.placed||l.icon!==u.icon.placed):(this.opacities[s]=new me(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var c in i){var f=i[c];if(!this.opacities[c]){var h=new me(f,n,!1,!1);h.isHidden()||(this.opacities[c]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},Ae.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},Ae.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new me(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),u=a.get(\"text-variable-anchor\"),c=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new me(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},v=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,v=a.crossTileID,g=r[v],y=i.opacities[v];g?y=o:y||(y=p,i.opacities[v]=y),r[v]=!0;var m=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(m){var T=ze(y.text),k=_?De:T;d(e.text,s,k);var A=w?De:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=ze(y.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:De;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var O=C?De:L;d(e.icon,a.numVerticalIconVertices,O),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var I=e.collisionArrays[n];if(I){var z=new t.Point(0,0);if(I.textBox||I.verticalTextBox){var D=!0;if(u){var R=i.variableOffsets[v];R?(z=Te(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),c&&z._rotate(f?i.transform.angle:-i.transform.angle)):D=!1}I.textBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!D||_,z.x,z.y),I.verticalTextBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!D||w,z.x,z.y)}var F=Boolean(!w&&I.verticalIconBox);I.iconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,h?z.x:0,h?z.y:0),I.verticalIconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,h?z.x:0,h?z.y:0)}}},g=0;g<e.symbolInstances.length;g++)v(g);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var y=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=y.invProjMatrix,e.placementViewportMatrix=y.viewportMatrix,e.collisionCircleArray=y.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},Ae.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},Ae.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},Ae.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},Ae.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},Ae.prototype.setStale=function(){this.stale=!0};var Se=Math.pow(2,25),Ee=Math.pow(2,24),Le=Math.pow(2,17),Ce=Math.pow(2,16),Pe=Math.pow(2,9),Oe=Math.pow(2,8),Ie=Math.pow(2,1);function ze(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Se+e*Ee+r*Le+e*Ce+r*Pe+e*Oe+r*Ie+e}var De=0,Re=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Re.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var Fe=function(t,e,r,n,i,a,o){this.placement=new Ae(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};Fe.prototype.isDone=function(){return this._done},Fe.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Re(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Fe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Be=512/t.EXTENT/2,Ne=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Ne.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=Be/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Ne.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,u=o;l<u.length;l+=1){var c=u[l];if(Math.abs(c.coord.x-s.x)<=n&&Math.abs(c.coord.y-s.y)<=n&&!r[c.crossTileID]){r[c.crossTileID]=!0,a.crossTileID=c.crossTileID;break}}}}};var je=function(){this.maxCrossTileID=0};je.prototype.generate=function(){return++this.maxCrossTileID};var Ue=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Ue.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Ue.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var u=o[t.scaledTo(Number(a)).key];u&&u.findMatches(e.symbolInstances,t,i)}}for(var c=0;c<e.symbolInstances.length;c++){var f=e.symbolInstances.get(c);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Ne(t,e.symbolInstances,e.bucketInstanceId),!0},Ue.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Ue.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ve=function(){this.layerIndexes={},this.crossTileIDs=new je,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ve.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Ue);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],u=l.getBucket(t);u&&t.id===u.layerIds[0]&&(u.bucketInstanceId||(u.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,u,this.crossTileIDs)&&(i=!0),a[u.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ve.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var qe=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},He=t.pick(qt,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ge=t.pick(qt,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),We=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),Ye=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new A(jt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new k(256,512),this.crossTileSymbolIndex=new Ve,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if(t.triggerPluginCompletionEvent(e),r&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(We,!1)},r.prototype._load=function(e,r){if(!r||!qe(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=Vt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new T(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,c())})),u=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){u=null,o||(o=t,a=e,c())}));function c(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],u=l.width,c=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,v=l.stretchX,g=l.stretchY,y=l.content,m=new t.RGBAImage({width:u,height:c});t.RGBAImage.copy(e,m,{x:f,y:h},{x:0,y:0},{width:u,height:c}),r[s]={data:m,pixelRatio:d,sdf:p,stretchX:v,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),u&&(u.cancel(),u=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}var l={};for(var u in this.sourceCaches){var c=this.sourceCaches[u];l[u]=c.used,c.used=!1}for(var f=0,h=this._order;f<h.length;f+=1){var p=h[f],d=this._layers[p];d.recalculate(e,this._availableImages),!d.isHidden(e.zoom)&&d.source&&(this.sourceCaches[d.source].used=!0)}for(var v in l){var g=this.sourceCaches[v];l[v]!==g.used&&g.fire(new t.Event(\"data\",{sourceDataType:\"visibility\",dataType:\"source\",sourceId:v}))}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),qe(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=Vt(e.layers);var n=Jt(this.serialize(),e).filter((function(t){return!(t.command in Ge)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in He)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._afterImageUpdated(e)},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._afterImageUpdated(e)},r.prototype._afterImageUpdated=function(e){this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.dispatcher.broadcast(\"setImages\",this._availableImages),this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ot(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(qe(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is required to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var u=l[s][o];if(u)for(var c=0,f=u;c<f.length;c+=1){var h=f[c];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var v=this._order[d];if(r(v))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id]<d)break;p.push(y),i.pop()}else for(var m=0,x=t;m<x.length;m+=1){var b=x[m][v];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var u=[];for(var c in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[c]||u.push(B(this.sourceCaches[c],this._layers,this._serializedLayers,e,r,n));return this.placement&&u.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),u=[],c=0,f=Object.keys(l).map(Number);c<f.length;c+=1){var h=f[c];u.push(o[h])}u.sort(N);for(var p=function(){var r=v[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],u=n[a];u.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var c=0,f=u;c<f.length;c+=1){var h=f[c];o.push(h)}}},d=0,v=u;d<v.length;d+=1)p();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var y in s)g(y);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(u)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&qe(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers)this._layers[e].setEventedParent(null);for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},u=0,c=this._order;u<c.length;u+=1){var f=c[u],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new Fe(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var v=0,g=this._order;v<g.length;v+=1){var y=g[v],m=this._layers[y];\"symbol\"===m.type&&this.placement.updateLayerOpacities(m,l[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);Ye.getSourceType=function(t){return R[t]},Ye.setSourceType=function(t,e){R[t]=e},Ye.registerForPluginStateChange=t.registerForPluginStateChange;var Xe=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ze=_r(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),Ke=_r(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Je=_r(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),$e=_r(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Qe=_r(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),tr=_r(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),er=_r(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),rr=_r(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),nr=_r(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),ir=_r(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),ar=_r(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),or=_r(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),sr=_r(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),lr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ur=_r(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),cr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),fr=_r(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),hr=_r(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),pr=_r(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),dr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),vr=_r(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),gr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),yr=_r(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=_r(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),xr=_r(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),br=_r(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function _r(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n=e.match(/attribute ([\\w]+) ([\\w]+)/g),i=t.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),a=e.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),o=a?a.concat(i):i,s={};return{fragmentSource:t=t.replace(r,(function(t,e,r,n,i){return s[i]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nvarying \"+r+\" \"+n+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,n,i){var a=\"float\"===n?\"vec2\":\"vec4\",o=i.match(/color/)?\"color\":a;return s[i]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+a+\" a_\"+i+\";\\nvarying \"+r+\" \"+n+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===o?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+i+\" = a_\"+i+\";\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+i+\" = unpack_mix_\"+o+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+a+\" a_\"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===o?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+n+\" \"+i+\" = a_\"+i+\";\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+n+\" \"+i+\" = unpack_mix_\"+o+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n    \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"})),staticAttributes:n,staticUniforms:o}}var wr=Object.freeze({__proto__:null,prelude:Ze,background:Ke,backgroundPattern:Je,circle:$e,clippingMask:Qe,heatmap:tr,heatmapTexture:er,collisionBox:rr,collisionCircle:nr,debug:ir,fill:ar,fillOutline:or,fillOutlinePattern:sr,fillPattern:lr,fillExtrusion:ur,fillExtrusionPattern:cr,hillshadePrepare:fr,hillshade:hr,line:pr,lineGradient:dr,linePattern:vr,lineSDF:gr,raster:yr,symbolIcon:mr,symbolSDF:xr,symbolTextAndIcon:br}),Tr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};function kr(t){for(var e=[],r=0;r<t.length;r++)if(null!==t[r]){var n=t[r].split(\" \");e.push(n.pop())}return e}Tr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,u=0;!l&&u<n.length;u++)this.boundPaintVertexBuffers[u]!==n[u]&&(l=!0);var c=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||c?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},Tr.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,u=this.context,c=u.gl;if(u.extVertexArrayObject)this.vao&&this.destroy(),this.vao=u.extVertexArrayObject.createVertexArrayOES(),u.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=u.currentNumAttributes||0;for(var f=l;f<s;f++)c.disableVertexAttribArray(f)}e.enableAttributes(c,t);for(var h=0,p=r;h<p.length;h+=1)p[h].enableAttributes(c,t);a&&a.enableAttributes(c,t),o&&o.enableAttributes(c,t),e.bind(),e.setVertexAttribPointers(c,t,i);for(var d=0,v=r;d<v.length;d+=1){var g=v[d];g.bind(),g.setVertexAttribPointers(c,t,i)}a&&(a.bind(),a.setVertexAttribPointers(c,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(c,t,i)),u.currentNumAttributes=l},Tr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var Ar=function(t,e,r,n,i,a){var o=t.gl;this.program=o.createProgram();for(var s=kr(r.staticAttributes),l=n?n.getBinderAttributes():[],u=s.concat(l),c=r.staticUniforms?kr(r.staticUniforms):[],f=n?n.getBinderUniforms():[],h=[],p=0,d=c.concat(f);p<d.length;p+=1){var v=d[p];h.indexOf(v)<0&&h.push(v)}var g=n?n.defines():[];a&&g.push(\"#define OVERDRAW_INSPECTOR;\");var y=g.concat(Ze.fragmentSource,r.fragmentSource).join(\"\\n\"),m=g.concat(Ze.vertexSource,r.vertexSource).join(\"\\n\"),x=o.createShader(o.FRAGMENT_SHADER);if(o.isContextLost())this.failedToCreate=!0;else{o.shaderSource(x,y),o.compileShader(x),o.attachShader(this.program,x);var b=o.createShader(o.VERTEX_SHADER);if(o.isContextLost())this.failedToCreate=!0;else{o.shaderSource(b,m),o.compileShader(b),o.attachShader(this.program,b),this.attributes={};var _={};this.numAttributes=u.length;for(var w=0;w<this.numAttributes;w++)u[w]&&(o.bindAttribLocation(this.program,w,u[w]),this.attributes[u[w]]=w);o.linkProgram(this.program),o.deleteShader(b),o.deleteShader(x);for(var T=0;T<h.length;T++){var k=h[T];if(k&&!_[k]){var A=o.getUniformLocation(this.program,k);A&&(_[k]=A)}}this.fixedUniforms=i(t,_),this.binderUniforms=n?n.getUniforms(t,_):[]}}};function Mr(t,e,r){var n=1/ge(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}Ar.prototype.draw=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=t.gl;if(!this.failedToCreate){for(var m in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[m].set(o[m]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],b=0,_=c.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new Tr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],u,w.vertexOffset,d,v),y.drawElements(e,w.primitiveLength*x,y.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Sr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var u=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Er=function(e,r,n,i,a,o,s){return t.extend(Sr(e,r,n,i),Mr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Lr=function(t){return{u_matrix:t}},Cr=function(e,r,n,i){return t.extend(Lr(e),Mr(n,r,i))},Pr=function(t,e){return{u_matrix:t,u_world:e}},Or=function(e,r,n,i,a){return t.extend(Cr(e,r,n,i),{u_world:a})},Ir=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=ge(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},zr=function(t,e,r){var n=ge(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Dr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Rr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Fr=function(t){return{u_matrix:t}},Br=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ge(e,1,r),u_intensity:n}},Nr=function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}},jr=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,u,c,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,u=Math.pow(2,l.canonical.z),c=l.canonical.y,[new t.MercatorCoordinate(0,c/u).toLngLat().lat,new t.MercatorCoordinate(0,(c+1)/u).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}},Ur=function(e,r){var n=r.stride,i=t.create();return t.ortho(i,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(i,i,[0,-t.EXTENT,0]),{u_matrix:i,u_image:1,u_dimension:[n,n],u_zoom:e.overscaledZ,u_unpack:r.getUnpackVector()}};var Vr=function(e,r,n){var i=e.transform;return{u_matrix:Yr(e,r,n),u_ratio:1/ge(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},qr=function(e,r,n,i){return t.extend(Vr(e,r,n),{u_image:0,u_image_height:i})},Hr=function(e,r,n,i){var a=e.transform,o=Wr(r,a);return{u_matrix:Yr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ge(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Gr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=Wr(r,o),u=\"round\"===n.layout.get(\"line-cap\"),c=s.getDash(i.from,u),f=s.getDash(i.to,u),h=c.width*a.fromScale,p=f.width*a.toScale;return t.extend(Vr(e,r,n),{u_patternscale_a:[l/h,-c.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:f.y,u_mix:a.t})};function Wr(t,e){return 1/ge(t,1,e.tileZoom)}function Yr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Xr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Zr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Zr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Kr,Jr=function(t,e,r,n,i,a,o,s,l,u){var c=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:c.cameraToCenterDistance,u_pitch:c.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:c.width/c.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:u,u_texture:0}},$r=function(e,r,n,i,a,o,s,l,u,c,f){var h=a.transform;return t.extend(Jr(e,r,n,i,a,o,s,l,u,c),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Qr=function(e,r,n,i,a,o,s,l,u,c){return t.extend($r(e,r,n,i,a,o,s,l,!0,u,!0),{u_texsize_icon:c,u_texture_icon:1})},tn=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},en=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,u=Math.pow(2,n.tileID.overscaledZ),c=n.tileSize*Math.pow(2,r.transform.tileZoom)/u,f=c*(n.tileID.canonical.x+n.tileID.wrap*u),h=c*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ge(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},rn={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image),u_image_height:new t.Uniform1f(e,r.u_image_height)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function nn(e,r,n,i,a,o,s){for(var l=e.context,u=l.gl,c=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var v=i[d],g=r.getTile(v),y=g.getBucket(n);if(y){var m=v.posMatrix;0===a[0]&&0===a[1]||(m=e.translatePosMatrix(v.posMatrix,g,a,o));var x=s?y.textCollisionBox:y.iconCollisionBox,b=y.collisionCircleArray;if(b.length>0){var _=t.create(),w=m;t.mul(_,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,y.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&c.draw(l,u.LINES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,zr(m,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],O=E.circleArray[C+1],I=E.circleArray[C+2],z=E.circleArray[C+3];k.emplace(A++,P,O,I,z,0),k.emplace(A++,P,O,I,z,1),k.emplace(A++,P,O,I,z,2),k.emplace(A++,P,O,I,z,3)}(!Kr||Kr.length<2*h)&&(Kr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(Kr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Dr(N.transform,N.invTransform,e.transform);T.draw(l,u.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var an=t.identity(new Float32Array(16));function on(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,u=-(s.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point((l/a+c[0])*o,(u/a+c[1])*o)}function sn(e,r,n,i,a,o,s,l,u,c,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,v={};p.clear();for(var g=0;g<h.length;g++){var y=h.get(g),m=e.allowVerticalPlacement&&!y.placedOrientation,x=y.hidden||!y.crossTileID||m?null:i[y.crossTileID];if(x){var b=new t.Point(y.anchorX,y.anchorY),_=re(b,n?l:s),w=ne(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,c,y)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/u);for(var k=x.width,A=x.height,M=on(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?re(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&y.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<y.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&y.associatedIconIndex>=0&&(v[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else he(y.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var O=C.get(P);if(O.hidden)he(O.numGlyphs,d);else{var I=v[P];if(I)for(var z=0;z<O.numGlyphs;z++)t.addDynamicAttributes(d,I.shiftedAnchor,I.angle);else he(O.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function ln(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function un(e,r,n,i,a,o,s,l,u,c,f,h){for(var p=e.context,d=p.gl,v=e.transform,g=\"map\"===l,y=\"map\"===u,m=g&&\"point\"!==n.layout.get(\"symbol-placement\"),x=g&&!y&&!m,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=!1,w=e.depthModeForSublayer(0,Mt.ReadOnly),T=n.layout.get(\"text-variable-anchor\"),k=[],A=0,M=i;A<M.length;A+=1){var S=M[A],E=r.getTile(S),L=E.getBucket(n);if(L){var C=a?L.text:L.icon;if(C&&C.segments.get().length){var P=C.programConfigurations.get(n.id),O=a||L.sdfIcons,I=a?L.textSizeData:L.iconSizeData,z=y||0!==v.pitch,D=e.useProgram(ln(O,a,L),P),R=t.evaluateSizeForZoom(I,v.zoom),F=void 0,B=[0,0],N=void 0,j=void 0,U=null,V=void 0;if(a){if(N=E.glyphAtlasTexture,j=d.LINEAR,F=E.glyphAtlasTexture.size,L.iconsInText){B=E.imageAtlasTexture.size,U=E.imageAtlasTexture;var q=\"composite\"===I.kind||\"camera\"===I.kind;V=z||e.options.rotating||e.options.zooming||q?d.LINEAR:d.NEAREST}}else{var H=1!==n.layout.get(\"icon-size\").constantOr(0)||L.iconsNeedLinear;N=E.imageAtlasTexture,j=O||e.options.rotating||e.options.zooming||H||z?d.LINEAR:d.NEAREST,F=E.imageAtlasTexture.size}var G=ge(E,1,e.transform.zoom),W=te(S.posMatrix,y,g,e.transform,G),Y=ee(S.posMatrix,y,g,e.transform,G),X=T&&L.hasTextData(),Z=\"none\"!==n.layout.get(\"icon-text-fit\")&&X&&L.hasIconData();m&&ae(L,S.posMatrix,e,a,W,Y,y,c);var K=e.translatePosMatrix(S.posMatrix,E,o,s),J=m||a&&T||Z?an:W,$=e.translatePosMatrix(Y,E,o,s,!0),Q=O&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),tt={program:D,buffers:C,uniformValues:O?L.iconsInText?Qr(I.kind,R,x,y,e,K,J,$,F,B):$r(I.kind,R,x,y,e,K,J,$,a,F,!0):Jr(I.kind,R,x,y,e,K,J,$,a,F),atlasTexture:N,atlasTextureIcon:U,atlasInterpolation:j,atlasInterpolationIcon:V,isSDF:O,hasHalo:Q};if(b&&L.canOverlap){_=!0;for(var et=0,rt=C.segments.get();et<rt.length;et+=1){var nt=rt[et];k.push({segments:new t.SegmentVector([nt]),sortKey:nt.sortKey,state:tt})}}else k.push({segments:C.segments,sortKey:0,state:tt})}}}_&&k.sort((function(t,e){return t.sortKey-e.sortKey}));for(var it=0,at=k;it<at.length;it+=1){var ot=at[it],st=ot.state;if(p.activeTexture.set(d.TEXTURE0),st.atlasTexture.bind(st.atlasInterpolation,d.CLAMP_TO_EDGE),st.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),st.atlasTextureIcon&&st.atlasTextureIcon.bind(st.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),st.isSDF){var lt=st.uniformValues;st.hasHalo&&(lt.u_is_halo=1,cn(st.buffers,ot.segments,n,e,st.program,w,f,h,lt)),lt.u_is_halo=0}cn(st.buffers,ot.segments,n,e,st.program,w,f,h,st.uniformValues)}}function cn(t,e,r,n,i,a,o,s,l){var u=n.context,c=u.gl;i.draw(u,c.TRIANGLES,a,o,s,Ct.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function fn(t,e,r,n,i,a,o){var s,l,u,c,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),v=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var g=0,y=n;g<y.length;g+=1){var m=y[g],x=e.getTile(m);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(v));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(m.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){c=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];u=\"fillOutlinePattern\"===l&&d?Or(S,t,v,x,E):Pr(S,E)}else c=b.indexBuffer,f=b.segments,u=d?Cr(S,t,v,x):Lr(S);w.draw(t.context,s,i,t.stencilModeForClipping(m),a,Ct.disabled,u,r.id,b.layoutVertexBuffer,c,f,r.paint,t.transform.zoom,_)}}}}function hn(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,u=r.paint.get(\"fill-extrusion-pattern\"),c=u.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var v=d[p],g=e.getTile(v),y=g.getBucket(r);if(y){var m=y.programConfigurations.get(r.id),x=t.useProgram(c?\"fillExtrusionPattern\":\"fillExtrusion\",m);c&&(t.context.activeTexture.set(l.TEXTURE0),g.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),m.updatePaintBuffers(f));var b=u.constantOr(null);if(b&&g.imageAtlas){var _=g.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&m.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(v.posMatrix,g,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),A=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=c?Er(k,t,A,h,v,f,g):Sr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Ct.backCCW,M,r.id,y.layoutVertexBuffer,y.indexBuffer,y.segments,r.paint,t.transform.zoom,m)}}}function pn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var u=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var c=jr(t,e,r);u.draw(o,s.TRIANGLES,n,i,a,Ct.disabled,c,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function dn(e,r,n,i,a,o){var s=e.context,l=s.gl,u=r.dem;if(u&&u.data){var c=u.dim,f=u.stride,h=u.getPixels();if(s.activeTexture.set(l.TEXTURE1),s.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(f),r.demTexture){var p=r.demTexture;p.update(h,{premultiply:!1}),p.bind(l.NEAREST,l.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(s,h,l.RGBA,{premultiply:!1}),r.demTexture.bind(l.NEAREST,l.CLAMP_TO_EDGE);s.activeTexture.set(l.TEXTURE0);var d=r.fbo;if(!d){var v=new t.Texture(s,{width:c,height:c,data:null},l.RGBA);v.bind(l.LINEAR,l.CLAMP_TO_EDGE),(d=r.fbo=s.createFramebuffer(c,c,!0)).colorAttachment.set(v.texture)}s.bindFramebuffer.set(d.framebuffer),s.viewport.set([0,0,c,c]),e.useProgram(\"hillshadePrepare\").draw(s,l.TRIANGLES,i,a,o,Ct.disabled,Ur(r.tileID,u),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function vn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,u=r?(s-r.timeAdded)/o:-1,c=n.getSource(),f=a.coveringZoomLevel({tileSize:c.tileSize,roundZoom:c.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-u,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var gn=new t.Color(1,0,0,1),yn=new t.Color(0,1,0,1),mn=new t.Color(0,0,1,1),xn=new t.Color(1,0,1,1),bn=new t.Color(0,1,1,1);function _n(t){var e=t.transform.padding;wn(t,t.transform.height-(e.top||0),3,gn),wn(t,e.bottom||0,3,yn),Tn(t,e.left||0,3,mn),Tn(t,t.transform.width-(e.right||0),3,xn);var r=t.transform.centerPoint;!function(t,e,r,n){var i=20,a=2;kn(t,e-a/2,r-i/2,a,i,n),kn(t,e-i/2,r-a/2,i,a,n)}(t,r.x,t.transform.height-r.y,bn)}function wn(t,e,r,n){kn(t,0,e+r/2,t.transform.width,r,n)}function Tn(t,e,r,n){kn(t,e-r/2,0,r,t.transform.height,n)}function kn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function An(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,u=Et.disabled,c=e.colorModeForRenderPass(),f=\"$debug\";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,u,c,Ct.disabled,Rr(o,t.Color.red),f,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,p=h&&h.byteLength||0,d=Math.floor(p/1024),v=r.getTile(n).tileSize,g=512/Math.min(v,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+\" \"+d+\"kb\"),s.draw(i,a.TRIANGLES,l,u,Lt.alphaBlended,Ct.disabled,Rr(o,t.Color.transparent,g),f,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var Mn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Et.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,u=\"map\"===a,c=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),v=d.getBucket(n);if(v&&v.text&&v.text.segments.get().length){var g=v.textSizeData,y=t.evaluateSizeForZoom(g,l.zoom),m=ge(d,1,r.transform.zoom),x=te(p.posMatrix,c,u,r.transform,m),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&v.hasIconData();if(y){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);sn(v,u,c,s,t.symbolSize,l,x,p.posMatrix,_,y,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&un(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&un(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(nn(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),nn(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var u=e.context,c=u.gl,f=e.depthModeForSublayer(0,Mt.ReadOnly),h=Et.disabled,p=e.colorModeForRenderPass(),d=[],v=0;v<i.length;v++){var g=i[v],y=r.getTile(g),m=y.getBucket(n);if(m){var x=m.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:m.layoutVertexBuffer,indexBuffer:m.indexBuffer,uniformValues:Ir(e,g,y,n)};if(l)for(var _=0,w=m.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:m.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,O=S.uniformValues,I=M.segments;L.draw(u,c.TRIANGLES,f,h,p,Ct.disabled,O,n.id,C,P,I,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=Et.disabled,l=new Lt([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);(function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}})(a,e,n),a.clear({color:t.Color.transparent});for(var u=0;u<i.length;u++){var c=i[u];if(!r.hasRenderableParent(c)){var f=r.getTile(c),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),v=e.transform.zoom;d.draw(a,o.TRIANGLES,Mt.disabled,s,l,Ct.disabled,Br(c.posMatrix,f,v,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(a){n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA)),o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Nr(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1))for(var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),u=n.paint.get(\"line-dasharray\"),c=n.paint.get(\"line-pattern\"),f=c.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":u?\"lineSDF\":h?\"lineGradient\":\"line\",v=e.context,g=v.gl,y=!0,m=0,x=i;m<x.length;m+=1){var b=x[m],_=r.getTile(b);if(!f||_.patternsLoaded()){var w=_.getBucket(n);if(w){var T=w.programConfigurations.get(n.id),k=e.context.program.get(),A=e.useProgram(d,T),M=y||A.program!==k,S=c.constantOr(null);if(S&&_.imageAtlas){var E=_.imageAtlas,L=E.patternPositions[S.to.toString()],C=E.patternPositions[S.from.toString()];L&&C&&T.setConstantPatternPositions(L,C)}var P=f?Hr(e,_,n,p):u?Gr(e,_,n,u,p):h?qr(e,_,n,w.lineClipsArray.length):Vr(e,_,n);if(f)v.activeTexture.set(g.TEXTURE0),_.imageAtlasTexture.bind(g.LINEAR,g.CLAMP_TO_EDGE),T.updatePaintBuffers(p);else if(u&&(M||e.lineAtlas.dirty))v.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(v);else if(h){var O=w.gradients[n.id],I=O.texture;if(n.gradientVersion!==O.version){var z=256;if(n.stepInterpolant){var D=r.getSource().maxzoom,R=b.canonical.z===D?Math.ceil(1<<e.transform.maxZoom-b.canonical.z):1,F=w.maxLineLength/t.EXTENT*1024*R;z=t.clamp(t.nextPowerOfTwo(F),256,v.maxTextureSize)}O.gradient=t.renderColorRamp({expression:n.gradientExpression(),evaluationKey:\"lineProgress\",resolution:z,image:O.gradient||void 0,clips:w.lineClipsArray}),O.texture?O.texture.update(O.gradient):O.texture=new t.Texture(v,O.gradient,g.RGBA),O.version=n.gradientVersion,I=O.texture}v.activeTexture.set(g.TEXTURE0),I.bind(n.stepInterpolant?g.NEAREST:g.LINEAR,g.CLAMP_TO_EDGE)}A.draw(v,g.TRIANGLES,s,e.stencilModeForClipping(b),l,Ct.disabled,P,n.id,w.layoutVertexBuffer,w.indexBuffer,w.segments,n.paint,e.transform.zoom,T,w.layoutVertexBuffer2),y=!1}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),u=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===u){var c=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);fn(e,r,n,i,c,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Mt.ReadOnly);fn(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))hn(t,e,r,n,a,Et.disabled,Lt.disabled),hn(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();hn(t,e,r,n,a,Et.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=t.depthModeForSublayer(0,Mt.ReadOnly),o=t.colorModeForRenderPass(),s=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],l=s[0],u=0,c=s[1];u<c.length;u+=1){var f=c[u],h=e.getTile(f);h.needsHillshadePrepare&&\"offscreen\"===t.renderPass?dn(t,h,r,a,Et.disabled,o):\"translucent\"===t.renderPass&&pn(t,h,r,a,l[f.overscaledZ],o)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),u=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),c=u[0],f=u[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,v=f;d<v.length;d+=1){var g=v[d],y=t.depthModeForSublayer(g.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?Mt.ReadWrite:Mt.ReadOnly,a.LESS),m=e.getTile(g),x=t.transform.calculatePosMatrix(g.toUnwrapped(),p);m.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(g,0),_=vn(m,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-m.tileID.overscaledZ),T=[m.tileID.canonical.x*w%1,m.tileID.canonical.y*w%1]):m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Xr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,y,Et.disabled,l,Ct.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,y,c[g.overscaledZ],l,Ct.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,u=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(u)){var c=!u&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===c){var f=Et.disabled,h=t.depthModeForSublayer(0,\"opaque\"===c?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(u?\"backgroundPattern\":\"background\"),v=s.coveringTiles({tileSize:l});u&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var g=r.getCrossfadeParameters(),y=0,m=v;y<m.length;y+=1){var x=m[y],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=u?en(b,i,t,u,{tileID:x,tileSize:l},g):tn(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Ct.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)An(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Et.disabled);var o=\"3d\"===i.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},Sn=function(t,e){this.context=new Pt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ot.maxUnderzooming+Ot.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ve,this.gpuTimers={}};Sn.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},Sn.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Xe.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Xe.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,O.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Xe.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Et({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},Sn.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,Lt.disabled,Ct.disabled,Fr(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},Sn.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(Lt.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,Mt.disabled,new Et({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),Lt.disabled,Ct.disabled,Fr(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},Sn.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Et({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},Sn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Et({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},Sn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Et({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Et.disabled,e),n]},Sn.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){var r=1/8;return new Lt([e.CONSTANT_COLOR,e.ONE],new t.Color(r,r,r,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?Lt.unblended:Lt.alphaBlended},Sn.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},Sn.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},Sn.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,u,c={},f={},h={};for(var p in a){var d=a[p];c[p]=d.getVisibleCoordinates(),f[p]=c[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var v=0;v<i.length;v++){var g=i[v];if(this.style._layers[g].is3D()){this.opaquePassCutoff=v;break}}this.renderPass=\"offscreen\";for(var y=0,m=i;y<m.length;y+=1){var x=m[y],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=c[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=(\"symbol\"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,c[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(u&&u.id)&&(u=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<u.getSource().maxzoom)&&(l=u))})),l&&Mn.debug(this,l,l.getVisibleCoordinates())),this.options.showPadding&&_n(this),this.context.setDefault()},Sn.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),Mn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},Sn.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},Sn.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},Sn.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},Sn.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},Sn.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var u=[a?n[0]:ge(r,n[0],this.transform.zoom),a?n[1]:ge(r,n[1],this.transform.zoom),0],c=new Float32Array(16);return t.translate(c,e,u),c},Sn.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},Sn.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},Sn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},Sn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new Ar(this.context,t,wr[t],e,rn[t],this._showOverdrawInspector)),this.cache[r]},Sn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Sn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},Sn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},Sn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var En=function(t,e){this.points=t,this.planes=e};En.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new En(a,o)};var Ln=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Ln.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new Ln(n,i)},Ln.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},Ln.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},Ln.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var u=Number.MAX_VALUE,c=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];u=Math.min(u,h),c=Math.max(c,h)}if(c<0||u>this.max[l]-this.min[l])return 0}return 1};var Cn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};Cn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Cn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Cn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Cn.prototype.clone=function(){return new Cn(this.top,this.bottom,this.left,this.right)},Cn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Pn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Cn,this._posMatrixCache={},this._alignedPosMatrixCache={}},On={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Pn.prototype.clone=function(){var t=new Pn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},On.minZoom.get=function(){return this._minZoom},On.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},On.maxZoom.get=function(){return this._maxZoom},On.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},On.minPitch.get=function(){return this._minPitch},On.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},On.maxPitch.get=function(){return this._maxPitch},On.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},On.renderWorldCopies.get=function(){return this._renderWorldCopies},On.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},On.worldSize.get=function(){return this.tileSize*this.scale},On.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},On.size.get=function(){return new t.Point(this.width,this.height)},On.bearing.get=function(){return-this.angle/Math.PI*180},On.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},On.pitch.get=function(){return this._pitch/Math.PI*180},On.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},On.fov.get=function(){return this._fov/Math.PI*180},On.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},On.zoom.get=function(){return this._zoom},On.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},On.center.get=function(){return this._center},On.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},On.padding.get=function(){return this._edgeInsets.toJSON()},On.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},On.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Pn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Pn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Pn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Pn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),u=s-1;u<=l+1;u++)0!==u&&r.push(new t.UnwrappedTileID(u,e));return r},Pn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=En.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var u=function(t){return{aabb:new Ln([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},c=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)c.push(u(-d)),c.push(u(d));for(c.push(u(0));c.length>0;){var v=c.pop(),g=v.x,y=v.y,m=v.fullyVisible;if(!m){var x=v.aabb.intersects(s);if(0===x)continue;m=2===x}var b=v.aabb.distanceX(o),_=v.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-v.zoom)-2;if(v.zoom===h||w>T&&v.zoom>=l)f.push({tileID:new t.OverscaledTileID(v.zoom===h?p:v.zoom,v.wrap,v.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);c.push({aabb:v.aabb.quadrant(k),zoom:v.zoom+1,x:A,y:M,wrap:v.wrap,fullyVisible:m})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Pn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},On.unmodified.get=function(){return this._unmodified},Pn.prototype.zoomScale=function(t){return Math.pow(2,t)},Pn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Pn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Pn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},On.point.get=function(){return this.project(this.center)},Pn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Pn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Pn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Pn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Pn.prototype.coordinateLocation=function(t){return t.toLngLat()},Pn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,u=n[1]/a,c=r[2]/i,f=n[2]/a,h=c===f?0:(0-c)/(f-c);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,u,h)/this.worldSize)},Pn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Pn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Pn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Pn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Pn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Pn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Pn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,u=this.size,c=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<u.y?u.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<u.x?u.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=c,void(this._constraining=!1);if(this.latRange){var v=p.y,g=u.y/2;v-g<a&&(i=a+g),v+g>o&&(i=o-g)}if(this.lngRange){var y=p.x,m=u.x/2;y-m<s&&(n=s+m),y+m>l&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=c,this._constraining=!1}},Pn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,u=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,c,u),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),v=Math.sin(this.angle),g=s-Math.round(s)+d*h+v*p,y=l-Math.round(l)+d*p+v*h,m=new Float64Array(f);if(t.translate(m,m,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=m,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Pn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Pn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Pn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var u=l[s];n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(Pn.prototype,On);var In=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};In.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},In.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},In.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),u=this._map.getPitch(),c=\"\";if(c+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||u)&&(c+=\"/\"+Math.round(10*l)/10),u&&(c+=\"/\"+Math.round(u)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+c):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+c),\"#\"+p.join(\"&\")}return\"#\"+c},In.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},In.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},In.prototype._updateHashUnthrottled=function(){var e=t.window.location.href.replace(/(#.+)?$/,this.getHashString());try{t.window.history.replaceState(t.window.history.state,null,e)}catch(t){}};var zn={linearity:.3,easing:t.bezier(0,0,.3,1)},Dn=t.extend({deceleration:2500,maxSpeed:1400},zn),Rn=t.extend({deceleration:20,maxSpeed:1400},zn),Fn=t.extend({deceleration:1e3,maxSpeed:360},zn),Bn=t.extend({deceleration:1e3,maxSpeed:90},zn),Nn=function(t){this._map=t,this.clear()};function jn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Un(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}Nn.prototype.clear=function(){this._inertiaBuffer=[]},Nn.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},Nn.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},Nn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Un(r.pan.mag(),o,t.extend({},Dn,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,jn(s,l)}if(r.zoom){var u=Un(r.zoom,o,Rn);s.zoom=this._map.transform.zoom+u.amount,jn(s,u)}if(r.bearing){var c=Un(r.bearing,o,Fn);s.bearing=this._map.transform.bearing+t.clamp(c.amount,-179,179),jn(s,c)}if(r.pitch){var f=Un(r.pitch,o,Bn);s.pitch=this._map.transform.pitch+f.amount,jn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Vn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),qn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),u=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),c=i.unproject(u);e.call(this,n,{points:s,point:u,lngLats:l,lngLat:c,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Hn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Gn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Gn.prototype.reset=function(){delete this._mousedownPos},Gn.prototype.wheel=function(t){return this._firePreventable(new Hn(t.type,this._map,t))},Gn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Vn(t.type,this._map,t))},Gn.prototype.mouseup=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.dblclick=function(t){return this._firePreventable(new Vn(t.type,this._map,t))},Gn.prototype.mouseover=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.mouseout=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.touchstart=function(t){return this._firePreventable(new qn(t.type,this._map,t))},Gn.prototype.touchmove=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype.touchend=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype.touchcancel=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Gn.prototype.isEnabled=function(){return!0},Gn.prototype.isActive=function(){return!1},Gn.prototype.enable=function(){},Gn.prototype.disable=function(){};var Wn=function(t){this._map=t};Wn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Wn.prototype.mousemove=function(t){this._map.fire(new Vn(t.type,this._map,t))},Wn.prototype.mousedown=function(){this._delayContextMenu=!0},Wn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Vn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Wn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Vn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Wn.prototype.isEnabled=function(){return!0},Wn.prototype.isActive=function(){return!1},Wn.prototype.enable=function(){},Wn.prototype.disable=function(){};var Yn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Xn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Yn.prototype.isEnabled=function(){return!!this._enabled},Yn.prototype.isActive=function(){return!!this._active},Yn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Yn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Yn.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Yn.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Yn.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Yn.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Yn.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Yn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var Zn=function(t){this.reset(),this.numTouches=t.numTouches};Zn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},Zn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Xn(n,r)))},Zn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Xn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},Zn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Kn=function(t){this.singleTap=new Zn(t),this.numTaps=t.numTaps,this.reset()};Kn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Kn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Kn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Kn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Jn=function(){this._zoomIn=new Kn({numTouches:1,numTaps:2}),this._zoomOut=new Kn({numTouches:2,numTaps:1}),this.reset()};Jn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Jn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Jn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Jn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var $n={};$n[0]=1,$n[2]=2;var Qn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Qn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Qn.prototype._correctButton=function(t,e){return!1},Qn.prototype._move=function(t,e){return{}},Qn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Qn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r)if(t.preventDefault(),function(t,e){var r=$n[e];return void 0===t.buttons||(t.buttons&r)!==r}(t,this._eventButton))this.reset();else if(this._moved||!(e.dist(r)<this._clickTolerance))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Qn.prototype.mouseupWindow=function(t){this._lastPoint&&r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Qn.prototype.enable=function(){this._enabled=!0},Qn.prototype.disable=function(){this._enabled=!1,this.reset()},Qn.prototype.isEnabled=function(){return this._enabled},Qn.prototype.isActive=function(){return this._active};var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Qn),ei=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Qn),ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Qn),ni=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};ni.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},ni.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},ni.prototype.touchmove=function(t,e,r){if(this._active&&!(r.length<this._minTouches))return t.preventDefault(),this._calculateTransform(t,e,r)},ni.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},ni.prototype.touchcancel=function(){this.reset()},ni.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Xn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var u=i[l],c=this._touches[l];c&&(a._add(u),o._add(u.sub(c)),s++,i[l]=u)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},ni.prototype.enable=function(){this._enabled=!0},ni.prototype.disable=function(){this._enabled=!1,this.reset()},ni.prototype.isEnabled=function(){return this._enabled},ni.prototype.isActive=function(){return this._active};var ii=function(){this.reset()};function ai(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}ii.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},ii.prototype._start=function(t){},ii.prototype._move=function(t,e,r){return{}},ii.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},ii.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=ai(r,e,i),s=ai(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},ii.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=ai(n,e,a),l=ai(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},ii.prototype.touchcancel=function(){this.reset()},ii.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},ii.prototype.disable=function(){this._enabled=!1,this.reset()},ii.prototype.isEnabled=function(){return this._enabled},ii.prototype.isActive=function(){return this._active};function oi(t,e){return Math.log(t/e)/Math.LN2}var si=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs(oi(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:oi(this._distance,r),pinchAround:e}},e}(ii);function li(t,e){return 180*t.angleWith(e)/Math.PI}var ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:li(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=li(t,this._startVector);return Math.abs(r)<e},e}(ii);function ci(t){return Math.abs(t.y)>Math.abs(t.x)}var fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ci(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ci(t)&&ci(e)&&a}},e}(ii),hi={panStep:100,bearingStep:15,pitchStep:10},pi=function(){var t=hi;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep,this._rotationDisabled=!1};function di(t){return t*(2-t)}pi.prototype.reset=function(){this._active=!1},pi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return this._rotationDisabled&&(n=0,i=0),{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:di,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},pi.prototype.enable=function(){this._enabled=!0},pi.prototype.disable=function(){this._enabled=!1,this.reset()},pi.prototype.isEnabled=function(){return this._enabled},pi.prototype.isActive=function(){return this._active},pi.prototype.disableRotation=function(){this._rotationDisabled=!0},pi.prototype.enableRotation=function(){this._rotationDisabled=!1};var vi=4.000244140625,gi=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222,t.bindAll([\"_onTimeout\"],this)};gi.prototype.setZoomRate=function(t){this._defaultZoomRate=t},gi.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},gi.prototype.isEnabled=function(){return!!this._enabled},gi.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},gi.prototype.isZooming=function(){return!!this._zooming},gi.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},gi.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},gi.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%vi==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},gi.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},gi.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},gi.prototype.renderFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>vi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,u=this._easing,c=!1;if(\"wheel\"===this._type&&l&&u){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=u(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):c=!0}else o=s,c=!0;return this._active=!0,c&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!c,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},gi.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},gi.prototype.reset=function(){this._active=!1};var yi=function(t,e){this._clickZoom=t,this._tapZoom=e};yi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},yi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},yi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},yi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var mi=function(){this.reset()};mi.prototype.reset=function(){this._active=!1},mi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},mi.prototype.enable=function(){this._enabled=!0},mi.prototype.disable=function(){this._enabled=!1,this.reset()},mi.prototype.isEnabled=function(){return this._enabled},mi.prototype.isActive=function(){return this._active};var xi=function(){this._tap=new Kn({numTouches:1,numTaps:1}),this.reset()};xi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},xi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},xi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},xi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},xi.prototype.touchcancel=function(){this.reset()},xi.prototype.enable=function(){this._enabled=!0},xi.prototype.disable=function(){this._enabled=!1,this.reset()},xi.prototype.isEnabled=function(){return this._enabled},xi.prototype.isActive=function(){return this._active};var bi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};bi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},bi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},bi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},bi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var _i=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};_i.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},_i.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},_i.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},_i.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var wi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};wi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},wi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},wi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},wi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},wi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},wi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var Ti=function(t){return t.zoom||t.drag||t.pitch||t.rotate},ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ai(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var Mi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Nn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!0}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],u=s[1],c=s[2];r.addEventListener(l,u,l===t.window.document?this.handleWindowEvent:this.handleEvent,c)}};Mi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},Mi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Gn(e,t));var n=e.boxZoom=new Yn(e,t);this._add(\"boxZoom\",n);var i=new Jn,a=new mi;e.doubleClickZoom=new yi(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new xi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new fi;this._add(\"touchPitch\",s);var l=new ei(t),u=new ri(t);e.dragRotate=new _i(t,l,u),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",u,[\"mouseRotate\"]);var c=new ti(t),f=new ni(t);e.dragPan=new bi(r,c,f),this._add(\"mousePan\",c),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new ui,p=new si;e.touchZoomRotate=new wi(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new gi(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var v=e.keyboard=new pi;this._add(\"keyboard\",v),this._add(\"blockableMapEvent\",new Wn(e));for(var g=0,y=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];g<y.length;g+=1){var m=y[g];t.interactive&&t[m]&&e[m].enable(t[m])}},Mi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},Mi.prototype.stop=function(t){if(!this._updatingCamera){for(var e=0,r=this._handlers;e<r.length;e+=1)r[e].handler.reset();this._inertia.clear(),this._fireEvents({},{},t),this._changes=[]}},Mi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1)if(e[t].handler.isActive())return!0;return!1},Mi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},Mi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},Mi.prototype.isMoving=function(){return Boolean(Ti(this._eventsInProgress))||this.isZooming()},Mi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},Mi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},Mi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},Mi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),u=0,c=this._handlers;u<c.length;u+=1){var f=c[u],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var v=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(v=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,v,h,n),v&&v.needsRenderFrame&&this._triggerRenderFrame()),(v||p.isActive())&&(o[h]=p)}}var g={};for(var y in this._previousActiveHandlers)o[y]||(g[y]=n);this._previousActiveHandlers=o,(Object.keys(g).length||Ai(i))&&(this._changes.push([i,a,g]),this._triggerRenderFrame()),(Object.keys(o).length||Ai(i))&&this._map._stop(!0),this._updatingCamera=!1;var m=i.cameraAnimation;m&&(this._inertia.clear(),this._fireEvents({},{},!0),this._changes=[],m(this._map))}else this.stop(!0)},Mi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},Mi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],u=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,u)}this._updateMapTransform(e,r,n),this._changes=[]},Mi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!Ai(t))return this._fireEvents(e,r,!0);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,u=t.around,c=t.pinchAround;void 0!==c&&(u=c),n._stop(!0),u=u||n.transform.centerPoint;var f=i.pointLocation(a?u.sub(a):u);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,u),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r,!0)},Mi.prototype._fireEvents=function(e,r,n){var i=this,a=Ti(this._eventsInProgress),o=Ti(e),s={};for(var l in e){var u=e[l].originalEvent;this._eventsInProgress[l]||(s[l+\"start\"]=u),this._eventsInProgress[l]=e[l]}for(var c in!a&&o&&this._fireEvent(\"movestart\",o.originalEvent),s)this._fireEvent(c,s[c]);for(var f in o&&this._fireEvent(\"move\",o.originalEvent),e){var h=e[f].originalEvent;this._fireEvent(f,h)}var p,d={};for(var v in this._eventsInProgress){var g=this._eventsInProgress[v],y=g.handlerName,m=g.originalEvent;this._handlersById[y].isActive()||(delete this._eventsInProgress[v],p=r[y]||m,d[v+\"end\"]=p)}for(var x in d)this._fireEvent(x,d[x]);var b=Ti(this._eventsInProgress);if(n&&(a||o)&&!b){this._updatingCamera=!0;var _=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),w=function(t){return 0!==t&&-i._bearingSnap<t&&t<i._bearingSnap};_?(w(_.bearing||this._map.getBearing())&&(_.bearing=0),this._map.easeTo(_,{originalEvent:p})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:p})),w(this._map.getBearing())&&this._map.resetNorth()),this._updatingCamera=!1}},Mi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},Mi.prototype._requestFrame=function(){var t=this;return this._map.triggerRepaint(),this._map._renderTaskQueue.add((function(e){delete t._frameId,t.handleEvent(new ki(\"renderFrame\",{timeStamp:e})),t._applyChanges()}))},Mi.prototype._triggerRenderFrame=function(){void 0===this._frameId&&(this._frameId=this._requestFrame())};var Si=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){e=t.LngLatBounds.convert(e);var n=r&&r.bearing||0;return this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),n,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,u=s.project(t.LngLat.convert(e)),c=s.project(t.LngLat.convert(r)),f=u.rotate(-n*Math.PI/180),h=c.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),v=p.sub(d),g=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/v.x,y=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/v.y;if(!(y<0||g<0)){var m=Math.min(s.scaleZoom(s.scale*Math.min(g,y)),i.maxZoom),x=\"number\"==typeof i.offset.x?new t.Point(i.offset.x,i.offset.y):t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(b,_).rotate(n*Math.PI/180),T=x.add(w).mult(s.scale/s.zoomScale(m));return{center:s.unproject(u.add(c).div(2).sub(T)),zoom:m,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),u=\"zoom\"in e?+e.zoom:a,c=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),v=i.pointLocation(d),g=t.LngLat.convert(e.center||v);this._normalizeCenter(g);var y,m,x=i.project(v),b=i.project(g).sub(x),_=i.zoomScale(u-a);e.around&&(y=t.LngLat.convert(e.around),m=i.locationPoint(y));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||u!==a,this._rotating=this._rotating||o!==c,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,u,e)),n._rotating&&(i.bearing=t.number(o,c,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),y)i.setLocationAtPoint(y,m);else{var v=i.zoomScale(i.zoom-a),g=u>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(v));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),u=this.getPadding(),c=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(c-o),v=t.Point.convert(e.offset),g=a.centerPoint.add(v),y=a.pointLocation(g),m=t.LngLat.convert(e.center||y);this._normalizeCenter(m);var x=a.project(y),b=a.project(m).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,c),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),O=function(t){return C(P)/C(P+_*t)},I=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},z=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(z)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;z=Math.abs(Math.log(T/w))/_,I=function(){return 0},O=function(t){return Math.exp(D*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*z/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*z,d=1/O(i);a.zoom=1===e?c:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(u,p,e),g=a.centerPoint.add(v));var y=1===e?m:a.unproject(x.add(b.mult(I(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop(!1)}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),Ei=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_toggleAttribution\",\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};Ei.prototype.getDefaultPosition=function(){return\"bottom-right\"},Ei.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._compactButton=r.create(\"button\",\"mapboxgl-ctrl-attrib-button\",this._container),this._compactButton.addEventListener(\"click\",this._toggleAttribution),this._setElementTitle(this._compactButton,\"ToggleAttribution\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),this._innerContainer.setAttribute(\"role\",\"list\"),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},Ei.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Ei.prototype._setElementTitle=function(t,e){var r=this._map._getUIString(\"AttributionControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)},Ei.prototype._toggleAttribution=function(){this._container.classList.contains(\"mapboxgl-compact-show\")?(this._container.classList.remove(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"false\")):(this._container.classList.add(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"true\"))},Ei.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\",this._setElementTitle(e,\"MapFeedback\")}},Ei.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"visibility\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},Ei.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},Ei.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\",\"mapboxgl-compact-show\")};var Li=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};Li.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Li.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Li.prototype.getDefaultPosition=function(){return\"bottom-left\"},Li.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Li.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Li.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var Ci=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ci.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ci.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},Ci.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},Ci.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Pi={\"AttributionControl.ToggleAttribution\":\"Toggle attribution\",\"AttributionControl.MapFeedback\":\"Map feedback\",\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},Oi=t.window.HTMLImageElement,Ii=t.window.HTMLElement,zi=t.window.ImageBitmap,Di=60,Ri={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:Di,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Fi=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Ri,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>Di)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new Pn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ci,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Pi,e.locale),this._clickTolerance=e.clickTolerance,this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Ii))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_onMapScroll\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1),t.window.addEventListener(\"orientationchange\",this._onWindowResize,!1)),this.handlers=new Mi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new In(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Ei({customAttribution:e.customAttribution})),this.addControl(new Li,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&(r=e.getDefaultPosition?e.getDefaultPosition():\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.hasControl=function(t){return this._controls.indexOf(t)>-1},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?Di:t)>Di)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Vn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Vn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Vn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new Ye(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new Ye(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof Oi||zi&&r instanceof zi){var u=t.browser.getImageData(r),c=u.width,f=u.height,h=u.data;this.style.addImage(e,{data:new t.RGBAImage({width:c,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,v=r.data,g=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(v)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:g}),g.onAdd&&g.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof Oi||zi&&r instanceof zi?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof Oi||zi&&r instanceof zi);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\"),this._canvas.setAttribute(\"role\",\"region\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)})),this._container.addEventListener(\"scroll\",this._onMapScroll,!1)},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new Sn(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype._onMapScroll=function(t){if(t.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var u=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),c=u.crossFadingFactor();1===c&&c===this._crossFadingFactor||(o=!0,this._crossFadingFactor=c),this.style.update(u)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}var p=this._sourcesDirty||this._styleDirty||this._placementDirty;return p||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new t.Event(\"idle\")),!this._loaded||this._fullyLoaded||p||(this._fullyLoaded=!0),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"orientationchange\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext&&n.loseContext(),Bi(this._canvasContainer),Bi(this._controlContainer),Bi(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(Si);function Bi(t){t.parentNode&&t.parentNode.removeChild(t)}var Ni={showCompass:!0,showZoom:!0,visualizePitch:!1},ji=function(e){var n=this;this.options=t.extend({},Ni,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};ji.prototype._updateZoomButtons=function(){var t=this._map.getZoom(),e=t===this._map.getMaxZoom(),r=t===this._map.getMinZoom();this._zoomInButton.disabled=e,this._zoomOutButton.disabled=r,this._zoomInButton.setAttribute(\"aria-disabled\",e.toString()),this._zoomOutButton.setAttribute(\"aria-disabled\",r.toString())},ji.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},ji.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ui(this._map,this._compass,this.options.visualizePitch)),this._container},ji.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},ji.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},ji.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ui=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new ei({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new ri({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Vi(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ui.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ui.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ui.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ui.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ui.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ui.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ui.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ui.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ui.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ui.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ui.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var qi={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Hi(t,e,r){var n=t.classList;for(var i in qi)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Gi,Wi=function(e){function n(n,i){if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._scale=n&&n.scale||1,this._draggable=n&&n.draggable||!1,this._clickTolerance=n&&n.clickTolerance||0,this._isDragging=!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var a=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");a.setAttributeNS(null,\"display\",\"block\"),a.setAttributeNS(null,\"height\",\"41px\"),a.setAttributeNS(null,\"width\",\"27px\"),a.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");o.setAttributeNS(null,\"stroke\",\"none\"),o.setAttributeNS(null,\"stroke-width\",\"1\"),o.setAttributeNS(null,\"fill\",\"none\"),o.setAttributeNS(null,\"fill-rule\",\"evenodd\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"fill-rule\",\"nonzero\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),l.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,c=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<c.length;u+=1){var f=c[u],h=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");h.setAttributeNS(null,\"opacity\",\"0.04\"),h.setAttributeNS(null,\"cx\",\"10.5\"),h.setAttributeNS(null,\"cy\",\"5.80029008\"),h.setAttributeNS(null,\"rx\",f.rx),h.setAttributeNS(null,\"ry\",f.ry),l.appendChild(h)}var p=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");p.setAttributeNS(null,\"fill\",this._color);var d=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");d.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),p.appendChild(d);var v=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");v.setAttributeNS(null,\"opacity\",\"0.25\"),v.setAttributeNS(null,\"fill\",\"#000000\");var g=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");g.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),v.appendChild(g);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");x.setAttributeNS(null,\"fill\",\"#000000\"),x.setAttributeNS(null,\"opacity\",\"0.25\"),x.setAttributeNS(null,\"cx\",\"5.5\"),x.setAttributeNS(null,\"cy\",\"5.5\"),x.setAttributeNS(null,\"r\",\"5.4999962\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#FFFFFF\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\"),m.appendChild(x),m.appendChild(b),s.appendChild(l),s.appendChild(p),s.appendChild(v),s.appendChild(y),s.appendChild(m),a.appendChild(s),a.setAttributeNS(null,\"height\",41*this._scale+\"px\"),a.setAttributeNS(null,\"width\",27*this._scale+\"px\"),this._element.appendChild(a),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),Hi(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=13.5,r=Math.sqrt(Math.pow(e,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[r,-1*(24.6+r)],\"bottom-right\":[-r,-1*(24.6+r)],left:[e,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Vi(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,qi[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){if(!this._isDragging){var r=this._clickTolerance||this._map._clickTolerance;this._isDragging=e.point.dist(this._pointerdownPos)>=r}this._isDragging&&(this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\")))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._pointerdownPos=t.point,this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Yi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Xi=0,Zi=!1,Ki=function(e){function n(r){e.call(this),this.options=t.extend({},Yi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Gi?n(Gi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Gi=\"denied\"!==t.state,n(Gi)})):(Gi=!!t.window.navigator.geolocation,n(Gi)),this._container;var n},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Xi=0,Zi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Zi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Wi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Wi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Xi--,Zi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Xi>1?(e={maximumAge:6e5,timeout:0},Zi=!0):(e=this.options.positionOptions,Zi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Ji={maxWidth:100,unit:\"metric\"},$i=function(e){this.options=t.extend({},Ji,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Qi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?ta(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):ta(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?ta(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?ta(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):ta(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function ta(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*((o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\"&nbsp;\"+n}$i.prototype.getDefaultPosition=function(){return\"bottom-left\"},$i.prototype._onMove=function(){Qi(this._map,this._container,this.options)},$i.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},$i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},$i.prototype.setUnit=function(t){this.options.unit=t,Qi(this._map,this._container,this.options)};var ea=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};ea.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},ea.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},ea.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},ea.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},ea.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},ea.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},ea.prototype._isFullscreen=function(){return this._fullscreen},ea.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},ea.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var ra={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:\"\",maxWidth:\"240px\"},na=[\"a[href]\",\"[tabindex]:not([tabindex='-1'])\",\"[contenteditable]:not([contenteditable='false'])\",\"button:not([disabled])\",\"input:not([disabled])\",\"select:not([disabled])\",\"textarea:not([disabled])\"].join(\", \"),ia=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(ra),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container);return this._content.appendChild(t),this._createCloseButton(),this._update(),this._focusFirstElement(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.setOffset=function(t){return this.options.offset=t,this._update(),this},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createCloseButton=function(){this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(t){var e=this,n=this._lngLat||this._trackPointer;if(this._map&&n&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return e._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Vi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||t)){var i=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat),a=this.options.anchor,o=aa(this.options.offset);if(!a){var s,l=this._container.offsetWidth,u=this._container.offsetHeight;s=i.y+o.bottom.y<u?[\"top\"]:i.y>this._map.transform.height-u?[\"bottom\"]:[],i.x<l/2?s.push(\"left\"):i.x>this._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var c=i.add(o[a]).round();r.setTransform(this._container,qi[a]+\" translate(\"+c.x+\"px,\"+c.y+\"px)\"),Hi(this._container,a,\"popup\")}},n.prototype._focusFirstElement=function(){if(this.options.focusAfterOpen&&this._container){var t=this._container.querySelector(na);t&&t.focus()}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);function aa(e){if(e){if(\"number\"==typeof e){var r=Math.round(Math.sqrt(.5*Math.pow(e,2)));return{center:new t.Point(0,0),top:new t.Point(0,e),\"top-left\":new t.Point(r,r),\"top-right\":new t.Point(-r,r),bottom:new t.Point(0,-e),\"bottom-left\":new t.Point(r,-r),\"bottom-right\":new t.Point(-r,-r),left:new t.Point(e,0),right:new t.Point(-e,0)}}if(e instanceof t.Point||Array.isArray(e)){var n=t.Point.convert(e);return{center:n,top:n,\"top-left\":n,\"top-right\":n,bottom:n,\"bottom-left\":n,\"bottom-right\":n,left:n,right:n}}return{center:t.Point.convert(e.center||[0,0]),top:t.Point.convert(e.top||[0,0]),\"top-left\":t.Point.convert(e[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(e[\"top-right\"]||[0,0]),bottom:t.Point.convert(e.bottom||[0,0]),\"bottom-left\":t.Point.convert(e[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(e[\"bottom-right\"]||[0,0]),left:t.Point.convert(e.left||[0,0]),right:t.Point.convert(e.right||[0,0])}}return aa(new t.Point(0,0))}var oa={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Fi,NavigationControl:ji,GeolocateControl:Ki,AttributionControl:Ei,ScaleControl:$i,FullscreenControl:ea,Popup:ia,Marker:Wi,Style:Ye,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){jt().acquire(Rt)},clearPrewarmedResources:function(){var t=Bt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Rt),Bt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Ft.workerCount},set workerCount(t){Ft.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return oa})),r}()},3108:function(t,e,r){\"use strict\";t.exports=r(26099)},26099:function(t,e,r){\"use strict\";var n=r(64928),i=r(32420),a=r(51160),o=r(76752),s=r(55616),l=r(31264),u=r(47520),c=r(18400),f=r(72512),h=r(76244);function p(t,e){for(var r=e[0],n=e[1],a=1/(e[2]-r),o=1/(e[3]-n),s=new Array(t.length),l=0,u=t.length/2;l<u;l++)s[2*l]=i((t[2*l]-r)*a,0,1),s[2*l+1]=i((t[2*l+1]-n)*o,0,1);return 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t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst 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float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ vec2(positionOffset.x, -positionOffset.y)))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 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return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign 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t.offset&&(t.offset=[t.offset,0]),this.positionOffset=m(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else{var i=t.style,s=t.weight,l=t.stretch,u=t.variant;t=n.parse(n.stringify(t)),i&&(t.style=i),s&&(t.weight=s),l&&(t.stretch=l),u&&(t.variant=u)}var c=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),f=p(t.size),h=Math.round(f[0]*d(f[1]));if(h!==e.fontSize[r]&&(o=!0,e.fontSize[r]=h),!(e.font[r]&&c==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[c],e.font[r]))){var v=t.family.join(\", \"),g=[t.style];t.style!=t.variant&&g.push(t.variant),t.variant!=t.weight&&g.push(t.weight),_&&t.weight!=t.stretch&&g.push(t.stretch),e.font[r]={baseString:c,family:v,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:y(v,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:g.join(\" \")})},T.fonts[c]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);g(t.kerning,v(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=c.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=this.counts[A];if(w)for(var E=0;E<S;E++)k[M++]=t.position[2*A],k[M++]=t.position[2*A+1];else for(var L=0;L<S;L++)k[M++]=t.position[A][0],k[M++]=t.position[A][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),c.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var C=c.mallocUint8(this.count),P=c.mallocFloat(2*this.count);this.textWidth=[];for(var O=0,I=0;O<this.counts.length;O++){for(var z=this.counts[O],D=this.font[O]||this.font[0],R=this.fontAtlas[O]||this.fontAtlas[0],F=0;F<z;F++){var B=this.text.charAt(I),N=this.text.charAt(I-1);if(C[I]=R.ids[B],P[2*I]=D.width[B],F){var j=P[2*I-2],U=P[2*I],V=P[2*I-1]+.5*j+.5*U;if(this.kerning){var q=D.kerning[N+B];q&&(V+=.001*q)}P[2*I+1]=V}else P[2*I+1]=.5*P[2*I];I++}this.textWidth.push(P.length?.5*P[2*I-2]+P[2*I-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),c.freeUint8(C),c.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),c=x(s*i);n.width=l,n.height=c,n.rows=s,n.cols=o,n.em&&n.texture({data:u({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,c],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,-1*(i+=\"number\"==typeof t?t-n.baseline:-n[t])}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=c.mallocUint8(G);for(var W=(t.color.subarray||t.color.slice).bind(t.color),Y=0;Y<G;Y+=4)H.set(l(W(Y,Y+4),\"uint8\"),Y)}else{var X=t.color.length;H=c.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var K=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(K);for(var J=0;J<this.batch.length;J++)this.batch[J]={count:this.counts.length>1?this.counts[J]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[J]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*J,4*J+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[J]:this.opacity,baseline:null!=this.baselineOffset[J]?this.baselineOffset[J]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[J]?this.alignOffset[J]:this.alignOffset[0]:0,atlas:this.fontAtlas[J]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*J,2*J+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},t.exports=T},55212:function(t,e,r){\"use strict\";var n=r(55616);function 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n=t.segments({inverted:!1,regions:[]}),i=0;i<e.coordinates.length;i++)n=t.selectUnion(t.combine(n,r(e.coordinates[i])));return t.polygon(n)}throw new Error(\"PolyBool: Cannot convert GeoJSON object to PolyBool polygon\")},fromPolygon:function(t,e,r){function n(t,r){return e.pointInsideRegion([.5*(t[0][0]+t[1][0]),.5*(t[0][1]+t[1][1])],r)}function i(t){return{region:t,children:[]}}r=t.polygon(t.segments(r));var a=i(null);function o(t,e){for(var r=0;r<t.children.length;r++)if(n(e,(s=t.children[r]).region))return void o(s,e);var a=i(e);for(r=0;r<t.children.length;r++){var s;n((s=t.children[r]).region,e)&&(a.children.push(s),t.children.splice(r,1),r--)}t.children.push(a)}for(var s=0;s<r.regions.length;s++){var l=r.regions[s];l.length<3||o(a,l)}function u(t,e){for(var r=0,n=t[t.length-1][0],i=t[t.length-1][1],a=[],o=0;o<t.length;o++){var s=t[o][0],l=t[o][1];a.push([s,l]),r+=l*n-s*i,n=s,i=l}return r<0!==e&&a.reverse(),a.push([a[0][0],a[0][1]]),a}var c=[];function f(t){var e=[u(t.region,!1)];c.push(e);for(var r=0;r<t.children.length;r++)e.push(h(t.children[r]))}function h(t){for(var e=0;e<t.children.length;e++)f(t.children[e]);return u(t.region,!0)}for(s=0;s<a.children.length;s++)f(a.children[s]);return c.length<=0?{type:\"Polygon\",coordinates:[]}:1==c.length?{type:\"Polygon\",coordinates:c[0]}:{type:\"MultiPolygon\",coordinates:c}}};t.exports=e},72200:function(t,e,r){var n=r(48088);t.exports=function(t,e,r){function i(t,e,n){return{id:r?r.segmentId():-1,start:t,end:e,myFill:{above:n.myFill.above,below:n.myFill.below},otherFill:null}}var a=n.create();function o(t,r){a.insertBefore(t,(function(n){return i=t.isStart,a=t.pt,o=r,s=n.isStart,l=n.pt,u=n.other.pt,(0!==(c=e.pointsCompare(a,l))?c:e.pointsSame(o,u)?0:i!==s?i?1:-1:e.pointAboveOrOnLine(o,s?l:u,s?u:l)?1:-1)<0;var i,a,o,s,l,u,c}))}function s(t,e){var r=function(t,e){var r=n.node({isStart:!0,pt:t.start,seg:t,primary:e,other:null,status:null});return o(r,t.end),r}(t,e);return function(t,e,r){var 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y,m,x=g();if(x)t?(m=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below)&&(x.seg.myFill.above=!x.seg.myFill.above):x.seg.otherFill=h.seg.myFill,r&&r.segmentUpdate(x.seg),h.other.remove(),h.remove();if(a.getHead()!==h){r&&r.rewind(h.seg);continue}t?(m=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below,h.seg.myFill.below=v?v.seg.myFill.above:i,h.seg.myFill.above=m?!h.seg.myFill.below:h.seg.myFill.below):null===h.seg.otherFill&&(y=v?h.primary===v.primary?v.seg.otherFill.above:v.seg.myFill.above:h.primary?o:i,h.seg.otherFill={above:y,below:y}),r&&r.status(h.seg,!!d&&d.seg,!!v&&v.seg),h.other.status=p.insert(n.node({ev:h}))}else{var b=h.status;if(null===b)throw new Error(\"PolyBool: Zero-length segment detected; your epsilon is probably too small or too large\");if(s.exists(b.prev)&&s.exists(b.next)&&c(b.prev.ev,b.next.ev),r&&r.statusRemove(b.ev.seg),b.remove(),!h.primary){var 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r=t.root,n=t.root.next;null!==n&&!e(n);)r=n,n=n.next;return{before:r===t.root?null:r,after:n,insert:function(t){return t.prev=r,t.next=n,r.next=t,null!==n&&(n.prev=t),t}}}};return t},node:function(t){return t.prev=null,t.next=null,t.remove=function(){t.prev.next=t.next,t.next&&(t.next.prev=t.prev),t.prev=null,t.next=null},t}}},11403:function(t){t.exports=function(t,e,r){var n=[],i=[];return t.forEach((function(t){var a=t.start,o=t.end;if(e.pointsSame(a,o))console.warn(\"PolyBool: Warning: Zero-length segment detected; your epsilon is probably too small or too large\");else{r&&r.chainStart(t);for(var s={index:0,matches_head:!1,matches_pt1:!1},l={index:0,matches_head:!1,matches_pt1:!1},u=s,c=0;c<n.length;c++){var f=(g=n[c])[0],h=(g[1],g[g.length-1]);if(g[g.length-2],e.pointsSame(f,a)){if(k(c,!0,!0))break}else if(e.pointsSame(f,o)){if(k(c,!0,!1))break}else if(e.pointsSame(h,a)){if(k(c,!1,!0))break}else if(e.pointsSame(h,o)&&k(c,!1,!1))break}if(u===s)return 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a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],u=o[0],c=o[1];e.pointsCollinear(l,s,u)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,u,c)&&(r&&r.chainRemoveHead(i,u),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},82368:function(t){function e(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var r={union:function(t,r){return e(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],r)},intersect:function(t,r){return e(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],r)},difference:function(t,r){return e(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],r)},differenceRev:function(t,r){return e(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],r)},xor:function(t,r){return e(t,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],r)}};t.exports=r},9696:function(t,e,r){\"use 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this.big_endian?16777216*r[t]+65536*r[t+1]+256*r[t+2]+r[t+3]:r[t]+256*r[t+1]+65536*r[t+2]+16777216*r[t+3]},n.prototype.is_subifd_link=function(t,e){return 0===t&&34665===e||0===t&&34853===e||34665===t&&40965===e},n.prototype.exif_format_length=function(t){switch(t){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}},n.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return this.read_uint32(e);case 9:return 0|this.read_uint32(e);default:return null}},n.prototype.scan_ifd=function(t,n,i){var a=this.read_uint16(n);n+=2;for(var o=0;o<a;o++){var s=this.read_uint16(n),l=this.read_uint16(n+2),u=this.read_uint32(n+4),c=this.exif_format_length(l),f=u*c,h=f<=4?n+8:this.read_uint32(n+8),p=!1;if(h+f>this.input.length)throw e(\"unexpected EOF\",\"EBADDATA\");for(var d=[],v=h,g=0;g<u;g++,v+=c){var y=this.exif_format_read(l,v);if(null===y){d=null;break}d.push(y)}if(Array.isArray(d)&&2===l&&(d=r(String.fromCharCode.apply(null,d)))&&\"\\0\"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===i({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:u,entry_offset:n+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);n+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(n)})},t.exports.ExifParser=n,t.exports.get_orientation=function(t){var e=0;try{return new n(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},44600:function(t,e,r){\"use strict\";var n=r(9696).eW,i=r(9696).eI;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return 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t=l(t,\"float64\"),r.count=Math.floor(t.length/2),r.bounds=n(t,2),r.offset=e,e+=r.count,t}},{color:function(t,e){var r=e.count;if(t||(t=\"transparent\"),!Array.isArray(t)||\"number\"==typeof t[0]){var n=t;t=Array(r);for(var a=0;a<r;a++)t[a]=n}if(t.length<r)throw Error(\"Not enough colors\");for(var o=new Uint8Array(4*r),s=0;s<r;s++){var l=i(t[s],\"uint8\");o.set(l,4*s)}return o},range:function(t,e,r){var n=e.bounds;return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=f(e.scale),e.translateFract=f(e.translate),t},viewport:function(t){var e;return Array.isArray(t)?e={x:t[0],y:t[1],width:t[2]-t[0],height:t[3]-t[1]}:t?(e={x:t.x||t.left||0,y:t.y||t.top||0},t.right?e.width=t.right-e.x:e.width=t.w||t.width||0,t.bottom?e.height=t.bottom-e.y:e.height=t.h||t.height||0):e={x:0,y:0,width:y.drawingBufferWidth,height:y.drawingBufferHeight},e}}]),c):c})),e||r){var h=x.reduce((function(t,e,r){return t+(e?e.count:0)}),0),g=new Float64Array(2*h),_=new Uint8Array(4*h),w=new Float32Array(4*h);x.forEach((function(t,e){if(t){var r=t.positions,n=t.count,i=t.offset,a=t.color,o=t.errors;n&&(_.set(a,4*i),w.set(o,4*i),g.set(r,2*i))}}));var T=c(g);u(T);var k=f(g,T);p(k),d(_),v(w)}}}function k(){u.destroy(),p.destroy(),d.destroy(),v.destroy(),g.destroy()}};var h=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},13472:function(t,e,r){\"use strict\";var n=r(72160),i=r(76752),a=r(50896),o=r(55616),s=r(47520),l=r(28912),u=r(71152),c=r(37816),f=c.float32,h=c.fract32,p=r(60463),d=r(51160),v=r(10272);function g(t,e){if(!(this instanceof g))return new g(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=g.shaders.has(t)?g.shaders.get(t):g.shaders.set(t,g.createShaders(t)).get(t),this.update(e)}t.exports=g,g.dashMult=2,g.maxPatternLength=256,g.precisionThreshold=3e6,g.maxPoints=1e4,g.maxLines=2048,g.shaders=new p,g.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashTexture:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashLength:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:\"\\nprecision highp float;\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\",frag:\"\\nprecision highp float;\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\",attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:\"\\nprecision highp float;\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\",frag:\"\\nprecision highp float;\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\",attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:\"\\nprecision highp float;\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat 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at=0;at<t.dashes.length;++at){for(var ot=0,st=t.dashes[at]*g.dashMult*.5;ot<st;++ot)Q[rt++]=nt;nt^=255}}y.dashLength=tt,y.dashTexture({channels:1,data:Q,width:Q.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var lt=y.count,ut=t.color;ut||(ut=\"transparent\");var ct=new Uint8Array(4*lt+4);if(Array.isArray(ut)&&\"number\"!=typeof ut[0]){for(var ft=0;ft<lt;ft++){var ht=n(ut[ft],\"uint8\");ct.set(ht,4*ft)}ct.set(n(ut[0],\"uint8\"),4*lt)}else for(var pt=n(ut,\"uint8\"),dt=0;dt<lt+1;dt++)ct.set(pt,4*dt);y.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:ct})}}else e.passes[p]=null})),t.length<this.passes.length){for(var p=t.length;p<this.passes.length;p++){var y=this.passes[p];y&&(y.colorBuffer.destroy(),y.positionBuffer.destroy(),y.dashTexture.destroy())}this.passes.length=t.length}for(var m=[],x=0;x<this.passes.length;x++)null!==this.passes[x]&&m.push(this.passes[x]);return this.passes=m,this}},g.prototype.destroy=function(){return 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Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),c(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{constPointSize:!!e.constPointSize,opacity:t.prop(\"opacity\"),paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},pixelRatio:t.context(\"pixelRatio\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),markerTexture:t.prop(\"markerTexture\"),paletteTexture:n},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return 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vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragColor = color;\\n  fragBorderColor = borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n\\n  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\\n\"]),this.drawMarker=t(s);var l=c({},o);l.frag=f([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nuniform float opacity;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=f([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\n// `invariant` effectively turns off optimizations for the position.\\n// We need this because -fast-math on M1 Macs is re-ordering\\n// floating point operations in a way that causes floating point\\n// precision limits to put points in the wrong locations.\\ninvariant gl_Position;\\n\\nuniform bool constPointSize;\\nuniform float pixelRatio;\\nuniform vec2 paletteSize, scale, scaleFract, translate, translateFract;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(paletteTexture,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),v&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}x.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},x.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},x.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},x.prototype.drawItem=function(t,e){var r,n=this.groups,o=n[t];if(\"number\"==typeof e&&(t=e,o=n[e],e=null),o&&o.count&&o.opacity){o.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,o,e));for(var s=[],l=1;l<o.activation.length;l++)o.activation[l]&&(!0===o.activation[l]||o.activation[l].data.length)&&s.push.apply(s,function(t){if(Array.isArray(t))return a(t)}(r=this.getMarkerDrawOptions(l,o,e))||function(t){if(\"undefined\"!=typeof Symbol&&null!=t[Symbol.iterator]||null!=t[\"@@iterator\"])return Array.from(t)}(r)||i(r)||function(){throw new TypeError(\"Invalid attempt to spread non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}());s.length&&this.drawMarker(s)}},x.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,u=e.count;if(this.regl,!a)return r?[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var f=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(u),v=0;v<r.length;v++){var g=r[v];d[g]=p?p[g]:1}l.subdata(d)}for(var y=h.length;y--;){var m=n(h[y],2),x=m[0],b=m[1];f.push(c({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return f},x.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,l=this.maxSize,f=this.maxColors,v=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=h(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},e=c({},x.defaults,e)),e.positions&&!(\"marker\"in e)&&(e.marker=n.marker,delete n.marker),e.marker&&!(\"positions\"in e)&&(e.positions=n.positions,delete n.positions);var m=0,b=0;if(p(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=x.defaults.size),m+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=x.defaults.borderSize),m+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=x.defaults.color),e=t.updateColor(e),b++,e},borderColor:function(e,r){return null==e&&(e=x.defaults.borderColor),e=t.updateColor(e),b++,e},bounds:function(t,e,r){return\"range\"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,i=e.positionBuffer,a=e.positionFractBuffer,l=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=d(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?s(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}var p=g.float32(t);return i({data:p,usage:\"dynamic\"}),a({data:g.fract32(t,p),usage:\"dynamic\"}),l({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var u=t.addMarker(e[s]);a[u]||(a[u]=new Uint8Array(r.count)),a[u][s]=1}for(var c=0;c<a.length;c++)if(a[c]){var f={data:a[c],type:\"uint8\",usage:\"static\"};i[c]?i[c](f):i[c]=o.buffer(f),i[c].data=a[c]}}else i[t.addMarker(e)]=!0;return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=g.fract(e.scale),e.translateFract=g.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),m){var _=n,w=_.count,T=_.size,k=_.borderSize,A=_.sizeBuffer,M=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)M[2*S]=Math.round(255*(null==T[S]?T:T[S])/l),M[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/l);A({data:M,usage:\"dynamic\"})}if(b){var E,L=n,C=L.count,P=L.color,O=L.borderColor,I=L.colorBuffer;if(t.tooManyColors){if(P.length||O.length){E=new Uint8Array(8*C);for(var z=0;z<C;z++){var D=P[z];E[8*z]=v[4*D],E[8*z+1]=v[4*D+1],E[8*z+2]=v[4*D+2],E[8*z+3]=v[4*D+3];var R=O[z];E[8*z+4]=v[4*R],E[8*z+5]=v[4*R+1],E[8*z+6]=v[4*R+2],E[8*z+7]=v[4*R+3]}}}else if(P.length||O.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%f,E[4*F+1]=Math.floor(P[F]/f)),null!=O[F]&&(E[4*F+2]=O[F]%f,E[4*F+3]=Math.floor(O[F]/f))}I({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},x.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},x.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var s=0;s<t.length;s+=4)a.push(t.slice(s,s+4));else for(var u=0;u<t.length;u+=4)a.push(t.subarray(u,u+4));t=a}for(var c=0;c<t.length;c++){var f=t[c];f=o(f,\"uint8\");var h=l(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[c]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},x.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},x.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var b=r(50896);t.exports=function(t,e){var r=new m(t,e),n=r.render.bind(r);return b(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},55795:function(t,e,r){\"use strict\";var n=r(38540),i=r(55616),a=r(76752),o=r(3951),s=r(67752),l=r(51160),u=r(47520);function c(t,e){if(!(this instanceof c))return new c(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x,s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y,l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}t.exports=c,c.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},c.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,u=0;u<l.length;u++)i.push(this.passes[l[u]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},c.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values 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Uint8Array}),color:\"black\",marker:null,size:12,borderColor:\"transparent\",borderSize:1,viewport:l([r._gl.drawingBufferWidth,r._gl.drawingBufferHeight]),padding:[0,0,0,0],opacity:1,diagonal:!0,upper:!0,lower:!0});if(null!=o.color&&(s.color=o.color),null!=o.size&&(s.size=o.size),null!=o.marker&&(s.marker=o.marker),null!=o.borderColor&&(s.borderColor=o.borderColor),null!=o.borderSize&&(s.borderSize=o.borderSize),null!=o.opacity&&(s.opacity=o.opacity),o.viewport&&(s.viewport=l(o.viewport)),null!=o.diagonal&&(s.diagonal=o.diagonal),null!=o.upper&&(s.upper=o.upper),null!=o.lower&&(s.lower=o.lower),o.data){s.buffer(u(o.data)),s.columns=o.data.length,s.count=o.data[0].length,s.bounds=[];for(var c=0;c<s.columns;c++)s.bounds[c]=a(o.data[c],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var v=s.columns,g=s.count,y=s.viewport.width,m=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=y/v,w=m/v;s.passes=[];for(var T=0;T<v;T++)for(var k=0;k<v;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=f(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:g,stride:v},y:{buffer:s.buffer,offset:T,count:g,stride:v}}:M.positions={x:{buffer:s.buffer,offset:k*g,count:g},y:{buffer:s.buffer,offset:T*g,count:g}},M.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),L=E[0],C=E[1],P=E[2],O=E[3];M.viewport=[x+L*y+S[0],b+C*m+S[1],x+P*y-S[2],b+O*m-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?h(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},c.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var u=e[i],c=this.traces[i],f=c.passes,h=c.passOffset;f=f.map((function(t,e){n[h+e]=u}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},c.prototype.destroy=function(){return this.traces.forEach((function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()})),this.traces=null,this.passes=null,this.scatter.destroy(),this}},28624:function(t){t.exports=function(){function t(t,e){this.id=W++,this.type=t,this.data=e}function e(t){if(0===t.length)return[];var r=t.charAt(0),n=t.charAt(t.length-1);if(1<t.length&&r===n&&('\"'===r||\"'\"===r))return['\"'+t.substr(1,t.length-2).replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];if(r=/\\[(false|true|null|\\d+|'[^']*'|\"[^\"]*\")\\]/.exec(t))return e(t.substr(0,r.index)).concat(e(r[1])).concat(e(t.substr(r.index+r[0].length)));if(1===(r=t.split(\".\")).length)return['\"'+t.replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];for(t=[],n=0;n<r.length;++n)t=t.concat(e(r[n]));return t}function r(t){return\"[\"+e(t).join(\"][\")+\"]\"}function n(t){return\"string\"==typeof t?t.split():t}function i(t){return\"string\"==typeof t?document.querySelector(t):t}function a(t){var e,r,a,o,s=t||{};t={};var 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),13},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),400},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(t,e,r){return(this._validate(t,e,r,n.local.invalidDate).day()+1)%8},weekDay:function(t,e,r){var n=this.dayOfWeek(t,e,r);return n>=2&&n<=6},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{century:o[Math.floor((i.year()-1)/100)+1]||\"\"}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year()+(i.year()<0?1:0),e=i.month(),(r=i.day())+(e>1?16:0)+(e>2?32*(e-2):0)+400*(t-1)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t+.5)-Math.floor(this.jdEpoch)-1;var e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},65168:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return this.newDate(r,n,i)}}),n.calendars.ethiopian=a},2084:function(t,e,r){var n=r(38700),i=r(50896);function 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return this._leapYear(e.year())},_leapYear:function(t){return o(7*(t=t<0?t+1:t)+1,19)<7},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),this._leapYear(t.year?t.year():t)?13:12},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),this.toJD(-1===t?1:t+1,7,1)-this.toJD(t,7,1)},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),12===e&&this.leapYear(t)||8===e&&5===o(this.daysInYear(t),10)?30:9===e&&3===o(this.daysInYear(t),10)?29:this.daysPerMonth[e-1]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return 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e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},24747:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},65616:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return 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o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},73040:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),void 0===this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),void 0===this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var u=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(u)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(u,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var u=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,u)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)void 0===this.NEPALI_CALENDAR_DATA[r]&&(this.NEPALI_CALENDAR_DATA[r]=e)},NEPALI_CALENDAR_DATA:{1970:[18,31,31,32,31,31,31,30,29,30,29,30,30],1971:[18,31,31,32,31,32,30,30,29,30,29,30,30],1972:[17,31,32,31,32,31,30,30,30,29,29,30,30],1973:[19,30,32,31,32,31,30,30,30,29,30,29,31],1974:[19,31,31,32,30,31,31,30,29,30,29,30,30],1975:[18,31,31,32,32,30,31,30,29,30,29,30,30],1976:[17,31,32,31,32,31,30,30,30,29,29,30,31],1977:[18,31,32,31,32,31,31,29,30,29,30,29,31],1978:[18,31,31,32,31,31,31,30,29,30,29,30,30],1979:[18,31,31,32,32,31,30,30,29,30,29,30,30],1980:[17,31,32,31,32,31,30,30,30,29,29,30,31],1981:[18,31,31,31,32,31,31,29,30,30,29,30,30],1982:[18,31,31,32,31,31,31,30,29,30,29,30,30],1983:[18,31,31,32,32,31,30,30,29,30,29,30,30],1984:[17,31,32,31,32,31,30,30,30,29,29,30,31],1985:[18,31,31,31,32,31,31,29,30,30,29,30,30],1986:[18,31,31,32,31,31,31,30,29,30,29,30,30],1987:[18,31,32,31,32,31,30,30,29,30,29,30,30],1988:[17,31,32,31,32,31,30,30,30,29,29,30,31],1989:[18,31,31,31,32,31,31,30,29,30,29,30,30],1990:[18,31,31,32,31,31,31,30,29,30,29,30,30],1991:[18,31,32,31,32,31,30,30,29,30,29,30,30],1992:[17,31,32,31,32,31,30,30,30,29,30,29,31],1993:[18,31,31,31,32,31,31,30,29,30,29,30,30],1994:[18,31,31,32,31,31,31,30,29,30,29,30,30],1995:[17,31,32,31,32,31,30,30,30,29,29,30,30],1996:[17,31,32,31,32,31,30,30,30,29,30,29,31],1997:[18,31,31,32,31,31,31,30,29,30,29,30,30],1998:[18,31,31,32,31,31,31,30,29,30,29,30,30],1999:[17,31,32,31,32,31,30,30,30,29,29,30,31],2e3:[17,30,32,31,32,31,30,30,30,29,30,29,31],2001:[18,31,31,32,31,31,31,30,29,30,29,30,30],2002:[18,31,31,32,32,31,30,30,29,30,29,30,30],2003:[17,31,32,31,32,31,30,30,30,29,29,30,31],2004:[17,30,32,31,32,31,30,30,30,29,30,29,31],2005:[18,31,31,32,31,31,31,30,29,30,29,30,30],2006:[18,31,31,32,32,31,30,30,29,30,29,30,30],2007:[17,31,32,31,32,31,30,30,30,29,29,30,31],2008:[17,31,31,31,32,31,31,29,30,30,29,29,31],2009:[18,31,31,32,31,31,31,30,29,30,29,30,30],2010:[18,31,31,32,32,31,30,30,29,30,29,30,30],2011:[17,31,32,31,32,31,30,30,30,29,29,30,31],2012:[17,31,31,31,32,31,31,29,30,30,29,30,30],2013:[18,31,31,32,31,31,31,30,29,30,29,30,30],2014:[18,31,31,32,32,31,30,30,29,30,29,30,30],2015:[17,31,32,31,32,31,30,30,30,29,29,30,31],2016:[17,31,31,31,32,31,31,29,30,30,29,30,30],2017:[18,31,31,32,31,31,31,30,29,30,29,30,30],2018:[18,31,32,31,32,31,30,30,29,30,29,30,30],2019:[17,31,32,31,32,31,30,30,30,29,30,29,31],2020:[17,31,31,31,32,31,31,30,29,30,29,30,30],2021:[18,31,31,32,31,31,31,30,29,30,29,30,30],2022:[17,31,32,31,32,31,30,30,30,29,29,30,30],2023:[17,31,32,31,32,31,30,30,30,29,30,29,31],2024:[17,31,31,31,32,31,31,30,29,30,29,30,30],2025:[18,31,31,32,31,31,31,30,29,30,29,30,30],2026:[17,31,32,31,32,31,30,30,30,29,29,30,31],2027:[17,30,32,31,32,31,30,30,30,29,30,29,31],2028:[17,31,31,32,31,31,31,30,29,30,29,30,30],2029:[18,31,31,32,31,32,30,30,29,30,29,30,30],2030:[17,31,32,31,32,31,30,30,30,30,30,30,31],2031:[17,31,32,31,32,31,31,31,31,31,31,31,31],2032:[17,32,32,32,32,32,32,32,32,32,32,32,32],2033:[18,31,31,32,32,31,30,30,29,30,29,30,30],2034:[17,31,32,31,32,31,30,30,30,29,29,30,31],2035:[17,30,32,31,32,31,31,29,30,30,29,29,31],2036:[17,31,31,32,31,31,31,30,29,30,29,30,30],2037:[18,31,31,32,32,31,30,30,29,30,29,30,30],2038:[17,31,32,31,32,31,30,30,30,29,29,30,31],2039:[17,31,31,31,32,31,31,29,30,30,29,30,30],2040:[17,31,31,32,31,31,31,30,29,30,29,30,30],2041:[18,31,31,32,32,31,30,30,29,30,29,30,30],2042:[17,31,32,31,32,31,30,30,30,29,29,30,31],2043:[17,31,31,31,32,31,31,29,30,30,29,30,30],2044:[17,31,31,32,31,31,31,30,29,30,29,30,30],2045:[18,31,32,31,32,31,30,30,29,30,29,30,30],2046:[17,31,32,31,32,31,30,30,30,29,29,30,31],2047:[17,31,31,31,32,31,31,30,29,30,29,30,30],2048:[17,31,31,32,31,31,31,30,29,30,29,30,30],2049:[17,31,32,31,32,31,30,30,30,29,29,30,30],2050:[17,31,32,31,32,31,30,30,30,29,30,29,31],2051:[17,31,31,31,32,31,31,30,29,30,29,30,30],2052:[17,31,31,32,31,31,31,30,29,30,29,30,30],2053:[17,31,32,31,32,31,30,30,30,29,29,30,30],2054:[17,31,32,31,32,31,30,30,30,29,30,29,31],2055:[17,31,31,32,31,31,31,30,29,30,30,29,30],2056:[17,31,31,32,31,32,30,30,29,30,29,30,30],2057:[17,31,32,31,32,31,30,30,30,29,29,30,31],2058:[17,30,32,31,32,31,30,30,30,29,30,29,31],2059:[17,31,31,32,31,31,31,30,29,30,29,30,30],2060:[17,31,31,32,32,31,30,30,29,30,29,30,30],2061:[17,31,32,31,32,31,30,30,30,29,29,30,31],2062:[17,30,32,31,32,31,31,29,30,29,30,29,31],2063:[17,31,31,32,31,31,31,30,29,30,29,30,30],2064:[17,31,31,32,32,31,30,30,29,30,29,30,30],2065:[17,31,32,31,32,31,30,30,30,29,29,30,31],2066:[17,31,31,31,32,31,31,29,30,30,29,29,31],2067:[17,31,31,32,31,31,31,30,29,30,29,30,30],2068:[17,31,31,32,32,31,30,30,29,30,29,30,30],2069:[17,31,32,31,32,31,30,30,30,29,29,30,31],2070:[17,31,31,31,32,31,31,29,30,30,29,30,30],2071:[17,31,31,32,31,31,31,30,29,30,29,30,30],2072:[17,31,32,31,32,31,30,30,29,30,29,30,30],2073:[17,31,32,31,32,31,30,30,30,29,29,30,31],2074:[17,31,31,31,32,31,31,30,29,30,29,30,30],2075:[17,31,31,32,31,31,31,30,29,30,29,30,30],2076:[16,31,32,31,32,31,30,30,30,29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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(i.year()),a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=this._t2gYear(i.year()),a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},4592:function(t,e,r){var n=r(38700),i=r(50896),a=n.instance();function o(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}o.prototype=new 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(i.year()),a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=this._t2gYear(i.year()),a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},45348:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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n=r(50896);function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(u.local.differentCalendars||u.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day(),\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),i=new Date(n.year(),n.month()-1,n.day());return i.setHours(0),i.setMinutes(0),i.setSeconds(0),i.setMilliseconds(0),i.setHours(i.getHours()>12?i.getHours()+2:0),i},fromJSDate:function(t){return this.newDate(t.getFullYear(),t.getMonth()+1,t.getDate())}});var u=t.exports=new i;u.cdate=a,u.baseCalendar=s,u.calendars.gregorian=l},15168:function(t,e,r){var n=r(50896),i=r(38700);n(i.regionalOptions[\"\"],{invalidArguments:\"Invalid arguments\",invalidFormat:\"Cannot format a date from another calendar\",missingNumberAt:\"Missing number at position {0}\",unknownNameAt:\"Unknown name at position {0}\",unexpectedLiteralAt:\"Unexpected literal at position {0}\",unexpectedText:\"Additional text found at end\"}),i.local=i.regionalOptions[\"\"],n(i.cdate.prototype,{formatDate:function(t,e){return\"string\"!=typeof 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        "                            \n",
-       "var gd = document.getElementById('7d49a7d2-77b4-4a8d-81af-269e07c693cb');\n",
+       "var gd = document.getElementById('f49004bd-b5cd-468a-b4bb-1472b9c9154b');\n",
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From b1d9fa415d654d4f78ca2b820b8a98e721bdebac Mon Sep 17 00:00:00 2001
From: franciscoeacosta <facosta@ucsb.edu>
Date: Tue, 24 Jun 2025 11:18:57 -0700
Subject: [PATCH 6/6] merge main

---
 neurometry/estimators/topology/plotting.py    | 90 +++++++++++++++++++
 ...3_methods_estimate_manifold_topology.ipynb |  2 +-
 2 files changed, 91 insertions(+), 1 deletion(-)

diff --git a/neurometry/estimators/topology/plotting.py b/neurometry/estimators/topology/plotting.py
index 7fb2651..0c8ff35 100644
--- a/neurometry/estimators/topology/plotting.py
+++ b/neurometry/estimators/topology/plotting.py
@@ -124,6 +124,96 @@ def plot_all_barcodes_with_null(
     return fig
 
 
+# def plot_all_barcodes(diagrams1, diagrams2, dataset_name_1, dataset_name_2, **kwargs):
+#     dims = np.unique(diagrams1[diagrams1[:, 2] > 0, 2]).astype(int)
+
+#     num_dims = len(dims)
+#     colors = plt.cm.Greens(np.linspace(0.5, 1, num_dims))
+
+#     fig, axs = plt.subplots(
+#         num_dims, 1, figsize=kwargs.get("figsize", (10, 5 * num_dims)), sharex=True
+#     )
+
+#     for i, dim in enumerate(dims):
+#         color = colors[i % len(colors)]
+
+#         ax = axs[i] if num_dims > 1 else axs
+#         diag_dim1 = diagrams1[diagrams1[:, 2] == dim]
+#         diag_dim2 = diagrams2[diagrams2[:, 2] == dim]
+#         _plot_bars_from_diagrams(
+#             ax,
+#             diag_dim1,
+#             color=color,
+#             linewidth=6,
+#             bar_offset=kwargs.get("bar_offset", 0.2),
+#         )
+#         _plot_bars_from_diagrams(
+#             ax,
+#             diag_dim2,
+#             color=color,
+#             linewidth=6,
+#             bar_offset=kwargs.get("bar_offset", 0.2),
+#         )
+#         ax.set_ylabel(f"Homology {dim}", fontsize=24)
+#         ax.set_yticks([])
+#         if i == num_dims - 1:
+#             ax.set_xlabel(kwargs.get("xlabel", "Filtration Value"), fontsize=24)
+#         if i == 0:
+#             ax.set_title(dataset_name, fontsize=30)
+
+#     plt.tight_layout()
+#     return fig
+
+def plot_all_barcodes(diagrams1, diagrams2, dataset_name_1, dataset_name_2, **kwargs):
+    dims = np.unique(diagrams1[diagrams1[:, 2] > 0, 2]).astype(int)
+
+    num_dims = len(dims)
+    colors = plt.cm.Greens(np.linspace(0.5, 1, num_dims))
+
+    fig, axs = plt.subplots(
+        num_dims, 2, figsize=kwargs.get("figsize", (20, 5 * num_dims)), sharex=True
+    )
+
+    for i, dim in enumerate(dims):
+        color = colors[i % len(colors)]
+
+        # Plot diagrams1
+        ax1 = axs[i, 0] if num_dims > 1 else axs[0]
+        diag_dim1 = diagrams1[diagrams1[:, 2] == dim]
+        _plot_bars_from_diagrams(
+            ax1,
+            diag_dim1,
+            color=color,
+            linewidth=6,
+            bar_offset=kwargs.get("bar_offset", 0.2),
+        )
+        ax1.set_ylabel(f"Homology {dim}", fontsize=24)
+        ax1.set_yticks([])
+        if i == num_dims - 1:
+            ax1.set_xlabel(kwargs.get("xlabel", "Filtration Value"), fontsize=24)
+        if i == 0:
+            ax1.set_title(dataset_name_1, fontsize=30)
+
+        # Plot diagrams2
+        ax2 = axs[i, 1] if num_dims > 1 else axs[1]
+        diag_dim2 = diagrams2[diagrams2[:, 2] == dim]
+        _plot_bars_from_diagrams(
+            ax2,
+            diag_dim2,
+            color=color,
+            linewidth=6,
+            bar_offset=kwargs.get("bar_offset", 0.2),
+        )
+        ax2.set_yticks([])
+        if i == num_dims - 1:
+            ax2.set_xlabel(kwargs.get("xlabel", "Filtration Value"), fontsize=24)
+        if i == 0:
+            ax2.set_title(dataset_name_2, fontsize=30)
+
+    plt.tight_layout()
+    return fig
+
+
 def plot_activity_on_torus(
     neural_activations, toroidal_coords, neuron_id, neuron_id2=None
 ):
diff --git a/tutorials/03_methods_estimate_manifold_topology.ipynb b/tutorials/03_methods_estimate_manifold_topology.ipynb
index 883b99b..57e31a1 100644
--- a/tutorials/03_methods_estimate_manifold_topology.ipynb
+++ b/tutorials/03_methods_estimate_manifold_topology.ipynb
@@ -43073,7 +43073,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "neurometry",
    "language": "python",
    "name": "python3"
   },