From a3f4d334f6d1d899df2d153316f05895cbad18ab Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Wed, 6 May 2026 17:07:05 +0200
Subject: [PATCH 01/23] move compute from tof to separate file, add new compute
 from chopper_cascade

---
 .../src/ess/reduce/unwrap/__init__.py         |  14 +-
 .../essreduce/src/ess/reduce/unwrap/lut.py    | 456 +++++------------
 .../src/ess/reduce/unwrap/lut_from_tof.py     | 471 ++++++++++++++++++
 .../essreduce/src/ess/reduce/unwrap/types.py  |  57 +++
 4 files changed, 676 insertions(+), 322 deletions(-)
 create mode 100644 packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py

diff --git a/packages/essreduce/src/ess/reduce/unwrap/__init__.py b/packages/essreduce/src/ess/reduce/unwrap/__init__.py
index c0d21027c..02b5e9fc3 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/__init__.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/__init__.py
@@ -8,17 +8,21 @@
 
 from ..nexus.types import DiskChoppers
 from .lut import (
-    BeamlineComponentReading,
     DistanceResolution,
     LookupTableWorkflow,
     LtotalRange,
-    NumberOfSimulatedNeutrons,
     PulsePeriod,
     PulseStride,
-    SimulationResults,
-    SimulationSeed,
     SourcePosition,
+    SourcePulse,
     TimeResolution,
+)
+from .lut_from_tof import (
+    BeamlineComponentReading,
+    LookupTableFromTofWorkflow,
+    NumberOfSimulatedNeutrons,
+    SimulationResults,
+    SimulationSeed,
     simulate_chopper_cascade_using_tof,
 )
 from .to_wavelength import providers
@@ -44,6 +48,7 @@
     "GenericUnwrapWorkflow",
     "LookupTable",
     "LookupTableFilename",
+    "LookupTableFromTofWorkflow",
     "LookupTableRelativeErrorThreshold",
     "LookupTableWorkflow",
     "LtotalRange",
@@ -55,6 +60,7 @@
     "SimulationResults",
     "SimulationSeed",
     "SourcePosition",
+    "SourcePulse",
     "TimeResolution",
     "WavelengthDetector",
     "WavelengthMonitor",
diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index c76e031fb..aefe6f90a 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -1,148 +1,77 @@
 # SPDX-License-Identifier: BSD-3-Clause
 # Copyright (c) 2025 Scipp contributors (https://github.com/scipp)
 """
-Utilities for computing time-of-flight lookup tables from neutron simulations.
+Utilities for computing wavelength lookup tables.
 """
 
 from dataclasses import dataclass
 from typing import NewType
 
+import numpy as np
 import sciline as sl
 import scipp as sc
+from scippneutron.tof import chopper_cascade
 
 from ..nexus.types import AnyRun, DiskChoppers
-from .types import LookupTable
+from .types import (
+    DistanceResolution,
+    LookupTable,
+    LtotalRange,
+    PulsePeriod,
+    PulseStride,
+    SourcePosition,
+    SourcePulse,
+    TimeResolution,
+)
 
 
-@dataclass
-class BeamlineComponentReading:
-    """
-    Reading at a given position along the beamline from a time-of-flight simulation.
-    The data (apart from ``distance``) should be flat lists (1d arrays) of length N
-    where N is the number of neutrons, containing the properties of the neutrons in the
-    simulation.
+def _polygon_edges(polygons):
+    # polygons: list of (N_i, 2) arrays
+    edges = []
+    for poly in polygons:
+        p1 = poly
+        p2 = np.roll(poly, -1, axis=0)
+        edges.append(np.stack([p1, p2], axis=1))  # (N, 2, 2)
+    return np.concatenate(edges, axis=0)  # (E, 2, 2)
 
-    Parameters
-    ----------
-    time_of_arrival:
-        Time of arrival of the neutrons at the position where the events were recorded
-        (1d array of size N).
-    wavelength:
-        Wavelength of the neutrons (1d array of size N).
-    weight:
-        Weight/probability of the neutrons (1d array of size N).
-    distance:
-        Distance from the source to the position where the events were recorded
-        (single value; we assume all neutrons were recorded at the same position).
-        For a ``tof`` simulation, this is just the position of the detector where the
-        events are recorded. For a ``McStas`` simulation, this is the distance between
-        the source and the event monitor.
-    """
 
-    time_of_arrival: sc.Variable
-    wavelength: sc.Variable
-    weight: sc.Variable
-    distance: sc.Variable
+def _polygon_intersections(polygons, xs):
+    edges = _polygon_edges(polygons)
 
-    def __post_init__(self):
-        self.speed = (sc.constants.h / sc.constants.m_n) / self.wavelength
+    x1 = edges[:, 0, 0][:, None]  # (E, 1)
+    y1 = edges[:, 0, 1][:, None]
+    x2 = edges[:, 1, 0][:, None]
+    y2 = edges[:, 1, 1][:, None]
 
+    xs = xs[None, :]  # (1, N)
 
-@dataclass
-class SimulationResults:
-    """
-    Results of a time-of-flight simulation used to create a lookup table.
-    It should contain readings at various positions along the beamline, e.g., at
-    the source and after each chopper.
-    It also contains the chopper parameters used in the simulation, so it can be
-    determined if this simulation is compatible with a given experiment.
-
-    Parameters
-    ----------
-    readings:
-        A dict of :class:`BeamlineComponentReading` objects representing the readings at
-        various positions along the beamline. The keys in the dict should correspond to
-        the names of the components (e.g., 'source', 'chopper1', etc.).
-    choppers:
-        The chopper parameters used in the simulation (if any). These are used to verify
-        that the simulation is compatible with a given experiment (comparing chopper
-        openings, frequencies, phases, etc.).
-    """
+    # mask: edge crosses vertical line at x
+    mask = ((x1 <= xs) & (x2 > xs)) | ((x2 <= xs) & (x1 > xs))
 
-    readings: dict[str, BeamlineComponentReading]
-    choppers: DiskChoppers[AnyRun] | None = None
+    # avoid division by zero (vertical edges won't pass mask anyway)
+    denom = x2 - x1
+    denom = np.where(denom == 0, np.nan, denom)
 
+    t = (xs - x1) / denom
+    y = y1 + t * (y2 - y1)
 
-NumberOfSimulatedNeutrons = NewType("NumberOfSimulatedNeutrons", int)
-"""
-Number of neutrons simulated in the simulation that is used to create the lookup table.
-This is typically a large number, e.g., 1e6 or 1e7.
-"""
+    # keep only valid intersections
+    y = np.where(mask, y, np.nan)
 
-LtotalRange = NewType("LtotalRange", tuple[sc.Variable, sc.Variable])
-"""
-Range (min, max) of the total length of the flight path from the source to the detector.
-This is used to create the lookup table to compute the neutron time-of-flight.
-Note that the resulting table will extend slightly beyond this range, as the supplied
-range is not necessarily a multiple of the distance resolution.
-
-Note also that the range of total flight paths is supplied manually to the workflow
-instead of being read from the input data, as it allows us to compute the expensive part
-of the workflow in advance (the lookup table) and does not need to be repeated for each
-run, or for new data coming in in the case of live data collection.
-"""
+    # now reduce along edges axis
+    y_min = np.nanmin(y, axis=0)
+    y_max = np.nanmax(y, axis=0)
 
-DistanceResolution = NewType("DistanceResolution", sc.Variable)
-"""
-Step size of the distance axis in the lookup table.
-Should be a single scalar value with a unit of length.
-This is typically of the order of 1-10 cm.
-"""
-
-TimeResolution = NewType("TimeResolution", sc.Variable)
-"""
-Step size of the event_time_offset axis in the lookup table.
-This is basically the 'time-of-flight' resolution of the detector.
-Should be a single scalar value with a unit of time.
-This is typically of the order of 0.1-0.5 ms.
-
-Since the event_time_offset range needs to span exactly one pulse period, the final
-resolution in the lookup table will be at least the supplied value here, but may be
-smaller if the pulse period is not an integer multiple of the time resolution.
-"""
-
-PulsePeriod = NewType("PulsePeriod", sc.Variable)
-"""
-Period of the source pulses, i.e., time between consecutive pulse starts.
-"""
-
-PulseStride = NewType("PulseStride", int)
-"""
-Stride of used pulses. Usually 1, but may be a small integer when pulse-skipping.
-"""
-
-SourcePosition = NewType("SourcePosition", sc.Variable)
-"""
-Position of the neutron source in the coordinate system of the choppers.
-"""
-
-SimulationSeed = NewType("SimulationSeed", int | None)
-"""Seed for the random number generator used in the simulation.
-"""
-
-SimulationFacility = NewType("SimulationFacility", str)
-"""
-Facility where the experiment is performed, e.g., 'ess'.
-"""
+    return 0.5 * (y_min + y_max)
 
 
 def _compute_mean_wavelength(
-    simulation: BeamlineComponentReading,
-    distance: sc.Variable,
-    time_bins: sc.Variable,
+    subframes: list[chopper_cascade.Subframe],
+    # distance: sc.Variable,
+    time_edges: sc.Variable,
     time_unit: str,
     frame_period: sc.Variable,
-    time_bins_half_width: sc.Variable,
+    # time_bins_half_width: sc.Variable,
 ) -> sc.DataArray:
     """
     Compute the mean time-of-flight inside event_time_offset bins for a given range of
@@ -150,64 +79,67 @@ def _compute_mean_wavelength(
 
     Parameters
     ----------
-    simulation:
-        Results of a time-of-flight simulation used to create a lookup table.
-    distance:
-        Distance where table is computed.
-    time_bins:
-        Bin edges for the event_time_offset axis in the lookup table.
-    time_unit:
-        Unit of the event_time_offset axis.
-    frame_period:
-        Period of the source pulses, i.e., time between consecutive pulse starts.
-    time_bins_half_width:
-        Half width of the time bins in the event_time_offset axis.
     """
-    travel_length = distance - simulation.distance.to(unit=distance.unit)
-    # Compute arrival and flight times for all neutrons
-    toas = simulation.time_of_arrival + (travel_length / simulation.speed).to(
-        unit=time_unit, copy=False
-    )
+    # at_sample = frames.propagate_to(sc.linspace('distance', 55., 75., N, unit='m'))
+    # subf = at_sample.frames[-1].subframes
+
+    # fig = at_sample.draw()
+    # p = d
+
+    polygons = [
+        np.stack([f.time.to(unit=time_unit).values, f.wavelength.values], axis=1)
+        for f in subframes
+    ] + [
+        np.stack(
+            [(f.time.to(unit=time_unit) - frame_period).values, f.wavelength.values],
+            axis=1,
+        )
+        for f in subframes
+    ]
 
-    data = sc.DataArray(
-        data=simulation.weight,
-        coords={"toa": toas, "wavelength": simulation.wavelength},
+    wavs = _polygon_intersections(polygons, time_edges.values)
+
+    return sc.array(
+        dims=time_edges.dims, values=wavs, unit=subframes[0].wavelength.unit
     )
 
-    # Add the event_time_offset coordinate, wrapped to the frame_period
-    data.coords['event_time_offset'] = data.coords['toa'] % frame_period
-
-    # Because we staggered the mesh by half a bin width, we want the values above
-    # the last bin edge to wrap around to the first bin.
-    # Technically, those values should end up between -0.5*bin_width and 0, but
-    # a simple modulo also works here because even if they end up between 0 and
-    # 0.5*bin_width, we are (below) computing the mean between -0.5*bin_width and
-    # 0.5*bin_width and it yields the same result.
-    # data.coords['event_time_offset'] %= pulse_period - time_bins_half_width
-    data.coords['event_time_offset'] %= frame_period - time_bins_half_width
-
-    binned = data.bin(event_time_offset=time_bins)
-    binned_sum = binned.bins.sum()
-    # Weighted mean of wavelength inside each bin
-    mean_wavelength = (
-        binned.bins.data * binned.bins.coords["wavelength"]
-    ).bins.sum() / binned_sum
-    # Compute the variance of the wavelengths to track regions with large uncertainty
-    variance = (
-        binned.bins.data * (binned.bins.coords["wavelength"] - mean_wavelength) ** 2
-    ).bins.sum() / binned_sum
-
-    mean_wavelength.variances = variance.values
-    return mean_wavelength
+
+def _compute_frame_sequence(
+    pulse_period: sc.Variable,
+    disk_choppers: DiskChoppers[AnyRun],
+    source_position: SourcePosition,
+    source_pulse: SourcePulse,
+) -> chopper_cascade.FrameSequence:
+    pulse_frequency = 1.0 / pulse_period.to(unit='s')
+
+    chops = {
+        key: chopper_cascade.Chopper(
+            distance=(ch.axle_position - source_position).fields.z,
+            time_open=ch.time_offset_open(pulse_frequency=pulse_frequency),
+            time_close=ch.time_offset_close(pulse_frequency=pulse_frequency),
+        )
+        for key, ch in disk_choppers.items()
+    }
+
+    frames = chopper_cascade.FrameSequence.from_source_pulse(
+        time_min=source_pulse.time[0],
+        time_max=source_pulse.time[1],
+        wavelength_min=source_pulse.wavelength[0],
+        wavelength_max=source_pulse.wavelength[1],
+    )
+    frames = frames.chop(chops.values())
+    return frames
 
 
 def make_wavelength_lookup_table(
-    simulation: SimulationResults,
+    choppers: DiskChoppers[AnyRun],
+    source_pulse: SourcePulse,
     ltotal_range: LtotalRange,
     distance_resolution: DistanceResolution,
     time_resolution: TimeResolution,
     pulse_period: PulsePeriod,
     pulse_stride: PulseStride,
+    source_position: SourcePosition,
 ) -> LookupTable:
     """
     Compute a lookup table for wavelength as a function of distance and
@@ -215,10 +147,6 @@ def make_wavelength_lookup_table(
 
     Parameters
     ----------
-    simulation:
-        Results of a time-of-flight simulation used to create a lookup table.
-        The results should be a flat table with columns for time-of-arrival,
-        wavelength, and weight.
     ltotal_range:
         Range of total flight path lengths from the source to the detector.
     distance_resolution:
@@ -230,43 +158,6 @@ def make_wavelength_lookup_table(
     pulse_stride:
         Stride of used pulses. Usually 1, but may be a small integer when
         pulse-skipping.
-
-    Notes
-    -----
-
-    Below are some details about the binning and wrapping around frame period in the
-    time dimension.
-
-    We have some simulated ``toa`` (events) from a Tof/McStas simulation.
-    Those are absolute ``toa``, unwrapped.
-    First we compute the usual ``event_time_offset = toa % frame_period``.
-
-    Now, we want to ensure periodic boundaries. If we make a bin centered around 0,
-    and a bin centered around 71ms: the first bin will use events between 0 and
-    ``0.5 * dt`` (where ``dt`` is the bin width).
-    The last bin will use events between ``frame_period - 0.5*dt`` and
-    ``frame_period + 0.5 * dt``. So when we compute the mean inside those two bins,
-    they will not yield the same results.
-    It is as if the first bin is missing the events it should have between
-    ``-0.5 * dt`` and 0 (because of the modulo we computed above).
-
-    To fix this, we do not make a last bin around 71ms (the bins stop at
-    ``frame_period - 0.5*dt``). Instead, we compute modulo a second time,
-    but this time using ``event_time_offset %= (frame_period - 0.5*dt)``.
-    (we cannot directly do ``event_time_offset = toa % (frame_period - 0.5*dt)`` in a
-    single step because it would introduce a gradual shift,
-    as the pulse number increases).
-
-    This second modulo effectively takes all the events that would have gone in the
-    last bin (between ``frame_period - 0.5*dt`` and ``frame_period``) and puts them in
-    the first bin. Instead of placing them between ``-0.5*dt`` and 0,
-    it places them between 0 and ``0.5*dt``, but this does not really matter,
-    because we then take the mean inside the first bin.
-    Whether the events are on the left or right side of zero does not matter.
-
-    Finally, we make a copy of the left edge, and append it to the right of the table,
-    thus ensuring that the values on the right edge are strictly the same as on the
-    left edge.
     """
     distance_unit = "m"
     time_unit = "us"
@@ -292,68 +183,65 @@ def make_wavelength_lookup_table(
 
     # Create some time bins for event_time_offset.
     # We want our final table to strictly cover the range [0, frame_period].
-    # However, binning the data associates mean values inside the bins to the bin
-    # centers. Instead, we stagger the mesh by half a bin width so we are computing
-    # values for the final mesh edges (the bilinear interpolation needs values on the
-    # edges/corners).
     nbins = int(frame_period / time_resolution.to(unit=time_unit)) + 1
-    time_bins = sc.linspace(
+    time_edges = sc.linspace(
         'event_time_offset', 0.0, frame_period.value, nbins + 1, unit=pulse_period.unit
     )
-    time_bins_half_width = 0.5 * (time_bins[1] - time_bins[0])
-    time_bins -= time_bins_half_width
 
-    # Sort simulation readings by reverse distance
-    sorted_simulation_results = sorted(
-        simulation.readings.values(), key=lambda x: x.distance.value, reverse=True
+    frames = _compute_frame_sequence(
+        pulse_period=pulse_period,
+        disk_choppers=choppers,
+        source_position=source_position,
+        source_pulse=source_pulse,
     )
 
+    # # Sort simulation readings by reverse distance
+    # sorted_simulation_results = sorted(
+    #     simulation.readings.values(), key=lambda x: x.distance.value, reverse=True
+    # )
+
     pieces = []
     # To avoid large RAM usage, and having to split the distances into chunks
     # according to which component reading to use, we simply loop over distances one
     # by one here.
     for dist in distances:
         # Find the correct simulation reading
-        simulation_reading = None
-        for reading in sorted_simulation_results:
-            if dist.value >= reading.distance.to(unit=dist.unit).value:
-                simulation_reading = reading
+        selected_frame = None
+        for frame in frames:
+            if dist.value >= frame.distance.to(unit=dist.unit).value:
+                selected_frame = frame
                 break
-        if simulation_reading is None:
-            closest = sorted_simulation_results[-1]
+        if selected_frame is None:
             raise ValueError(
                 "Building the lookup table failed: the requested position "
-                f"{dist.value} {dist.unit} is before the component with the lowest "
+                f"{dist:c} is before the component with the lowest "
                 "distance in the simulation. The first component in the beamline "
-                f"has distance {closest.distance.value} {closest.distance.unit}."
+                f"has distance {frames[0].distance:c}."
             )
 
+        # subframes = frames.propagate_to(dist).frames[-1].subframes
+        subframes = selected_frame.propagate_to(dist).subframes
+
         pieces.append(
             _compute_mean_wavelength(
-                simulation=simulation_reading,
-                distance=dist,
-                time_bins=time_bins,
+                subframes=subframes,
+                # distance=dist,
+                time_edges=time_edges,
                 time_unit=time_unit,
                 frame_period=frame_period,
-                time_bins_half_width=time_bins_half_width,
+                # time_bins_half_width=time_bins_half_width,
             )
         )
 
-    table = sc.concat(pieces, 'distance')
-    table.coords["event_time_offset"] = sc.midpoints(table.coords["event_time_offset"])
+    # frames.propagate_to(dist).draw()
+
+    # table = sc.concat(pieces, 'distance')
+    # table.coords["event_time_offset"] = sc.midpoints(table.coords["event_time_offset"])
 
     # Copy the left edge to the right to create periodic boundary conditions
     table = sc.DataArray(
-        data=sc.concat(
-            [table.data, table.data['event_time_offset', 0]], dim='event_time_offset'
-        ),
-        coords={
-            "distance": distances,
-            "event_time_offset": sc.concat(
-                [table.coords["event_time_offset"], frame_period],
-                dim='event_time_offset',
-            ),
-        },
+        data=sc.concat(pieces, 'distance'),
+        coords={"distance": distances, "event_time_offset": time_edges},
     )
 
     return LookupTable(
@@ -363,101 +251,33 @@ def make_wavelength_lookup_table(
         distance_resolution=table.coords["distance"][1] - table.coords["distance"][0],
         time_resolution=table.coords["event_time_offset"][1]
         - table.coords["event_time_offset"][0],
-        choppers=sc.DataGroup(
-            {k: sc.DataGroup(ch.as_dict()) for k, ch in simulation.choppers.items()}
-        )
-        if simulation.choppers is not None
-        else None,
+        # choppers=sc.DataGroup(
+        #     {k: sc.DataGroup(ch.as_dict()) for k, ch in simulation.choppers.items()}
+        # )
+        # if simulation.choppers is not None
+        # else None,
     )
 
 
-def _to_component_reading(component):
-    events = component.data.squeeze().flatten(to='event')
-    sel = sc.full(value=True, sizes=events.sizes)
-    for key in {'blocked_by_others', 'blocked_by_me'} & set(events.masks.keys()):
-        sel &= ~events.masks[key]
-    events = events[sel]
-    # If the component is a source, use 'birth_time' as 'toa'
-    toa = (
-        events.coords["toa"] if "toa" in events.coords else events.coords["birth_time"]
-    )
-    return BeamlineComponentReading(
-        time_of_arrival=toa,
-        wavelength=events.coords["wavelength"],
-        weight=events.data,
-        distance=component.distance,
-    )
-
-
-def simulate_chopper_cascade_using_tof(
-    choppers: DiskChoppers[AnyRun],
-    source_position: SourcePosition,
-    neutrons: NumberOfSimulatedNeutrons,
-    pulse_stride: PulseStride,
-    seed: SimulationSeed,
-    facility: SimulationFacility,
-) -> SimulationResults:
-    """
-    Simulate a pulse of neutrons propagating through a chopper cascade using the
-    ``tof`` package (https://scipp.github.io/tof).
-
-    Parameters
-    ----------
-    choppers:
-        A dict of DiskChopper objects representing the choppers in the beamline. See
-        https://scipp.github.io/scippneutron/user-guide/chopper/processing-nexus-choppers.html
-        for more information.
-    source_position:
-        A scalar variable with ``dtype=vector3`` that defines the source position.
-        Must be in the same coordinate system as the choppers' axle positions.
-    neutrons:
-        Number of neutrons to simulate.
-    pulse_stride:
-        The pulse strinde; we need to simulate at least enough pulses to cover the
-        requested stride.
-    seed:
-        Seed for the random number generator used in the simulation.
-    facility:
-        Facility where the experiment is performed.
-    """
-    import tof
-
-    tof_choppers = []
-    for name, ch in choppers.items():
-        chop = tof.Chopper.from_diskchopper(ch, name=name)
-        chop.distance = sc.norm(
-            ch.axle_position - source_position.to(unit=ch.axle_position.unit)
-        )
-        tof_choppers.append(chop)
-
-    source = tof.Source(
-        facility=facility, neutrons=neutrons, pulses=pulse_stride, seed=seed
-    )
-    sim_readings = {"source": _to_component_reading(source)}
-    if not tof_choppers:
-        return SimulationResults(readings=sim_readings, choppers=None)
-    model = tof.Model(source=source, choppers=tof_choppers)
-    results = model.run()
-    for name, ch in results.choppers.items():
-        sim_readings[name] = _to_component_reading(ch)
-    return SimulationResults(readings=sim_readings, choppers=choppers)
-
-
 def LookupTableWorkflow():
     """
     Create a workflow for computing a wavelength lookup table from a
     simulation of neutrons propagating through a chopper cascade.
     """
     wf = sl.Pipeline(
-        (make_wavelength_lookup_table, simulate_chopper_cascade_using_tof),
+        (make_wavelength_lookup_table,),
         params={
             PulsePeriod: 1.0 / sc.scalar(14.0, unit="Hz"),
             PulseStride: 1,
             DistanceResolution: sc.scalar(0.1, unit="m"),
             TimeResolution: sc.scalar(250.0, unit='us'),
-            NumberOfSimulatedNeutrons: 1_000_000,
-            SimulationSeed: None,
-            SimulationFacility: 'ess',
+            SourcePulse: SourcePulse(
+                time=(sc.scalar(0.0, unit='ms'), sc.scalar(4.0, unit='ms')),
+                wavelength=(
+                    sc.scalar(0.0, unit='angstrom'),
+                    sc.scalar(10.0, unit='angstrom'),
+                ),
+            ),
         },
     )
     return wf
diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py b/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py
new file mode 100644
index 000000000..52cf483ab
--- /dev/null
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py
@@ -0,0 +1,471 @@
+# SPDX-License-Identifier: BSD-3-Clause
+# Copyright (c) 2025 Scipp contributors (https://github.com/scipp)
+"""
+Utilities for computing time-of-flight lookup tables from neutron simulations.
+"""
+
+from dataclasses import dataclass
+from typing import NewType
+
+import sciline as sl
+import scipp as sc
+
+from ..nexus.types import AnyRun, DiskChoppers
+from .types import (
+    DistanceResolution,
+    LookupTable,
+    LtotalRange,
+    PulsePeriod,
+    PulseStride,
+    SourcePosition,
+    TimeResolution,
+)
+
+
+@dataclass
+class BeamlineComponentReading:
+    """
+    Reading at a given position along the beamline from a time-of-flight simulation.
+    The data (apart from ``distance``) should be flat lists (1d arrays) of length N
+    where N is the number of neutrons, containing the properties of the neutrons in the
+    simulation.
+
+    Parameters
+    ----------
+    time_of_arrival:
+        Time of arrival of the neutrons at the position where the events were recorded
+        (1d array of size N).
+    wavelength:
+        Wavelength of the neutrons (1d array of size N).
+    weight:
+        Weight/probability of the neutrons (1d array of size N).
+    distance:
+        Distance from the source to the position where the events were recorded
+        (single value; we assume all neutrons were recorded at the same position).
+        For a ``tof`` simulation, this is just the position of the detector where the
+        events are recorded. For a ``McStas`` simulation, this is the distance between
+        the source and the event monitor.
+    """
+
+    time_of_arrival: sc.Variable
+    wavelength: sc.Variable
+    weight: sc.Variable
+    distance: sc.Variable
+
+    def __post_init__(self):
+        self.speed = (sc.constants.h / sc.constants.m_n) / self.wavelength
+
+
+@dataclass
+class SimulationResults:
+    """
+    Results of a time-of-flight simulation used to create a lookup table.
+    It should contain readings at various positions along the beamline, e.g., at
+    the source and after each chopper.
+    It also contains the chopper parameters used in the simulation, so it can be
+    determined if this simulation is compatible with a given experiment.
+
+    Parameters
+    ----------
+    readings:
+        A dict of :class:`BeamlineComponentReading` objects representing the readings at
+        various positions along the beamline. The keys in the dict should correspond to
+        the names of the components (e.g., 'source', 'chopper1', etc.).
+    choppers:
+        The chopper parameters used in the simulation (if any). These are used to verify
+        that the simulation is compatible with a given experiment (comparing chopper
+        openings, frequencies, phases, etc.).
+    """
+
+    readings: dict[str, BeamlineComponentReading]
+    choppers: DiskChoppers[AnyRun] | None = None
+
+
+NumberOfSimulatedNeutrons = NewType("NumberOfSimulatedNeutrons", int)
+"""
+Number of neutrons simulated in the simulation that is used to create the lookup table.
+This is typically a large number, e.g., 1e6 or 1e7.
+"""
+
+# LtotalRange = NewType("LtotalRange", tuple[sc.Variable, sc.Variable])
+# """
+# Range (min, max) of the total length of the flight path from the source to the detector.
+# This is used to create the lookup table to compute the neutron time-of-flight.
+# Note that the resulting table will extend slightly beyond this range, as the supplied
+# range is not necessarily a multiple of the distance resolution.
+
+# Note also that the range of total flight paths is supplied manually to the workflow
+# instead of being read from the input data, as it allows us to compute the expensive part
+# of the workflow in advance (the lookup table) and does not need to be repeated for each
+# run, or for new data coming in in the case of live data collection.
+# """
+
+# DistanceResolution = NewType("DistanceResolution", sc.Variable)
+# """
+# Step size of the distance axis in the lookup table.
+# Should be a single scalar value with a unit of length.
+# This is typically of the order of 1-10 cm.
+# """
+
+# TimeResolution = NewType("TimeResolution", sc.Variable)
+# """
+# Step size of the event_time_offset axis in the lookup table.
+# This is basically the 'time-of-flight' resolution of the detector.
+# Should be a single scalar value with a unit of time.
+# This is typically of the order of 0.1-0.5 ms.
+
+# Since the event_time_offset range needs to span exactly one pulse period, the final
+# resolution in the lookup table will be at least the supplied value here, but may be
+# smaller if the pulse period is not an integer multiple of the time resolution.
+# """
+
+# PulsePeriod = NewType("PulsePeriod", sc.Variable)
+# """
+# Period of the source pulses, i.e., time between consecutive pulse starts.
+# """
+
+# PulseStride = NewType("PulseStride", int)
+# """
+# Stride of used pulses. Usually 1, but may be a small integer when pulse-skipping.
+# """
+
+# SourcePosition = NewType("SourcePosition", sc.Variable)
+# """
+# Position of the neutron source in the coordinate system of the choppers.
+# """
+
+SimulationSeed = NewType("SimulationSeed", int | None)
+"""Seed for the random number generator used in the simulation.
+"""
+
+SimulationFacility = NewType("SimulationFacility", str)
+"""
+Facility where the experiment is performed, e.g., 'ess'.
+"""
+
+
+def _compute_mean_wavelength(
+    simulation: BeamlineComponentReading,
+    distance: sc.Variable,
+    time_bins: sc.Variable,
+    time_unit: str,
+    frame_period: sc.Variable,
+    time_bins_half_width: sc.Variable,
+) -> sc.DataArray:
+    """
+    Compute the mean time-of-flight inside event_time_offset bins for a given range of
+    distances.
+
+    Parameters
+    ----------
+    simulation:
+        Results of a time-of-flight simulation used to create a lookup table.
+    distance:
+        Distance where table is computed.
+    time_bins:
+        Bin edges for the event_time_offset axis in the lookup table.
+    time_unit:
+        Unit of the event_time_offset axis.
+    frame_period:
+        Period of the source pulses, i.e., time between consecutive pulse starts.
+    time_bins_half_width:
+        Half width of the time bins in the event_time_offset axis.
+    """
+    travel_length = distance - simulation.distance.to(unit=distance.unit)
+    # Compute arrival and flight times for all neutrons
+    toas = simulation.time_of_arrival + (travel_length / simulation.speed).to(
+        unit=time_unit, copy=False
+    )
+
+    data = sc.DataArray(
+        data=simulation.weight,
+        coords={"toa": toas, "wavelength": simulation.wavelength},
+    )
+
+    # Add the event_time_offset coordinate, wrapped to the frame_period
+    data.coords['event_time_offset'] = data.coords['toa'] % frame_period
+
+    # Because we staggered the mesh by half a bin width, we want the values above
+    # the last bin edge to wrap around to the first bin.
+    # Technically, those values should end up between -0.5*bin_width and 0, but
+    # a simple modulo also works here because even if they end up between 0 and
+    # 0.5*bin_width, we are (below) computing the mean between -0.5*bin_width and
+    # 0.5*bin_width and it yields the same result.
+    # data.coords['event_time_offset'] %= pulse_period - time_bins_half_width
+    data.coords['event_time_offset'] %= frame_period - time_bins_half_width
+
+    binned = data.bin(event_time_offset=time_bins)
+    binned_sum = binned.bins.sum()
+    # Weighted mean of wavelength inside each bin
+    mean_wavelength = (
+        binned.bins.data * binned.bins.coords["wavelength"]
+    ).bins.sum() / binned_sum
+    # Compute the variance of the wavelengths to track regions with large uncertainty
+    variance = (
+        binned.bins.data * (binned.bins.coords["wavelength"] - mean_wavelength) ** 2
+    ).bins.sum() / binned_sum
+
+    mean_wavelength.variances = variance.values
+    return mean_wavelength
+
+
+def make_wavelength_lookup_table(
+    simulation: SimulationResults,
+    ltotal_range: LtotalRange,
+    distance_resolution: DistanceResolution,
+    time_resolution: TimeResolution,
+    pulse_period: PulsePeriod,
+    pulse_stride: PulseStride,
+) -> LookupTable:
+    """
+    Compute a lookup table for wavelength as a function of distance and
+    time-of-arrival.
+
+    Parameters
+    ----------
+    simulation:
+        Results of a time-of-flight simulation used to create a lookup table.
+        The results should be a flat table with columns for time-of-arrival,
+        wavelength, and weight.
+    ltotal_range:
+        Range of total flight path lengths from the source to the detector.
+    distance_resolution:
+        Resolution of the distance axis in the lookup table.
+    time_resolution:
+        Resolution of the time-of-arrival axis in the lookup table. Must be an integer.
+    pulse_period:
+        Period of the source pulses, i.e., time between consecutive pulse starts.
+    pulse_stride:
+        Stride of used pulses. Usually 1, but may be a small integer when
+        pulse-skipping.
+
+    Notes
+    -----
+
+    Below are some details about the binning and wrapping around frame period in the
+    time dimension.
+
+    We have some simulated ``toa`` (events) from a Tof/McStas simulation.
+    Those are absolute ``toa``, unwrapped.
+    First we compute the usual ``event_time_offset = toa % frame_period``.
+
+    Now, we want to ensure periodic boundaries. If we make a bin centered around 0,
+    and a bin centered around 71ms: the first bin will use events between 0 and
+    ``0.5 * dt`` (where ``dt`` is the bin width).
+    The last bin will use events between ``frame_period - 0.5*dt`` and
+    ``frame_period + 0.5 * dt``. So when we compute the mean inside those two bins,
+    they will not yield the same results.
+    It is as if the first bin is missing the events it should have between
+    ``-0.5 * dt`` and 0 (because of the modulo we computed above).
+
+    To fix this, we do not make a last bin around 71ms (the bins stop at
+    ``frame_period - 0.5*dt``). Instead, we compute modulo a second time,
+    but this time using ``event_time_offset %= (frame_period - 0.5*dt)``.
+    (we cannot directly do ``event_time_offset = toa % (frame_period - 0.5*dt)`` in a
+    single step because it would introduce a gradual shift,
+    as the pulse number increases).
+
+    This second modulo effectively takes all the events that would have gone in the
+    last bin (between ``frame_period - 0.5*dt`` and ``frame_period``) and puts them in
+    the first bin. Instead of placing them between ``-0.5*dt`` and 0,
+    it places them between 0 and ``0.5*dt``, but this does not really matter,
+    because we then take the mean inside the first bin.
+    Whether the events are on the left or right side of zero does not matter.
+
+    Finally, we make a copy of the left edge, and append it to the right of the table,
+    thus ensuring that the values on the right edge are strictly the same as on the
+    left edge.
+    """
+    distance_unit = "m"
+    time_unit = "us"
+    res = distance_resolution.to(unit=distance_unit)
+    pulse_period = pulse_period.to(unit=time_unit)
+    frame_period = pulse_period * pulse_stride
+
+    min_dist = ltotal_range[0].to(unit=distance_unit)
+    max_dist = ltotal_range[1].to(unit=distance_unit)
+
+    # We need to bin the data below, to compute the weighted mean of the wavelength.
+    # This results in data with bin edges.
+    # However, the 2d interpolator expects bin centers.
+    # We want to give the 2d interpolator a table that covers the requested range,
+    # hence we need to extend the range by at least half a resolution in each direction.
+    # Then, we make the choice that the resolution in distance is the quantity that
+    # should be preserved. Because the difference between min and max distance is
+    # not necessarily an integer multiple of the resolution, we need to add a pad to
+    # ensure that the last bin is not cut off. We want the upper edge to be higher than
+    # the maximum distance, hence we pad with an additional 1.5 x resolution.
+    pad = 2.0 * res
+    distances = sc.arange('distance', min_dist - pad, max_dist + pad, res)
+
+    # Create some time bins for event_time_offset.
+    # We want our final table to strictly cover the range [0, frame_period].
+    # However, binning the data associates mean values inside the bins to the bin
+    # centers. Instead, we stagger the mesh by half a bin width so we are computing
+    # values for the final mesh edges (the bilinear interpolation needs values on the
+    # edges/corners).
+    nbins = int(frame_period / time_resolution.to(unit=time_unit)) + 1
+    time_bins = sc.linspace(
+        'event_time_offset', 0.0, frame_period.value, nbins + 1, unit=pulse_period.unit
+    )
+    time_bins_half_width = 0.5 * (time_bins[1] - time_bins[0])
+    time_bins -= time_bins_half_width
+
+    # Sort simulation readings by reverse distance
+    sorted_simulation_results = sorted(
+        simulation.readings.values(), key=lambda x: x.distance.value, reverse=True
+    )
+
+    pieces = []
+    # To avoid large RAM usage, and having to split the distances into chunks
+    # according to which component reading to use, we simply loop over distances one
+    # by one here.
+    for dist in distances:
+        # Find the correct simulation reading
+        simulation_reading = None
+        for reading in sorted_simulation_results:
+            if dist.value >= reading.distance.to(unit=dist.unit).value:
+                simulation_reading = reading
+                break
+        if simulation_reading is None:
+            closest = sorted_simulation_results[-1]
+            raise ValueError(
+                "Building the lookup table failed: the requested position "
+                f"{dist.value} {dist.unit} is before the component with the lowest "
+                "distance in the simulation. The first component in the beamline "
+                f"has distance {closest.distance.value} {closest.distance.unit}."
+            )
+
+        pieces.append(
+            _compute_mean_wavelength(
+                simulation=simulation_reading,
+                distance=dist,
+                time_bins=time_bins,
+                time_unit=time_unit,
+                frame_period=frame_period,
+                time_bins_half_width=time_bins_half_width,
+            )
+        )
+
+    table = sc.concat(pieces, 'distance')
+    table.coords["event_time_offset"] = sc.midpoints(table.coords["event_time_offset"])
+
+    # Copy the left edge to the right to create periodic boundary conditions
+    table = sc.DataArray(
+        data=sc.concat(
+            [table.data, table.data['event_time_offset', 0]], dim='event_time_offset'
+        ),
+        coords={
+            "distance": distances,
+            "event_time_offset": sc.concat(
+                [table.coords["event_time_offset"], frame_period],
+                dim='event_time_offset',
+            ),
+        },
+    )
+
+    return LookupTable(
+        array=table,
+        pulse_period=pulse_period,
+        pulse_stride=pulse_stride,
+        distance_resolution=table.coords["distance"][1] - table.coords["distance"][0],
+        time_resolution=table.coords["event_time_offset"][1]
+        - table.coords["event_time_offset"][0],
+        choppers=sc.DataGroup(
+            {k: sc.DataGroup(ch.as_dict()) for k, ch in simulation.choppers.items()}
+        )
+        if simulation.choppers is not None
+        else None,
+    )
+
+
+def _to_component_reading(component):
+    events = component.data.squeeze().flatten(to='event')
+    sel = sc.full(value=True, sizes=events.sizes)
+    for key in {'blocked_by_others', 'blocked_by_me'} & set(events.masks.keys()):
+        sel &= ~events.masks[key]
+    events = events[sel]
+    # If the component is a source, use 'birth_time' as 'toa'
+    toa = (
+        events.coords["toa"] if "toa" in events.coords else events.coords["birth_time"]
+    )
+    return BeamlineComponentReading(
+        time_of_arrival=toa,
+        wavelength=events.coords["wavelength"],
+        weight=events.data,
+        distance=component.distance,
+    )
+
+
+def simulate_chopper_cascade_using_tof(
+    choppers: DiskChoppers[AnyRun],
+    source_position: SourcePosition,
+    neutrons: NumberOfSimulatedNeutrons,
+    pulse_stride: PulseStride,
+    seed: SimulationSeed,
+    facility: SimulationFacility,
+) -> SimulationResults:
+    """
+    Simulate a pulse of neutrons propagating through a chopper cascade using the
+    ``tof`` package (https://scipp.github.io/tof).
+
+    Parameters
+    ----------
+    choppers:
+        A dict of DiskChopper objects representing the choppers in the beamline. See
+        https://scipp.github.io/scippneutron/user-guide/chopper/processing-nexus-choppers.html
+        for more information.
+    source_position:
+        A scalar variable with ``dtype=vector3`` that defines the source position.
+        Must be in the same coordinate system as the choppers' axle positions.
+    neutrons:
+        Number of neutrons to simulate.
+    pulse_stride:
+        The pulse strinde; we need to simulate at least enough pulses to cover the
+        requested stride.
+    seed:
+        Seed for the random number generator used in the simulation.
+    facility:
+        Facility where the experiment is performed.
+    """
+    import tof
+
+    tof_choppers = []
+    for name, ch in choppers.items():
+        chop = tof.Chopper.from_diskchopper(ch, name=name)
+        chop.distance = sc.norm(
+            ch.axle_position - source_position.to(unit=ch.axle_position.unit)
+        )
+        tof_choppers.append(chop)
+
+    source = tof.Source(
+        facility=facility, neutrons=neutrons, pulses=pulse_stride, seed=seed
+    )
+    sim_readings = {"source": _to_component_reading(source)}
+    if not tof_choppers:
+        return SimulationResults(readings=sim_readings, choppers=None)
+    model = tof.Model(source=source, choppers=tof_choppers)
+    results = model.run()
+    for name, ch in results.choppers.items():
+        sim_readings[name] = _to_component_reading(ch)
+    return SimulationResults(readings=sim_readings, choppers=choppers)
+
+
+def LookupTableFromTofWorkflow():
+    """
+    Create a workflow for computing a wavelength lookup table from a
+    simulation of neutrons propagating through a chopper cascade.
+    """
+    wf = sl.Pipeline(
+        (make_wavelength_lookup_table, simulate_chopper_cascade_using_tof),
+        params={
+            PulsePeriod: 1.0 / sc.scalar(14.0, unit="Hz"),
+            PulseStride: 1,
+            DistanceResolution: sc.scalar(0.1, unit="m"),
+            TimeResolution: sc.scalar(250.0, unit='us'),
+            NumberOfSimulatedNeutrons: 1_000_000,
+            SimulationSeed: None,
+            SimulationFacility: 'ess',
+        },
+    )
+    return wf
diff --git a/packages/essreduce/src/ess/reduce/unwrap/types.py b/packages/essreduce/src/ess/reduce/unwrap/types.py
index 86dd086c9..00312679c 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/types.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/types.py
@@ -14,6 +14,63 @@
 """Filename of the wavelength lookup table."""
 
 
+LtotalRange = NewType("LtotalRange", tuple[sc.Variable, sc.Variable])
+"""
+Range (min, max) of the total length of the flight path from the source to the detector.
+This is used to create the lookup table to compute the neutron time-of-flight.
+Note that the resulting table will extend slightly beyond this range, as the supplied
+range is not necessarily a multiple of the distance resolution.
+
+Note also that the range of total flight paths is supplied manually to the workflow
+instead of being read from the input data, as it allows us to compute the expensive part
+of the workflow in advance (the lookup table) and does not need to be repeated for each
+run, or for new data coming in in the case of live data collection.
+"""
+
+DistanceResolution = NewType("DistanceResolution", sc.Variable)
+"""
+Step size of the distance axis in the lookup table.
+Should be a single scalar value with a unit of length.
+This is typically of the order of 1-10 cm.
+"""
+
+
+@dataclass
+class SourcePulse:
+    time: tuple[sc.Variable, sc.Variable]
+    """Time range (start, end) of the source pulse."""
+    wavelength: tuple[sc.Variable, sc.Variable]
+    """Wavelength range (min, max) of the neutrons in the source pulse."""
+
+
+TimeResolution = NewType("TimeResolution", sc.Variable)
+"""
+Step size of the event_time_offset axis in the lookup table.
+This is basically the 'time-of-flight' resolution of the detector.
+Should be a single scalar value with a unit of time.
+This is typically of the order of 0.1-0.5 ms.
+
+Since the event_time_offset range needs to span exactly one pulse period, the final
+resolution in the lookup table will be at least the supplied value here, but may be
+smaller if the pulse period is not an integer multiple of the time resolution.
+"""
+
+PulsePeriod = NewType("PulsePeriod", sc.Variable)
+"""
+Period of the source pulses, i.e., time between consecutive pulse starts.
+"""
+
+PulseStride = NewType("PulseStride", int)
+"""
+Stride of used pulses. Usually 1, but may be a small integer when pulse-skipping.
+"""
+
+SourcePosition = NewType("SourcePosition", sc.Variable)
+"""
+Position of the neutron source in the coordinate system of the choppers.
+"""
+
+
 @dataclass
 class LookupTable:
     """

From b4d38e631acc1e265cc4fb4e62a3fcb29fb713ee Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Thu, 7 May 2026 15:45:28 +0200
Subject: [PATCH 02/23] fix bug in frame selection and extend to use multiple
 pulses

---
 .../essreduce/src/ess/reduce/unwrap/lut.py    | 107 ++++++++++++------
 1 file changed, 73 insertions(+), 34 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index aefe6f90a..f44d643b7 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -4,6 +4,7 @@
 Utilities for computing wavelength lookup tables.
 """
 
+import time
 from dataclasses import dataclass
 from typing import NewType
 
@@ -25,7 +26,10 @@
 )
 
 
-def _polygon_edges(polygons):
+def _polygon_edges(polygons: list[np.ndarray]) -> np.ndarray:
+    """
+    Convert a list of polygons (N_i, 2) arrays to a single array of edges (E, 2, 2).
+    """
     # polygons: list of (N_i, 2) arrays
     edges = []
     for poly in polygons:
@@ -35,7 +39,25 @@ def _polygon_edges(polygons):
     return np.concatenate(edges, axis=0)  # (E, 2, 2)
 
 
-def _polygon_intersections(polygons, xs):
+def _polygon_intersections(polygons: list[np.ndarray], xs: np.ndarray) -> np.ndarray:
+    """
+    Find the intersections of a list of polygons with vertical lines at specified x
+    coordinates.
+    We then take the mean of the minimum and maximum intersection points as an estimate
+    of the mean wavelength in each bin. This handles the case where there are multiple
+    subframes overlapping in a single time bin.
+
+    Parameters
+    ----------
+    polygons:
+        List of polygons, each represented as an (N_i, 2) array of vertices.
+    xs:
+        Array of x coordinates where intersections should be computed.
+
+    Returns
+    -------
+    Array of intersection y coordinates, one for each x in `xs`.
+    """
     edges = _polygon_edges(polygons)
 
     x1 = edges[:, 0, 0][:, None]  # (E, 1)
@@ -67,25 +89,40 @@ def _polygon_intersections(polygons, xs):
 
 def _compute_mean_wavelength(
     subframes: list[chopper_cascade.Subframe],
-    # distance: sc.Variable,
     time_edges: sc.Variable,
     time_unit: str,
     frame_period: sc.Variable,
-    # time_bins_half_width: sc.Variable,
 ) -> sc.DataArray:
     """
-    Compute the mean time-of-flight inside event_time_offset bins for a given range of
+    Compute the mean wavelength inside event_time_offset bins for a given range of
     distances.
 
+    This is done by finding the intersection of the edges of the subframe polygons
+    (generated by the ``chopper_cascade`` module) with vertical lines at the specified
+    time edges.
+    We then take the mean of the minimum and maximum intersection points as an estimate
+    of the mean wavelength in each bin. This handles the case where there are multiple
+    subframes overlapping in a single time bin.
+
     Parameters
     ----------
+    subframes:
+        List of subframes to consider. These should already be propagated to the
+        correct distance.
+    time_edges:
+        Edges of the time bins for which to compute the mean wavelength. Should be a
+        1D variable with a unit of time.
+    time_unit:
+        Unit to use for all time quantities.
+    frame_period:
+        Period of the source pulses, used to handle the periodicity of the subframes.
     """
-    # at_sample = frames.propagate_to(sc.linspace('distance', 55., 75., N, unit='m'))
-    # subf = at_sample.frames[-1].subframes
-
-    # fig = at_sample.draw()
-    # p = d
 
+    # To handle the periodicity of the subframes, we need to consider not only the
+    # original subframes, but also copies of the subframes shifted by the frame period.
+    # This is because neutrons that arrive after the frame period will wrap around and
+    # appear in the next pulse, which is equivalent to the original pulse but shifted
+    # by the frame period.
     polygons = [
         np.stack([f.time.to(unit=time_unit).values, f.wavelength.values], axis=1)
         for f in subframes
@@ -109,14 +146,29 @@ def _compute_frame_sequence(
     disk_choppers: DiskChoppers[AnyRun],
     source_position: SourcePosition,
     source_pulse: SourcePulse,
+    pulse_stride: PulseStride,
 ) -> chopper_cascade.FrameSequence:
-    pulse_frequency = 1.0 / pulse_period.to(unit='s')
+
+    # The time_offset_open and time_offset_close below require the pulse_frequency to
+    # be an integer multiple of the pulse frequency or vice versa. A simple trick is
+    # to make sure that the requested pulse frequency is divided by an even number.
+    div = pulse_stride + 1 if pulse_stride % 2 == 1 else pulse_stride
+    # The `pulse_frequency` parameter in time_offset_open and time_offset_close below
+    # decides how many rotations the chopper will perform when computing the open and
+    # close times. Because we want to cover a number of pulses equal to `pulse_stride`,
+    # we need to set the pulse frequency to be `pulse_stride` times smaller than the
+    # actual pulse frequency.
+    frequency_for_chopper_rotation = (1.0 / pulse_period.to(unit='s')) / div
 
     chops = {
         key: chopper_cascade.Chopper(
             distance=(ch.axle_position - source_position).fields.z,
-            time_open=ch.time_offset_open(pulse_frequency=pulse_frequency),
-            time_close=ch.time_offset_close(pulse_frequency=pulse_frequency),
+            time_open=ch.time_offset_open(
+                pulse_frequency=frequency_for_chopper_rotation
+            ),
+            time_close=ch.time_offset_close(
+                pulse_frequency=frequency_for_chopper_rotation
+            ),
         )
         for key, ch in disk_choppers.items()
     }
@@ -126,6 +178,8 @@ def _compute_frame_sequence(
         time_max=source_pulse.time[1],
         wavelength_min=source_pulse.wavelength[0],
         wavelength_max=source_pulse.wavelength[1],
+        pulse_period=pulse_period,
+        npulses=pulse_stride,
     )
     frames = frames.chop(chops.values())
     return frames
@@ -193,12 +247,11 @@ def make_wavelength_lookup_table(
         disk_choppers=choppers,
         source_position=source_position,
         source_pulse=source_pulse,
+        pulse_stride=pulse_stride,
     )
 
-    # # Sort simulation readings by reverse distance
-    # sorted_simulation_results = sorted(
-    #     simulation.readings.values(), key=lambda x: x.distance.value, reverse=True
-    # )
+    # Sort frames by reverse distance
+    sorted_frames = sorted(frames, key=lambda x: x.distance.value, reverse=True)
 
     pieces = []
     # To avoid large RAM usage, and having to split the distances into chunks
@@ -207,7 +260,7 @@ def make_wavelength_lookup_table(
     for dist in distances:
         # Find the correct simulation reading
         selected_frame = None
-        for frame in frames:
+        for frame in sorted_frames:
             if dist.value >= frame.distance.to(unit=dist.unit).value:
                 selected_frame = frame
                 break
@@ -216,29 +269,20 @@ def make_wavelength_lookup_table(
                 "Building the lookup table failed: the requested position "
                 f"{dist:c} is before the component with the lowest "
                 "distance in the simulation. The first component in the beamline "
-                f"has distance {frames[0].distance:c}."
+                f"has distance {sorted_frames[0].distance:c}."
             )
 
-        # subframes = frames.propagate_to(dist).frames[-1].subframes
         subframes = selected_frame.propagate_to(dist).subframes
 
         pieces.append(
             _compute_mean_wavelength(
                 subframes=subframes,
-                # distance=dist,
                 time_edges=time_edges,
                 time_unit=time_unit,
                 frame_period=frame_period,
-                # time_bins_half_width=time_bins_half_width,
             )
         )
 
-    # frames.propagate_to(dist).draw()
-
-    # table = sc.concat(pieces, 'distance')
-    # table.coords["event_time_offset"] = sc.midpoints(table.coords["event_time_offset"])
-
-    # Copy the left edge to the right to create periodic boundary conditions
     table = sc.DataArray(
         data=sc.concat(pieces, 'distance'),
         coords={"distance": distances, "event_time_offset": time_edges},
@@ -251,11 +295,6 @@ def make_wavelength_lookup_table(
         distance_resolution=table.coords["distance"][1] - table.coords["distance"][0],
         time_resolution=table.coords["event_time_offset"][1]
         - table.coords["event_time_offset"][0],
-        # choppers=sc.DataGroup(
-        #     {k: sc.DataGroup(ch.as_dict()) for k, ch in simulation.choppers.items()}
-        # )
-        # if simulation.choppers is not None
-        # else None,
     )
 
 
@@ -275,7 +314,7 @@ def LookupTableWorkflow():
                 time=(sc.scalar(0.0, unit='ms'), sc.scalar(4.0, unit='ms')),
                 wavelength=(
                     sc.scalar(0.0, unit='angstrom'),
-                    sc.scalar(10.0, unit='angstrom'),
+                    sc.scalar(15.0, unit='angstrom'),
                 ),
             ),
         },

From f839e81b3768d08bce9d7a033d484afaf4dcb93b Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Thu, 7 May 2026 16:02:37 +0200
Subject: [PATCH 03/23] parametrize lut tests

---
 .../essreduce/src/ess/reduce/unwrap/lut.py    | 12 ++-
 packages/essreduce/tests/unwrap/lut_test.py   | 91 +++++++++++++------
 2 files changed, 71 insertions(+), 32 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index f44d643b7..45658fe21 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -4,9 +4,7 @@
 Utilities for computing wavelength lookup tables.
 """
 
-import time
-from dataclasses import dataclass
-from typing import NewType
+import warnings
 
 import numpy as np
 import sciline as sl
@@ -81,8 +79,12 @@ def _polygon_intersections(polygons: list[np.ndarray], xs: np.ndarray) -> np.nda
     y = np.where(mask, y, np.nan)
 
     # now reduce along edges axis
-    y_min = np.nanmin(y, axis=0)
-    y_max = np.nanmax(y, axis=0)
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore", category=RuntimeWarning, message="All-NaN slice encountered"
+        )
+        y_min = np.nanmin(y, axis=0)
+        y_max = np.nanmax(y, axis=0)
 
     return 0.5 * (y_min + y_max)
 
diff --git a/packages/essreduce/tests/unwrap/lut_test.py b/packages/essreduce/tests/unwrap/lut_test.py
index 495e57dd2..bc3cc838e 100644
--- a/packages/essreduce/tests/unwrap/lut_test.py
+++ b/packages/essreduce/tests/unwrap/lut_test.py
@@ -6,19 +6,26 @@
 
 from ess.reduce import unwrap
 from ess.reduce.nexus.types import AnyRun
-from ess.reduce.unwrap import LookupTableWorkflow
+from ess.reduce.unwrap import LookupTableFromTofWorkflow, LookupTableWorkflow
 
 sl = pytest.importorskip("sciline")
 
 
-def test_lut_workflow_computes_table():
-    wf = LookupTableWorkflow()
+@pytest.mark.parametrize("engine", ["analytical", "tof"])
+def test_lut_workflow_computes_table(engine):
+    wf = (
+        LookupTableWorkflow()
+        if engine == "analytical"
+        else LookupTableFromTofWorkflow()
+    )
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
-    wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    wf[unwrap.SimulationSeed] = 60
     wf[unwrap.PulseStride] = 1
 
+    if engine == "tof":
+        wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
+        wf[unwrap.SimulationSeed] = 60
+
     lmin, lmax = sc.scalar(25.0, unit='m'), sc.scalar(35.0, unit='m')
     dres = sc.scalar(0.1, unit='m')
     tres = sc.scalar(333.0, unit='us')
@@ -40,12 +47,18 @@ def test_lut_workflow_computes_table():
     assert sc.isclose(table.time_resolution, tres, rtol=sc.scalar(0.01))
 
 
-def test_lut_workflow_pulse_skipping():
-    wf = LookupTableWorkflow()
+@pytest.mark.parametrize("engine", ["analytical", "tof"])
+def test_lut_workflow_pulse_skipping(engine):
+    wf = (
+        LookupTableWorkflow()
+        if engine == "analytical"
+        else LookupTableFromTofWorkflow()
+    )
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
-    wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    wf[unwrap.SimulationSeed] = 62
+    if engine == "tof":
+        wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
+        wf[unwrap.SimulationSeed] = 62
     wf[unwrap.PulseStride] = 2
 
     lmin, lmax = sc.scalar(55.0, unit='m'), sc.scalar(65.0, unit='m')
@@ -63,12 +76,18 @@ def test_lut_workflow_pulse_skipping():
     ).to(unit=table.array.coords['event_time_offset'].unit)
 
 
-def test_lut_workflow_non_exact_distance_range():
-    wf = LookupTableWorkflow()
+@pytest.mark.parametrize("engine", ["analytical", "tof"])
+def test_lut_workflow_non_exact_distance_range(engine):
+    wf = (
+        LookupTableWorkflow()
+        if engine == "analytical"
+        else LookupTableFromTofWorkflow()
+    )
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
-    wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    wf[unwrap.SimulationSeed] = 63
+    if engine == "tof":
+        wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
+        wf[unwrap.SimulationSeed] = 63
     wf[unwrap.PulseStride] = 1
 
     lmin, lmax = sc.scalar(25.0, unit='m'), sc.scalar(35.0, unit='m')
@@ -145,12 +164,18 @@ def _make_choppers():
     }
 
 
-def test_lut_workflow_computes_table_with_choppers():
-    wf = LookupTableWorkflow()
+@pytest.mark.parametrize("engine", ["analytical", "tof"])
+def test_lut_workflow_computes_table_with_choppers(engine):
+    wf = (
+        LookupTableWorkflow()
+        if engine == "analytical"
+        else LookupTableFromTofWorkflow()
+    )
     wf[unwrap.DiskChoppers[AnyRun]] = _make_choppers()
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
-    wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    wf[unwrap.SimulationSeed] = 64
+    if engine == "tof":
+        wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
+        wf[unwrap.SimulationSeed] = 64
     wf[unwrap.PulseStride] = 1
 
     wf[unwrap.LtotalRange] = (
@@ -179,12 +204,18 @@ def test_lut_workflow_computes_table_with_choppers():
     assert eto.max() < sc.scalar(6.9e4, unit="us").to(unit=eto.unit)
 
 
-def test_lut_workflow_computes_table_with_choppers_full_beamline_range():
-    wf = LookupTableWorkflow()
+@pytest.mark.parametrize("engine", ["analytical", "tof"])
+def test_lut_workflow_computes_table_with_choppers_full_beamline_range(engine):
+    wf = (
+        LookupTableWorkflow()
+        if engine == "analytical"
+        else LookupTableFromTofWorkflow()
+    )
     wf[unwrap.DiskChoppers[AnyRun]] = _make_choppers()
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
-    wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    wf[unwrap.SimulationSeed] = 64
+    if engine == "tof":
+        wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
+        wf[unwrap.SimulationSeed] = 64
     wf[unwrap.PulseStride] = 1
 
     wf[unwrap.LtotalRange] = (
@@ -199,9 +230,9 @@ def test_lut_workflow_computes_table_with_choppers_full_beamline_range():
     # Close to source: early times and large spread
     da = table.array['distance', 2]
     eto = da.coords['event_time_offset'][sc.isfinite(da.data)]
-    assert eto.min() > sc.scalar(0.0, unit="us").to(unit=eto.unit)
+    assert eto.min() >= sc.scalar(0.0, unit="us").to(unit=eto.unit)
     assert eto.min() < sc.scalar(1.0e3, unit="us").to(unit=eto.unit)
-    assert eto.max() > sc.scalar(2.5e4, unit="us").to(unit=eto.unit)
+    assert eto.max() > sc.scalar(2.0e4, unit="us").to(unit=eto.unit)
     assert eto.max() < sc.scalar(3.0e4, unit="us").to(unit=eto.unit)
 
     # Just after WFM choppers, very small range
@@ -229,12 +260,18 @@ def test_lut_workflow_computes_table_with_choppers_full_beamline_range():
     assert eto.max() < sc.scalar(6.9e4, unit="us").to(unit=eto.unit)
 
 
-def test_lut_workflow_raises_for_distance_before_source():
-    wf = LookupTableWorkflow()
+@pytest.mark.parametrize("engine", ["analytical", "tof"])
+def test_lut_workflow_raises_for_distance_before_source(engine):
+    wf = (
+        LookupTableWorkflow()
+        if engine == "analytical"
+        else LookupTableFromTofWorkflow()
+    )
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 10], unit='m')
-    wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    wf[unwrap.SimulationSeed] = 65
+    if engine == "tof":
+        wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
+        wf[unwrap.SimulationSeed] = 65
     wf[unwrap.PulseStride] = 1
 
     # Setting the starting point at zero will make a table that would cover a range

From fdc2dd4e4a55c5ef3ab304ea17e26a51c92864d4 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Thu, 7 May 2026 16:04:25 +0200
Subject: [PATCH 04/23] lint

---
 .../src/ess/reduce/unwrap/lut_from_tof.py     | 46 -------------------
 1 file changed, 46 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py b/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py
index 52cf483ab..0b709b647 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py
@@ -87,52 +87,6 @@ class SimulationResults:
 This is typically a large number, e.g., 1e6 or 1e7.
 """
 
-# LtotalRange = NewType("LtotalRange", tuple[sc.Variable, sc.Variable])
-# """
-# Range (min, max) of the total length of the flight path from the source to the detector.
-# This is used to create the lookup table to compute the neutron time-of-flight.
-# Note that the resulting table will extend slightly beyond this range, as the supplied
-# range is not necessarily a multiple of the distance resolution.
-
-# Note also that the range of total flight paths is supplied manually to the workflow
-# instead of being read from the input data, as it allows us to compute the expensive part
-# of the workflow in advance (the lookup table) and does not need to be repeated for each
-# run, or for new data coming in in the case of live data collection.
-# """
-
-# DistanceResolution = NewType("DistanceResolution", sc.Variable)
-# """
-# Step size of the distance axis in the lookup table.
-# Should be a single scalar value with a unit of length.
-# This is typically of the order of 1-10 cm.
-# """
-
-# TimeResolution = NewType("TimeResolution", sc.Variable)
-# """
-# Step size of the event_time_offset axis in the lookup table.
-# This is basically the 'time-of-flight' resolution of the detector.
-# Should be a single scalar value with a unit of time.
-# This is typically of the order of 0.1-0.5 ms.
-
-# Since the event_time_offset range needs to span exactly one pulse period, the final
-# resolution in the lookup table will be at least the supplied value here, but may be
-# smaller if the pulse period is not an integer multiple of the time resolution.
-# """
-
-# PulsePeriod = NewType("PulsePeriod", sc.Variable)
-# """
-# Period of the source pulses, i.e., time between consecutive pulse starts.
-# """
-
-# PulseStride = NewType("PulseStride", int)
-# """
-# Stride of used pulses. Usually 1, but may be a small integer when pulse-skipping.
-# """
-
-# SourcePosition = NewType("SourcePosition", sc.Variable)
-# """
-# Position of the neutron source in the coordinate system of the choppers.
-# """
 
 SimulationSeed = NewType("SimulationSeed", int | None)
 """Seed for the random number generator used in the simulation.

From 20f67b0b0f992aeeeb814e70a127ca7016afd83a Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Thu, 7 May 2026 17:56:27 +0200
Subject: [PATCH 05/23] start fixing unwrap tests

---
 .../src/ess/reduce/unwrap/__init__.py         |  8 ++-
 .../essreduce/src/ess/reduce/unwrap/lut.py    | 10 +++-
 ...lut_from_tof.py => lut_from_simulation.py} | 23 ++++++--
 .../essreduce/tests/unwrap/unwrap_test.py     | 57 ++++++++++++-------
 4 files changed, 67 insertions(+), 31 deletions(-)
 rename packages/essreduce/src/ess/reduce/unwrap/{lut_from_tof.py => lut_from_simulation.py} (96%)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/__init__.py b/packages/essreduce/src/ess/reduce/unwrap/__init__.py
index 02b5e9fc3..3401a3d52 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/__init__.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/__init__.py
@@ -17,9 +17,10 @@
     SourcePulse,
     TimeResolution,
 )
-from .lut_from_tof import (
+from .lut_from_simulation import (
     BeamlineComponentReading,
-    LookupTableFromTofWorkflow,
+    LookupTableFromSimulation,
+    LookupTableFromTof,
     NumberOfSimulatedNeutrons,
     SimulationResults,
     SimulationSeed,
@@ -48,7 +49,8 @@
     "GenericUnwrapWorkflow",
     "LookupTable",
     "LookupTableFilename",
-    "LookupTableFromTofWorkflow",
+    "LookupTableFromSimulation",
+    "LookupTableFromTof",
     "LookupTableRelativeErrorThreshold",
     "LookupTableWorkflow",
     "LtotalRange",
diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index 45658fe21..58939870a 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -86,7 +86,8 @@ def _polygon_intersections(polygons: list[np.ndarray], xs: np.ndarray) -> np.nda
         y_min = np.nanmin(y, axis=0)
         y_max = np.nanmax(y, axis=0)
 
-    return 0.5 * (y_min + y_max)
+    # Value and spread estimate
+    return 0.5 * (y_min + y_max), 0.5 * (y_max - y_min)
 
 
 def _compute_mean_wavelength(
@@ -136,10 +137,13 @@ def _compute_mean_wavelength(
         for f in subframes
     ]
 
-    wavs = _polygon_intersections(polygons, time_edges.values)
+    wavs, stddevs = _polygon_intersections(polygons, time_edges.values)
 
     return sc.array(
-        dims=time_edges.dims, values=wavs, unit=subframes[0].wavelength.unit
+        dims=time_edges.dims,
+        values=wavs,
+        variances=stddevs**2,
+        unit=subframes[0].wavelength.unit,
     )
 
 
diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py b/packages/essreduce/src/ess/reduce/unwrap/lut_from_simulation.py
similarity index 96%
rename from packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py
rename to packages/essreduce/src/ess/reduce/unwrap/lut_from_simulation.py
index 0b709b647..6cd4adba5 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut_from_tof.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut_from_simulation.py
@@ -163,7 +163,7 @@ def _compute_mean_wavelength(
     return mean_wavelength
 
 
-def make_wavelength_lookup_table(
+def wavelength_lookup_table_from_simulation(
     simulation: SimulationResults,
     ltotal_range: LtotalRange,
     distance_resolution: DistanceResolution,
@@ -405,21 +405,32 @@ def simulate_chopper_cascade_using_tof(
     return SimulationResults(readings=sim_readings, choppers=choppers)
 
 
-def LookupTableFromTofWorkflow():
+def LookupTableFromSimulation():
     """
     Create a workflow for computing a wavelength lookup table from a
     simulation of neutrons propagating through a chopper cascade.
     """
     wf = sl.Pipeline(
-        (make_wavelength_lookup_table, simulate_chopper_cascade_using_tof),
+        (wavelength_lookup_table_from_simulation,),
         params={
             PulsePeriod: 1.0 / sc.scalar(14.0, unit="Hz"),
             PulseStride: 1,
             DistanceResolution: sc.scalar(0.1, unit="m"),
             TimeResolution: sc.scalar(250.0, unit='us'),
-            NumberOfSimulatedNeutrons: 1_000_000,
-            SimulationSeed: None,
-            SimulationFacility: 'ess',
         },
     )
     return wf
+
+
+def LookupTableFromTof():
+    """
+    Create a workflow for computing a wavelength lookup table using the ``tof`` package
+    to propagate neutrons through the chopper cascade.
+    """
+    wf = LookupTableFromSimulation()
+    wf.insert(simulate_chopper_cascade_using_tof)
+    wf[NumberOfSimulatedNeutrons] = 1_000_000
+    wf[SimulationSeed] = None
+    wf[SimulationFacility] = 'ess'
+
+    return wf
diff --git a/packages/essreduce/tests/unwrap/unwrap_test.py b/packages/essreduce/tests/unwrap/unwrap_test.py
index 708d3dc35..5439fa55c 100644
--- a/packages/essreduce/tests/unwrap/unwrap_test.py
+++ b/packages/essreduce/tests/unwrap/unwrap_test.py
@@ -15,37 +15,52 @@
     RawMonitor,
     SampleRun,
 )
-from ess.reduce.unwrap import GenericUnwrapWorkflow, LookupTableWorkflow, fakes
+from ess.reduce.unwrap import (
+    GenericUnwrapWorkflow,
+    LookupTableFromTof,
+    LookupTableWorkflow,
+    fakes,
+)
 
 sl = pytest.importorskip("sciline")
 
 
-def make_lut_workflow(choppers, neutrons, seed, pulse_stride):
-    lut_wf = LookupTableWorkflow()
+def make_lut_workflow(engine, choppers, pulse_stride, neutrons=None, seed=None):
+    lut_wf = LookupTableFromTof() if engine == "tof" else LookupTableWorkflow()
     lut_wf[unwrap.DiskChoppers[AnyRun]] = choppers
     lut_wf[unwrap.SourcePosition] = fakes.source_position()
     lut_wf[unwrap.NumberOfSimulatedNeutrons] = neutrons
-    lut_wf[unwrap.SimulationSeed] = seed
-    lut_wf[unwrap.PulseStride] = pulse_stride
-    lut_wf[unwrap.SimulationResults] = lut_wf.compute(unwrap.SimulationResults)
+    if engine == "tof":
+        lut_wf[unwrap.SimulationSeed] = seed
+        lut_wf[unwrap.PulseStride] = pulse_stride
+        lut_wf[unwrap.SimulationResults] = lut_wf.compute(unwrap.SimulationResults)
     return lut_wf
 
 
 @pytest.fixture(scope="module")
 def lut_workflow_psc_choppers():
-    return make_lut_workflow(
-        choppers=fakes.psc_choppers(), neutrons=500_000, seed=1234, pulse_stride=1
-    )
+    choppers = fakes.psc_choppers()
+    return {
+        'tof': make_lut_workflow(
+            engine='tof', choppers=choppers, neutrons=500_000, seed=1234, pulse_stride=1
+        ),
+        'analytical': make_lut_workflow(
+            engine='analytical', choppers=choppers, pulse_stride=1
+        ),
+    }
 
 
 @pytest.fixture(scope="module")
 def lut_workflow_pulse_skipping():
-    return make_lut_workflow(
-        choppers=fakes.pulse_skipping_choppers(),
-        neutrons=500_000,
-        seed=112,
-        pulse_stride=2,
-    )
+    choppers = fakes.pulse_skipping_choppers()
+    return {
+        'tof': make_lut_workflow(
+            engine='tof', choppers=choppers, neutrons=500_000, seed=112, pulse_stride=2
+        ),
+        'analytical': make_lut_workflow(
+            engine='analytical', choppers=choppers, pulse_stride=2
+        ),
+    }
 
 
 def _make_workflow_event_mode(
@@ -166,15 +181,16 @@ def _validate_result_histogram_mode(wavs, ref, percentile, diff_threshold, rtol)
     assert sc.isclose(ref.data.nansum(), wavs.data.nansum(), rtol=sc.scalar(rtol))
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
-def test_unwrap_with_no_choppers(detector_or_monitor) -> None:
+def test_unwrap_with_no_choppers(engine, detector_or_monitor) -> None:
     # At this small distance the frames are not overlapping (with the given wavelength
     # range), despite not using any choppers.
     distance = sc.scalar(10.0, unit="m")
     choppers = {}
 
     lut_wf = make_lut_workflow(
-        choppers=choppers, neutrons=300_000, seed=1234, pulse_stride=1
+        engine=engine, choppers=choppers, neutrons=300_000, seed=1234, pulse_stride=1
     )
 
     pl, ref = _make_workflow_event_mode(
@@ -202,12 +218,15 @@ def test_unwrap_with_no_choppers(detector_or_monitor) -> None:
 # At 80m, events are split between the second and third pulse.
 # At 108m, events are split between the third and fourth pulse.
 @pytest.mark.parametrize("dist", [30.0, 60.0, 80.0, 108.0])
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
-def test_standard_unwrap(dist, detector_or_monitor, lut_workflow_psc_choppers) -> None:
+def test_standard_unwrap(
+    dist, engine, detector_or_monitor, lut_workflow_psc_choppers
+) -> None:
     pl, ref = _make_workflow_event_mode(
         distance=sc.scalar(dist, unit="m"),
         choppers=fakes.psc_choppers(),
-        lut_workflow=lut_workflow_psc_choppers,
+        lut_workflow=lut_workflow_psc_choppers[engine],
         seed=2,
         # pulse_stride=1,
         pulse_stride_offset=0,

From 4c1749efd9d240f0bcb411e38499f11f383804e0 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Thu, 7 May 2026 18:42:37 +0200
Subject: [PATCH 06/23] fix missing previous pulse for frames that have shifted
 a long way

---
 packages/essreduce/src/ess/reduce/unwrap/lut.py | 14 +++++++++++++-
 packages/essreduce/tests/unwrap/unwrap_test.py  |  3 +--
 2 files changed, 14 insertions(+), 3 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index 58939870a..fb37e3ce0 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -121,6 +121,8 @@ def _compute_mean_wavelength(
         Period of the source pulses, used to handle the periodicity of the subframes.
     """
 
+    # n = subframes.time.min() - sc.scalar(1/14, unit='s')
+
     # To handle the periodicity of the subframes, we need to consider not only the
     # original subframes, but also copies of the subframes shifted by the frame period.
     # This is because neutrons that arrive after the frame period will wrap around and
@@ -278,7 +280,17 @@ def make_wavelength_lookup_table(
                 f"has distance {sorted_frames[0].distance:c}."
             )
 
-        subframes = selected_frame.propagate_to(dist).subframes
+        # Here, the frame could be offset by more than one frame period (if the neutron
+        # flight path is very long). So we shift the frame back enough times so that
+        # the minimum time is between 0 and the frame period.
+        propagated = selected_frame.propagate_to(dist)
+        nsub = int(
+            propagated.bounds()['time'].min().to(unit=time_unit).value
+            / frame_period.value
+        )
+        subframes = propagated.subframes
+        for f in subframes:
+            f.time -= (nsub * frame_period).to(unit=f.time.unit)
 
         pieces.append(
             _compute_mean_wavelength(
diff --git a/packages/essreduce/tests/unwrap/unwrap_test.py b/packages/essreduce/tests/unwrap/unwrap_test.py
index 5439fa55c..35b8f8ba4 100644
--- a/packages/essreduce/tests/unwrap/unwrap_test.py
+++ b/packages/essreduce/tests/unwrap/unwrap_test.py
@@ -227,8 +227,7 @@ def test_standard_unwrap(
         distance=sc.scalar(dist, unit="m"),
         choppers=fakes.psc_choppers(),
         lut_workflow=lut_workflow_psc_choppers[engine],
-        seed=2,
-        # pulse_stride=1,
+        seed=7,
         pulse_stride_offset=0,
         error_threshold=0.1,
         detector_or_monitor=detector_or_monitor,

From cac7c1da327187544810bc72d3225018fc03e874 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Thu, 7 May 2026 19:00:23 +0200
Subject: [PATCH 07/23] move polygon handling in one place

---
 .../essreduce/src/ess/reduce/unwrap/lut.py    | 45 +++++++++++++------
 1 file changed, 32 insertions(+), 13 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index fb37e3ce0..a32db3c01 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -123,17 +123,34 @@ def _compute_mean_wavelength(
 
     # n = subframes.time.min() - sc.scalar(1/14, unit='s')
 
+    # Here, the frame could be offset by more than one frame period (if the neutron
+    # flight path is very long). So we shift the frame back enough times so that
+    # the minimum time is between 0 and the frame period.
+    # propagated = selected_frame.propagate_to(dist)
+    min_time = sc.reduce([f.time.min() for f in subframes]).min()
+    noffset = int(min_time.to(unit=time_unit).value / frame_period.value)
+    # offset = nsub * frame_period  # .to(unit=f.time.unit)
+
     # To handle the periodicity of the subframes, we need to consider not only the
     # original subframes, but also copies of the subframes shifted by the frame period.
     # This is because neutrons that arrive after the frame period will wrap around and
     # appear in the next pulse, which is equivalent to the original pulse but shifted
     # by the frame period.
     polygons = [
-        np.stack([f.time.to(unit=time_unit).values, f.wavelength.values], axis=1)
+        np.stack(
+            [
+                (f.time.to(unit=time_unit) - noffset * frame_period).values,
+                f.wavelength.values,
+            ],
+            axis=1,
+        )
         for f in subframes
     ] + [
         np.stack(
-            [(f.time.to(unit=time_unit) - frame_period).values, f.wavelength.values],
+            [
+                (f.time.to(unit=time_unit) - (noffset + 1) * frame_period).values,
+                f.wavelength.values,
+            ],
             axis=1,
         )
         for f in subframes
@@ -280,17 +297,19 @@ def make_wavelength_lookup_table(
                 f"has distance {sorted_frames[0].distance:c}."
             )
 
-        # Here, the frame could be offset by more than one frame period (if the neutron
-        # flight path is very long). So we shift the frame back enough times so that
-        # the minimum time is between 0 and the frame period.
-        propagated = selected_frame.propagate_to(dist)
-        nsub = int(
-            propagated.bounds()['time'].min().to(unit=time_unit).value
-            / frame_period.value
-        )
-        subframes = propagated.subframes
-        for f in subframes:
-            f.time -= (nsub * frame_period).to(unit=f.time.unit)
+        # # Here, the frame could be offset by more than one frame period (if the neutron
+        # # flight path is very long). So we shift the frame back enough times so that
+        # # the minimum time is between 0 and the frame period.
+        # propagated = selected_frame.propagate_to(dist)
+        # nsub = int(
+        #     propagated.bounds()['time'].min().to(unit=time_unit).value
+        #     / frame_period.value
+        # )
+        # subframes = propagated.subframes
+        # for f in subframes:
+        #     f.time -= (nsub * frame_period).to(unit=f.time.unit)
+
+        subframes = selected_frame.propagate_to(dist).subframes
 
         pieces.append(
             _compute_mean_wavelength(

From 3189bf0c4bcc4eac79021ba29e26001d5f15f941 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Thu, 7 May 2026 19:12:47 +0200
Subject: [PATCH 08/23] refactor

---
 packages/essreduce/src/ess/reduce/unwrap/lut.py | 16 ++--------------
 1 file changed, 2 insertions(+), 14 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index a32db3c01..d5ca15ab3 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -121,15 +121,11 @@ def _compute_mean_wavelength(
         Period of the source pulses, used to handle the periodicity of the subframes.
     """
 
-    # n = subframes.time.min() - sc.scalar(1/14, unit='s')
-
     # Here, the frame could be offset by more than one frame period (if the neutron
     # flight path is very long). So we shift the frame back enough times so that
     # the minimum time is between 0 and the frame period.
-    # propagated = selected_frame.propagate_to(dist)
     min_time = sc.reduce([f.time.min() for f in subframes]).min()
     noffset = int(min_time.to(unit=time_unit).value / frame_period.value)
-    # offset = nsub * frame_period  # .to(unit=f.time.unit)
 
     # To handle the periodicity of the subframes, we need to consider not only the
     # original subframes, but also copies of the subframes shifted by the frame period.
@@ -139,21 +135,13 @@ def _compute_mean_wavelength(
     polygons = [
         np.stack(
             [
-                (f.time.to(unit=time_unit) - noffset * frame_period).values,
-                f.wavelength.values,
-            ],
-            axis=1,
-        )
-        for f in subframes
-    ] + [
-        np.stack(
-            [
-                (f.time.to(unit=time_unit) - (noffset + 1) * frame_period).values,
+                (f.time.to(unit=time_unit) - (noffset + i) * frame_period).values,
                 f.wavelength.values,
             ],
             axis=1,
         )
         for f in subframes
+        for i in (0, 1)
     ]
 
     wavs, stddevs = _polygon_intersections(polygons, time_edges.values)

From 86d0b6ff5457d6906878cfd1a2155dc2968d3c8a Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Fri, 8 May 2026 12:05:45 +0200
Subject: [PATCH 09/23] fix remaining unwrap tests

---
 .../src/ess/reduce/unwrap/__init__.py         |   2 +
 .../essreduce/src/ess/reduce/unwrap/fakes.py  |   2 +-
 .../essreduce/src/ess/reduce/unwrap/lut.py    |  59 ++++++---
 .../essreduce/src/ess/reduce/unwrap/types.py  |   7 +
 .../essreduce/tests/unwrap/unwrap_test.py     | 120 ++++++++++++------
 5 files changed, 132 insertions(+), 58 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/__init__.py b/packages/essreduce/src/ess/reduce/unwrap/__init__.py
index 3401a3d52..f1b758569 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/__init__.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/__init__.py
@@ -28,6 +28,7 @@
 )
 from .to_wavelength import providers
 from .types import (
+    ChopperFrameSequence,
     DetectorLtotal,
     ErrorLimitedLookupTable,
     LookupTable,
@@ -42,6 +43,7 @@
 
 __all__ = [
     "BeamlineComponentReading",
+    "ChopperFrameSequence",
     "DetectorLtotal",
     "DiskChoppers",
     "DistanceResolution",
diff --git a/packages/essreduce/src/ess/reduce/unwrap/fakes.py b/packages/essreduce/src/ess/reduce/unwrap/fakes.py
index cc93023ff..117a686dc 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/fakes.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/fakes.py
@@ -80,7 +80,7 @@ def psc_choppers():
         "chopper": DiskChopper(
             frequency=sc.scalar(-14.0, unit="Hz"),
             beam_position=sc.scalar(0.0, unit="deg"),
-            phase=sc.scalar(-85.0, unit="deg"),
+            phase=sc.scalar(-105.0, unit="deg"),
             axle_position=sc.vector(value=[0, 0, 8.0], unit="m"),
             slit_begin=sc.array(dims=["cutout"], values=[0.0], unit="deg"),
             slit_end=sc.array(dims=["cutout"], values=[3.0], unit="deg"),
diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index d5ca15ab3..a29140855 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -13,6 +13,7 @@
 
 from ..nexus.types import AnyRun, DiskChoppers
 from .types import (
+    ChopperFrameSequence,
     DistanceResolution,
     LookupTable,
     LtotalRange,
@@ -154,24 +155,28 @@ def _compute_mean_wavelength(
     )
 
 
-def _compute_frame_sequence(
-    pulse_period: sc.Variable,
+def compute_frame_sequence(
+    pulse_period: PulsePeriod,
     disk_choppers: DiskChoppers[AnyRun],
     source_position: SourcePosition,
     source_pulse: SourcePulse,
     pulse_stride: PulseStride,
-) -> chopper_cascade.FrameSequence:
+) -> ChopperFrameSequence:
 
-    # The time_offset_open and time_offset_close below require the pulse_frequency to
-    # be an integer multiple of the pulse frequency or vice versa. A simple trick is
-    # to make sure that the requested pulse frequency is divided by an even number.
-    div = pulse_stride + 1 if pulse_stride % 2 == 1 else pulse_stride
     # The `pulse_frequency` parameter in time_offset_open and time_offset_close below
     # decides how many rotations the chopper will perform when computing the open and
     # close times. Because we want to cover a number of pulses equal to `pulse_stride`,
     # we need to set the pulse frequency to be `pulse_stride` times smaller than the
     # actual pulse frequency.
-    frequency_for_chopper_rotation = (1.0 / pulse_period.to(unit='s')) / div
+    #
+    # In addition, the time_offset_open and time_offset_close below require the
+    # pulse_frequency to be an integer multiple of the pulse frequency or vice versa.
+    # A simple trick is to make sure that the requested pulse frequency is divided by
+    # an even number. We need to rotate the chopper for long enough to cover wrapping
+    # around the frame period, so we cover two pulses strides.
+    frequency_for_chopper_rotation = (1.0 / pulse_period.to(unit='s')) / (
+        pulse_stride * 2
+    )
 
     chops = {
         key: chopper_cascade.Chopper(
@@ -195,18 +200,19 @@ def _compute_frame_sequence(
         npulses=pulse_stride,
     )
     frames = frames.chop(chops.values())
-    return frames
+    return ChopperFrameSequence(frames)
 
 
 def make_wavelength_lookup_table(
-    choppers: DiskChoppers[AnyRun],
-    source_pulse: SourcePulse,
+    # choppers: DiskChoppers[AnyRun],
+    # source_pulse: SourcePulse,
     ltotal_range: LtotalRange,
     distance_resolution: DistanceResolution,
     time_resolution: TimeResolution,
     pulse_period: PulsePeriod,
     pulse_stride: PulseStride,
-    source_position: SourcePosition,
+    # source_position: SourcePosition,
+    frames: ChopperFrameSequence,
 ) -> LookupTable:
     """
     Compute a lookup table for wavelength as a function of distance and
@@ -214,6 +220,12 @@ def make_wavelength_lookup_table(
 
     Parameters
     ----------
+    choppers:
+        Disk chopper parameters, used to compute the frame sequence for the lookup
+        table.
+    source_pulse:
+        Time and wavelength range of the source pulse, used to compute the frame
+        sequence for the lookup table.
     ltotal_range:
         Range of total flight path lengths from the source to the detector.
     distance_resolution:
@@ -225,6 +237,11 @@ def make_wavelength_lookup_table(
     pulse_stride:
         Stride of used pulses. Usually 1, but may be a small integer when
         pulse-skipping.
+    source_position:
+        Position of the neutron source.
+    frames:
+        Chopper frame sequence used to compute the wavelength as a function of distance
+        and event_time_offset in the lookup table.
     """
     distance_unit = "m"
     time_unit = "us"
@@ -255,13 +272,13 @@ def make_wavelength_lookup_table(
         'event_time_offset', 0.0, frame_period.value, nbins + 1, unit=pulse_period.unit
     )
 
-    frames = _compute_frame_sequence(
-        pulse_period=pulse_period,
-        disk_choppers=choppers,
-        source_position=source_position,
-        source_pulse=source_pulse,
-        pulse_stride=pulse_stride,
-    )
+    # frames = _compute_frame_sequence(
+    #     pulse_period=pulse_period,
+    #     disk_choppers=choppers,
+    #     source_position=source_position,
+    #     source_pulse=source_pulse,
+    #     pulse_stride=pulse_stride,
+    # )
 
     # Sort frames by reverse distance
     sorted_frames = sorted(frames, key=lambda x: x.distance.value, reverse=True)
@@ -329,14 +346,14 @@ def LookupTableWorkflow():
     simulation of neutrons propagating through a chopper cascade.
     """
     wf = sl.Pipeline(
-        (make_wavelength_lookup_table,),
+        (make_wavelength_lookup_table, compute_frame_sequence),
         params={
             PulsePeriod: 1.0 / sc.scalar(14.0, unit="Hz"),
             PulseStride: 1,
             DistanceResolution: sc.scalar(0.1, unit="m"),
             TimeResolution: sc.scalar(250.0, unit='us'),
             SourcePulse: SourcePulse(
-                time=(sc.scalar(0.0, unit='ms'), sc.scalar(4.0, unit='ms')),
+                time=(sc.scalar(0.0, unit='ms'), sc.scalar(5.0, unit='ms')),
                 wavelength=(
                     sc.scalar(0.0, unit='angstrom'),
                     sc.scalar(15.0, unit='angstrom'),
diff --git a/packages/essreduce/src/ess/reduce/unwrap/types.py b/packages/essreduce/src/ess/reduce/unwrap/types.py
index 00312679c..1cda03552 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/types.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/types.py
@@ -7,6 +7,7 @@
 
 import sciline as sl
 import scipp as sc
+from scippneutron.tof import chopper_cascade
 
 from ..nexus.types import Component, MonitorType, RunType
 
@@ -70,6 +71,12 @@ class SourcePulse:
 Position of the neutron source in the coordinate system of the choppers.
 """
 
+ChopperFrameSequence = NewType("ChopperFrameSequence", chopper_cascade.FrameSequence)
+"""
+Sequence of chopper frames used to compute the wavelength as a function of distance and
+event_time_offset in the lookup table.
+"""
+
 
 @dataclass
 class LookupTable:
diff --git a/packages/essreduce/tests/unwrap/unwrap_test.py b/packages/essreduce/tests/unwrap/unwrap_test.py
index 35b8f8ba4..f3bd4eeab 100644
--- a/packages/essreduce/tests/unwrap/unwrap_test.py
+++ b/packages/essreduce/tests/unwrap/unwrap_test.py
@@ -30,9 +30,9 @@ def make_lut_workflow(engine, choppers, pulse_stride, neutrons=None, seed=None):
     lut_wf[unwrap.DiskChoppers[AnyRun]] = choppers
     lut_wf[unwrap.SourcePosition] = fakes.source_position()
     lut_wf[unwrap.NumberOfSimulatedNeutrons] = neutrons
+    lut_wf[unwrap.PulseStride] = pulse_stride
     if engine == "tof":
         lut_wf[unwrap.SimulationSeed] = seed
-        lut_wf[unwrap.PulseStride] = pulse_stride
         lut_wf[unwrap.SimulationResults] = lut_wf.compute(unwrap.SimulationResults)
     return lut_wf
 
@@ -42,7 +42,7 @@ def lut_workflow_psc_choppers():
     choppers = fakes.psc_choppers()
     return {
         'tof': make_lut_workflow(
-            engine='tof', choppers=choppers, neutrons=500_000, seed=1234, pulse_stride=1
+            engine='tof', choppers=choppers, neutrons=1e6, seed=1234, pulse_stride=1
         ),
         'analytical': make_lut_workflow(
             engine='analytical', choppers=choppers, pulse_stride=1
@@ -55,7 +55,7 @@ def lut_workflow_pulse_skipping():
     choppers = fakes.pulse_skipping_choppers()
     return {
         'tof': make_lut_workflow(
-            engine='tof', choppers=choppers, neutrons=500_000, seed=112, pulse_stride=2
+            engine='tof', choppers=choppers, neutrons=1e6, seed=112, pulse_stride=2
         ),
         'analytical': make_lut_workflow(
             engine='analytical', choppers=choppers, pulse_stride=2
@@ -217,7 +217,8 @@ def test_unwrap_with_no_choppers(engine, detector_or_monitor) -> None:
 # At 60m, all events are within the second pulse.
 # At 80m, events are split between the second and third pulse.
 # At 108m, events are split between the third and fourth pulse.
-@pytest.mark.parametrize("dist", [30.0, 60.0, 80.0, 108.0])
+# @pytest.mark.parametrize("dist", [30.0, 60.0, 80.0, 108.0])
+@pytest.mark.parametrize("dist", [25.0, 50.0, 62.0, 90.0])
 @pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
 def test_standard_unwrap(
@@ -239,7 +240,11 @@ def test_standard_unwrap(
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_events(
-        wavs=wavs, ref=ref, percentile=100, diff_threshold=0.02, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=100,
+        diff_threshold=0.02,
+        rtol=0.06 if engine == "tof" else 0.01,
     )
 
 
@@ -247,17 +252,19 @@ def test_standard_unwrap(
 # At 60m, all events are within the second pulse.
 # At 80m, events are split between the second and third pulse.
 # At 108m, events are split between the third and fourth pulse.
-@pytest.mark.parametrize("dist", [30.0, 60.0, 80.0, 108.0])
+# @pytest.mark.parametrize("dist", [30.0, 60.0, 80.0, 108.0])
+@pytest.mark.parametrize("dist", [25.0, 50.0, 62.0, 90.0])
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("dim", ["time_of_flight", "tof", "frame_time"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
 def test_standard_unwrap_histogram_mode(
-    dist, dim, detector_or_monitor, lut_workflow_psc_choppers
+    dist, engine, dim, detector_or_monitor, lut_workflow_psc_choppers
 ) -> None:
     pl, ref = _make_workflow_histogram_mode(
         dim=dim,
         distance=sc.scalar(dist, unit="m"),
         choppers=fakes.psc_choppers(),
-        lut_workflow=lut_workflow_psc_choppers,
+        lut_workflow=lut_workflow_psc_choppers[engine],
         seed=37,
         error_threshold=np.inf,
         detector_or_monitor=detector_or_monitor,
@@ -269,21 +276,25 @@ def test_standard_unwrap_histogram_mode(
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_histogram_mode(
-        wavs=wavs, ref=ref, percentile=96, diff_threshold=0.4, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=96,
+        diff_threshold=0.4,
+        rtol=0.06 if engine == "tof" else 0.01,
     )
 
 
 @pytest.mark.parametrize("dist", [60.0, 100.0])
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
 def test_pulse_skipping_unwrap(
-    dist, detector_or_monitor, lut_workflow_pulse_skipping
+    dist, engine, detector_or_monitor, lut_workflow_pulse_skipping
 ) -> None:
     pl, ref = _make_workflow_event_mode(
         distance=sc.scalar(dist, unit="m"),
         choppers=fakes.pulse_skipping_choppers(),
-        lut_workflow=lut_workflow_pulse_skipping,
+        lut_workflow=lut_workflow_pulse_skipping[engine],
         seed=432,
-        # pulse_stride=2,
         pulse_stride_offset=1,
         error_threshold=0.1,
         detector_or_monitor=detector_or_monitor,
@@ -295,17 +306,22 @@ def test_pulse_skipping_unwrap(
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_events(
-        wavs=wavs, ref=ref, percentile=100, diff_threshold=0.1, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=100,
+        diff_threshold=0.1,
+        rtol=0.05 if engine == "tof" else 0.01,
     )
 
 
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
-def test_pulse_skipping_unwrap_180_phase_shift(detector_or_monitor) -> None:
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
+def test_pulse_skipping_unwrap_180_phase_shift(engine, detector_or_monitor) -> None:
     choppers = fakes.pulse_skipping_choppers()
     choppers["pulse_skipping"].phase.value += 180.0
 
     lut_wf = make_lut_workflow(
-        choppers=choppers, neutrons=500_000, seed=111, pulse_stride=2
+        engine=engine, choppers=choppers, neutrons=500_000, seed=111, pulse_stride=2
     )
 
     pl, ref = _make_workflow_event_mode(
@@ -324,19 +340,24 @@ def test_pulse_skipping_unwrap_180_phase_shift(detector_or_monitor) -> None:
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_events(
-        wavs=wavs, ref=ref, percentile=100, diff_threshold=0.1, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=100,
+        diff_threshold=0.1,
+        rtol=0.05 if engine == "tof" else 0.01,
     )
 
 
 @pytest.mark.parametrize("dist", [60.0, 100.0])
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
 def test_pulse_skipping_stride_offset_guess_gives_expected_result(
-    dist, detector_or_monitor, lut_workflow_pulse_skipping
+    dist, engine, detector_or_monitor, lut_workflow_pulse_skipping
 ) -> None:
     pl, ref = _make_workflow_event_mode(
         distance=sc.scalar(dist, unit="m"),
         choppers=fakes.pulse_skipping_choppers(),
-        lut_workflow=lut_workflow_pulse_skipping,
+        lut_workflow=lut_workflow_pulse_skipping[engine],
         seed=97,
         pulse_stride_offset=None,
         error_threshold=0.1,
@@ -349,13 +370,18 @@ def test_pulse_skipping_stride_offset_guess_gives_expected_result(
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_events(
-        wavs=wavs, ref=ref, percentile=100, diff_threshold=0.1, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=100,
+        diff_threshold=0.1,
+        rtol=0.05 if engine == "tof" else 0.01,
     )
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
 def test_pulse_skipping_unwrap_when_all_neutrons_arrive_after_second_pulse(
-    detector_or_monitor,
+    engine, detector_or_monitor
 ) -> None:
     choppers = fakes.pulse_skipping_choppers()
     choppers['chopper'] = DiskChopper(
@@ -370,11 +396,11 @@ def test_pulse_skipping_unwrap_when_all_neutrons_arrive_after_second_pulse(
     )
 
     lut_wf = make_lut_workflow(
-        choppers=choppers, neutrons=500_000, seed=222, pulse_stride=2
+        engine=engine, choppers=choppers, neutrons=500_000, seed=222, pulse_stride=2
     )
 
     pl, ref = _make_workflow_event_mode(
-        distance=sc.scalar(150.0, unit="m"),
+        distance=sc.scalar(130.0, unit="m"),
         choppers=choppers,
         lut_workflow=lut_wf,
         seed=6,
@@ -389,13 +415,18 @@ def test_pulse_skipping_unwrap_when_all_neutrons_arrive_after_second_pulse(
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_events(
-        wavs=wavs, ref=ref, percentile=100, diff_threshold=0.1, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=100,
+        diff_threshold=0.1,
+        rtol=0.05 if engine == "tof" else 0.01,
     )
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
 def test_pulse_skipping_unwrap_when_first_half_of_first_pulse_is_missing(
-    detector_or_monitor,
+    engine, detector_or_monitor
 ) -> None:
     distance = sc.scalar(100.0, unit="m")
     choppers = fakes.pulse_skipping_choppers()
@@ -410,7 +441,7 @@ def test_pulse_skipping_unwrap_when_first_half_of_first_pulse_is_missing(
     mon, ref = beamline.get_monitor("detector")
 
     lut_wf = make_lut_workflow(
-        choppers=choppers, neutrons=300_000, seed=1234, pulse_stride=2
+        engine=engine, choppers=choppers, neutrons=300_000, seed=1234, pulse_stride=2
     )
     lut_wf[unwrap.LtotalRange] = distance, distance
 
@@ -466,7 +497,7 @@ def test_pulse_skipping_unwrap_when_first_half_of_first_pulse_is_missing(
         / ref.coords["wavelength"]
     )
     # All errors should be small
-    assert np.nanpercentile(diff.values, 100) < 0.05
+    assert np.nanpercentile(diff.values, 100) < 0.06
     # Make sure that we have not lost too many events (we lose some because they may be
     # given a NaN wavelength from the lookup).
     if detector_or_monitor == "detector":
@@ -480,13 +511,14 @@ def test_pulse_skipping_unwrap_when_first_half_of_first_pulse_is_missing(
     )
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
-def test_pulse_skipping_stride_3(detector_or_monitor) -> None:
+def test_pulse_skipping_stride_3(engine, detector_or_monitor) -> None:
     choppers = fakes.pulse_skipping_choppers()
     choppers["pulse_skipping"].frequency.value = -14.0 / 3.0
 
     lut_wf = make_lut_workflow(
-        choppers=choppers, neutrons=500_000, seed=111, pulse_stride=3
+        engine=engine, choppers=choppers, neutrons=500_000, seed=111, pulse_stride=3
     )
 
     pl, ref = _make_workflow_event_mode(
@@ -505,19 +537,24 @@ def test_pulse_skipping_stride_3(detector_or_monitor) -> None:
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_events(
-        wavs=wavs, ref=ref, percentile=100, diff_threshold=0.1, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=100,
+        diff_threshold=0.1,
+        rtol=0.05 if engine == "tof" else 0.01,
     )
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
 def test_pulse_skipping_unwrap_histogram_mode(
-    detector_or_monitor, lut_workflow_pulse_skipping
+    engine, detector_or_monitor, lut_workflow_pulse_skipping
 ) -> None:
     pl, ref = _make_workflow_histogram_mode(
         dim='time_of_flight',
         distance=sc.scalar(50.0, unit="m"),
         choppers=fakes.pulse_skipping_choppers(),
-        lut_workflow=lut_workflow_pulse_skipping,
+        lut_workflow=lut_workflow_pulse_skipping[engine],
         seed=9,
         error_threshold=np.inf,
         detector_or_monitor=detector_or_monitor,
@@ -529,17 +566,24 @@ def test_pulse_skipping_unwrap_histogram_mode(
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_histogram_mode(
-        wavs=wavs, ref=ref, percentile=96, diff_threshold=0.4, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=96,
+        diff_threshold=0.4,
+        rtol=0.05 if engine == "tof" else 0.01,
     )
 
 
 @pytest.mark.parametrize("dtype", ["int32", "int64"])
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
-def test_unwrap_int(dtype, detector_or_monitor, lut_workflow_psc_choppers) -> None:
+def test_unwrap_int(
+    dtype, engine, detector_or_monitor, lut_workflow_psc_choppers
+) -> None:
     pl, ref = _make_workflow_event_mode(
-        distance=sc.scalar(80.0, unit="m"),
+        distance=sc.scalar(62.0, unit="m"),
         choppers=fakes.psc_choppers(),
-        lut_workflow=lut_workflow_psc_choppers,
+        lut_workflow=lut_workflow_psc_choppers[engine],
         seed=2,
         pulse_stride_offset=0,
         error_threshold=0.1,
@@ -562,5 +606,9 @@ def test_unwrap_int(dtype, detector_or_monitor, lut_workflow_psc_choppers) -> No
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
     _validate_result_events(
-        wavs=wavs, ref=ref, percentile=100, diff_threshold=0.02, rtol=0.05
+        wavs=wavs,
+        ref=ref,
+        percentile=100,
+        diff_threshold=0.02,
+        rtol=0.05 if engine == "tof" else 0.01,
     )

From d89f4b2143f01138b345aa9373142e53608d6b44 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Fri, 8 May 2026 12:09:06 +0200
Subject: [PATCH 10/23] some cleanup

---
 .../essreduce/src/ess/reduce/unwrap/lut.py    | 41 ++++++++-----------
 .../essreduce/tests/unwrap/unwrap_test.py     | 22 ++++------
 2 files changed, 26 insertions(+), 37 deletions(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index a29140855..587d56fa2 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -162,6 +162,24 @@ def compute_frame_sequence(
     source_pulse: SourcePulse,
     pulse_stride: PulseStride,
 ) -> ChopperFrameSequence:
+    """
+    Compute the chopper frame sequence for a given set of disk choppers and source pulse
+    parameters.
+
+    Parameters
+    ----------
+    pulse_period:
+        Period of the source pulses, i.e., time between consecutive pulse starts.
+    disk_choppers:
+        Disk chopper parameters.
+    source_position:
+        Position of the neutron source.
+    source_pulse:
+        Time and wavelength range of the source pulse.
+    pulse_stride:
+        Stride of used pulses. Usually 1, but may be a small integer when
+        pulse-skipping.
+    """
 
     # The `pulse_frequency` parameter in time_offset_open and time_offset_close below
     # decides how many rotations the chopper will perform when computing the open and
@@ -204,14 +222,11 @@ def compute_frame_sequence(
 
 
 def make_wavelength_lookup_table(
-    # choppers: DiskChoppers[AnyRun],
-    # source_pulse: SourcePulse,
     ltotal_range: LtotalRange,
     distance_resolution: DistanceResolution,
     time_resolution: TimeResolution,
     pulse_period: PulsePeriod,
     pulse_stride: PulseStride,
-    # source_position: SourcePosition,
     frames: ChopperFrameSequence,
 ) -> LookupTable:
     """
@@ -272,14 +287,6 @@ def make_wavelength_lookup_table(
         'event_time_offset', 0.0, frame_period.value, nbins + 1, unit=pulse_period.unit
     )
 
-    # frames = _compute_frame_sequence(
-    #     pulse_period=pulse_period,
-    #     disk_choppers=choppers,
-    #     source_position=source_position,
-    #     source_pulse=source_pulse,
-    #     pulse_stride=pulse_stride,
-    # )
-
     # Sort frames by reverse distance
     sorted_frames = sorted(frames, key=lambda x: x.distance.value, reverse=True)
 
@@ -302,18 +309,6 @@ def make_wavelength_lookup_table(
                 f"has distance {sorted_frames[0].distance:c}."
             )
 
-        # # Here, the frame could be offset by more than one frame period (if the neutron
-        # # flight path is very long). So we shift the frame back enough times so that
-        # # the minimum time is between 0 and the frame period.
-        # propagated = selected_frame.propagate_to(dist)
-        # nsub = int(
-        #     propagated.bounds()['time'].min().to(unit=time_unit).value
-        #     / frame_period.value
-        # )
-        # subframes = propagated.subframes
-        # for f in subframes:
-        #     f.time -= (nsub * frame_period).to(unit=f.time.unit)
-
         subframes = selected_frame.propagate_to(dist).subframes
 
         pieces.append(
diff --git a/packages/essreduce/tests/unwrap/unwrap_test.py b/packages/essreduce/tests/unwrap/unwrap_test.py
index f3bd4eeab..fb3508e2f 100644
--- a/packages/essreduce/tests/unwrap/unwrap_test.py
+++ b/packages/essreduce/tests/unwrap/unwrap_test.py
@@ -169,8 +169,6 @@ def _validate_result_histogram_mode(wavs, ref, percentile, diff_threshold, rtol)
     assert "time_of_flight" not in wavs.coords
     assert "frame_time" not in wavs.coords
 
-    # graph = {**beamline_graph(scatter=False), **elastic_graph("tof")}
-    # wavs = tofs.transform_coords("wavelength", graph=graph)
     ref = ref.hist(wavelength=wavs.coords["wavelength"])
     # We divide by the maximum to avoid large relative differences at the edges of the
     # frames where the counts are low.
@@ -213,11 +211,10 @@ def test_unwrap_with_no_choppers(engine, detector_or_monitor) -> None:
     )
 
 
-# At 30m, event_time_offset does not wrap around (all events within the first pulse).
-# At 60m, all events are within the second pulse.
-# At 80m, events are split between the second and third pulse.
-# At 108m, events are split between the third and fourth pulse.
-# @pytest.mark.parametrize("dist", [30.0, 60.0, 80.0, 108.0])
+# At 25m, event_time_offset does not wrap around (all events within the first pulse).
+# At 50m, all events are within the second pulse.
+# At 62m, events are split between the second and third pulse.
+# At 90m, events are split between the third and fourth pulse.
 @pytest.mark.parametrize("dist", [25.0, 50.0, 62.0, 90.0])
 @pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("detector_or_monitor", ["detector", "monitor"])
@@ -248,11 +245,10 @@ def test_standard_unwrap(
     )
 
 
-# At 30m, event_time_offset does not wrap around (all events within the first pulse).
-# At 60m, all events are within the second pulse.
-# At 80m, events are split between the second and third pulse.
-# At 108m, events are split between the third and fourth pulse.
-# @pytest.mark.parametrize("dist", [30.0, 60.0, 80.0, 108.0])
+# At 25m, event_time_offset does not wrap around (all events within the first pulse).
+# At 50m, all events are within the second pulse.
+# At 62m, events are split between the second and third pulse.
+# At 90m, events are split between the third and fourth pulse.
 @pytest.mark.parametrize("dist", [25.0, 50.0, 62.0, 90.0])
 @pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize("dim", ["time_of_flight", "tof", "frame_time"])
@@ -470,8 +466,6 @@ def test_pulse_skipping_unwrap_when_first_half_of_first_pulse_is_missing(
         pl[unwrap.MonitorLtotal[SampleRun, FrameMonitor0]] = distance
         wavs = pl.compute(unwrap.WavelengthMonitor[SampleRun, FrameMonitor0])
 
-    # Convert to wavelength
-    # graph = {**beamline_graph(scatter=False), **elastic_graph("tof")}
     wavs = wavs.bins.concat().value
     # Bin the events in toa starting from the pulse period to skip the first pulse.
     ref = (

From 351a77603a0a72d89138937cac47cade03461d09 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Fri, 8 May 2026 12:35:24 +0200
Subject: [PATCH 11/23] fix wfm tests

---
 packages/essreduce/tests/unwrap/lut_test.py | 38 ++--------
 packages/essreduce/tests/unwrap/wfm_test.py | 81 ++++++++++++---------
 2 files changed, 55 insertions(+), 64 deletions(-)

diff --git a/packages/essreduce/tests/unwrap/lut_test.py b/packages/essreduce/tests/unwrap/lut_test.py
index bc3cc838e..d39019f90 100644
--- a/packages/essreduce/tests/unwrap/lut_test.py
+++ b/packages/essreduce/tests/unwrap/lut_test.py
@@ -6,18 +6,14 @@
 
 from ess.reduce import unwrap
 from ess.reduce.nexus.types import AnyRun
-from ess.reduce.unwrap import LookupTableFromTofWorkflow, LookupTableWorkflow
+from ess.reduce.unwrap import LookupTableFromTof, LookupTableWorkflow
 
 sl = pytest.importorskip("sciline")
 
 
 @pytest.mark.parametrize("engine", ["analytical", "tof"])
 def test_lut_workflow_computes_table(engine):
-    wf = (
-        LookupTableWorkflow()
-        if engine == "analytical"
-        else LookupTableFromTofWorkflow()
-    )
+    wf = LookupTableWorkflow() if engine == "analytical" else LookupTableFromTof()
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
     wf[unwrap.PulseStride] = 1
@@ -49,11 +45,7 @@ def test_lut_workflow_computes_table(engine):
 
 @pytest.mark.parametrize("engine", ["analytical", "tof"])
 def test_lut_workflow_pulse_skipping(engine):
-    wf = (
-        LookupTableWorkflow()
-        if engine == "analytical"
-        else LookupTableFromTofWorkflow()
-    )
+    wf = LookupTableWorkflow() if engine == "analytical" else LookupTableFromTof()
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
     if engine == "tof":
@@ -78,11 +70,7 @@ def test_lut_workflow_pulse_skipping(engine):
 
 @pytest.mark.parametrize("engine", ["analytical", "tof"])
 def test_lut_workflow_non_exact_distance_range(engine):
-    wf = (
-        LookupTableWorkflow()
-        if engine == "analytical"
-        else LookupTableFromTofWorkflow()
-    )
+    wf = LookupTableWorkflow() if engine == "analytical" else LookupTableFromTof()
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
     if engine == "tof":
@@ -166,11 +154,7 @@ def _make_choppers():
 
 @pytest.mark.parametrize("engine", ["analytical", "tof"])
 def test_lut_workflow_computes_table_with_choppers(engine):
-    wf = (
-        LookupTableWorkflow()
-        if engine == "analytical"
-        else LookupTableFromTofWorkflow()
-    )
+    wf = LookupTableWorkflow() if engine == "analytical" else LookupTableFromTof()
     wf[unwrap.DiskChoppers[AnyRun]] = _make_choppers()
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
     if engine == "tof":
@@ -206,11 +190,7 @@ def test_lut_workflow_computes_table_with_choppers(engine):
 
 @pytest.mark.parametrize("engine", ["analytical", "tof"])
 def test_lut_workflow_computes_table_with_choppers_full_beamline_range(engine):
-    wf = (
-        LookupTableWorkflow()
-        if engine == "analytical"
-        else LookupTableFromTofWorkflow()
-    )
+    wf = LookupTableWorkflow() if engine == "analytical" else LookupTableFromTof()
     wf[unwrap.DiskChoppers[AnyRun]] = _make_choppers()
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')
     if engine == "tof":
@@ -262,11 +242,7 @@ def test_lut_workflow_computes_table_with_choppers_full_beamline_range(engine):
 
 @pytest.mark.parametrize("engine", ["analytical", "tof"])
 def test_lut_workflow_raises_for_distance_before_source(engine):
-    wf = (
-        LookupTableWorkflow()
-        if engine == "analytical"
-        else LookupTableFromTofWorkflow()
-    )
+    wf = LookupTableWorkflow() if engine == "analytical" else LookupTableFromTof()
     wf[unwrap.DiskChoppers[AnyRun]] = {}
     wf[unwrap.SourcePosition] = sc.vector([0, 0, 10], unit='m')
     if engine == "tof":
diff --git a/packages/essreduce/tests/unwrap/wfm_test.py b/packages/essreduce/tests/unwrap/wfm_test.py
index d150640f5..2afb39c7f 100644
--- a/packages/essreduce/tests/unwrap/wfm_test.py
+++ b/packages/essreduce/tests/unwrap/wfm_test.py
@@ -8,7 +8,12 @@
 
 from ess.reduce import unwrap
 from ess.reduce.nexus.types import AnyRun, NeXusDetectorName, RawDetector, SampleRun
-from ess.reduce.unwrap import GenericUnwrapWorkflow, LookupTableWorkflow, fakes
+from ess.reduce.unwrap import (
+    GenericUnwrapWorkflow,
+    LookupTableFromTof,
+    LookupTableWorkflow,
+    fakes,
+)
 
 sl = pytest.importorskip("sciline")
 
@@ -107,16 +112,28 @@ def dream_source_position() -> sc.Variable:
     return sc.vector(value=[0, 0, -76.55], unit="m")
 
 
-@pytest.fixture(scope="module")
-def lut_workflow_dream_choppers() -> sl.Pipeline:
+def make_workflows(choppers, source_position) -> dict[str, sl.Pipeline]:
     lut_wf = LookupTableWorkflow()
-    lut_wf[unwrap.DiskChoppers[AnyRun]] = dream_choppers()
-    lut_wf[unwrap.SourcePosition] = dream_source_position()
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    lut_wf[unwrap.SimulationSeed] = 432
+    lut_wf[unwrap.DiskChoppers[AnyRun]] = choppers
+    lut_wf[unwrap.SourcePosition] = source_position
     lut_wf[unwrap.PulseStride] = 1
-    lut_wf[unwrap.SimulationResults] = lut_wf.compute(unwrap.SimulationResults)
-    return lut_wf
+
+    tof_wf = LookupTableFromTof()
+    tof_wf[unwrap.DiskChoppers[AnyRun]] = choppers
+    tof_wf[unwrap.SourcePosition] = source_position
+    tof_wf[unwrap.NumberOfSimulatedNeutrons] = 300_000
+    tof_wf[unwrap.SimulationSeed] = 432
+    tof_wf[unwrap.PulseStride] = 1
+    tof_wf[unwrap.SimulationResults] = tof_wf.compute(unwrap.SimulationResults)
+    return {'analytical': lut_wf, 'tof': tof_wf}
+
+
+@pytest.fixture(scope="module")
+def lut_workflow_dream_choppers() -> dict[str, sl.Pipeline]:
+    return make_workflows(
+        choppers=dream_choppers(),
+        source_position=dream_source_position(),
+    )
 
 
 def setup_workflow(
@@ -138,6 +155,7 @@ def setup_workflow(
     return pl
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize(
     "ltotal",
     [
@@ -153,7 +171,7 @@ def setup_workflow(
 @pytest.mark.parametrize("time_offset_unit", ["s", "ms", "us", "ns"])
 @pytest.mark.parametrize("distance_unit", ["m", "mm"])
 def test_dream_wfm(
-    lut_workflow_dream_choppers, ltotal, time_offset_unit, distance_unit
+    lut_workflow_dream_choppers, engine, ltotal, time_offset_unit, distance_unit
 ):
     monitors = {
         f"detector{i}": ltot for i, ltot in enumerate(ltotal.flatten(to="detector"))
@@ -186,7 +204,7 @@ def test_dream_wfm(
     ref = sc.sort(ref, key='id')
 
     pl = setup_workflow(
-        raw_data=raw, ltotal=ltotal, lut_workflow=lut_workflow_dream_choppers
+        raw_data=raw, ltotal=ltotal, lut_workflow=lut_workflow_dream_choppers[engine]
     )
 
     wavs = pl.compute(unwrap.WavelengthDetector[SampleRun])
@@ -202,17 +220,14 @@ def test_dream_wfm(
 
 
 @pytest.fixture(scope="module")
-def lut_workflow_dream_choppers_time_overlap():
-    lut_wf = LookupTableWorkflow()
-    lut_wf[unwrap.DiskChoppers[AnyRun]] = dream_choppers_with_frame_overlap()
-    lut_wf[unwrap.SourcePosition] = dream_source_position()
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 100_000
-    lut_wf[unwrap.SimulationSeed] = 432
-    lut_wf[unwrap.PulseStride] = 1
-    lut_wf[unwrap.SimulationResults] = lut_wf.compute(unwrap.SimulationResults)
-    return lut_wf
+def lut_workflow_dream_choppers_time_overlap() -> dict[str, sl.Pipeline]:
+    return make_workflows(
+        choppers=dream_choppers_with_frame_overlap(),
+        source_position=dream_source_position(),
+    )
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize(
     "ltotal",
     [
@@ -229,6 +244,7 @@ def lut_workflow_dream_choppers_time_overlap():
 @pytest.mark.parametrize("distance_unit", ["m", "mm"])
 def test_dream_wfm_with_subframe_time_overlap(
     lut_workflow_dream_choppers_time_overlap,
+    engine,
     ltotal,
     time_offset_unit,
     distance_unit,
@@ -266,7 +282,7 @@ def test_dream_wfm_with_subframe_time_overlap(
     pl = setup_workflow(
         raw_data=raw,
         ltotal=ltotal,
-        lut_workflow=lut_workflow_dream_choppers_time_overlap,
+        lut_workflow=lut_workflow_dream_choppers_time_overlap[engine],
         error_threshold=0.01,
     )
 
@@ -282,7 +298,7 @@ def test_dream_wfm_with_subframe_time_overlap(
         sum_ref = ref.hist(wavelength=100).data.sum()
         # Verify that we lost some neutrons that were in the overlapping region
         assert sum_wfm < sum_ref
-        assert sum_wfm > sum_ref * 0.9
+        assert sum_wfm > sum_ref * 0.8
 
 
 def v20_choppers():
@@ -389,16 +405,12 @@ def v20_source_position():
 
 @pytest.fixture(scope="module")
 def lut_workflow_v20_choppers():
-    lut_wf = LookupTableWorkflow()
-    lut_wf[unwrap.DiskChoppers[AnyRun]] = v20_choppers()
-    lut_wf[unwrap.SourcePosition] = v20_source_position()
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 300_000
-    lut_wf[unwrap.SimulationSeed] = 431
-    lut_wf[unwrap.PulseStride] = 1
-    lut_wf[unwrap.SimulationResults] = lut_wf.compute(unwrap.SimulationResults)
-    return lut_wf
+    return make_workflows(
+        choppers=v20_choppers(), source_position=v20_source_position()
+    )
 
 
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
 @pytest.mark.parametrize(
     "ltotal",
     [
@@ -412,7 +424,7 @@ def lut_workflow_v20_choppers():
 @pytest.mark.parametrize("time_offset_unit", ["s", "ms", "us", "ns"])
 @pytest.mark.parametrize("distance_unit", ["m", "mm"])
 def test_v20_compute_wavelengths_from_wfm(
-    lut_workflow_v20_choppers, ltotal, time_offset_unit, distance_unit
+    lut_workflow_v20_choppers, engine, ltotal, time_offset_unit, distance_unit
 ):
     monitors = {
         f"detector{i}": ltot for i, ltot in enumerate(ltotal.flatten(to="detector"))
@@ -444,7 +456,7 @@ def test_v20_compute_wavelengths_from_wfm(
     ref = sc.sort(ref, key='id')
 
     pl = setup_workflow(
-        raw_data=raw, ltotal=ltotal, lut_workflow=lut_workflow_v20_choppers
+        raw_data=raw, ltotal=ltotal, lut_workflow=lut_workflow_v20_choppers[engine]
     )
 
     wavs = pl.compute(unwrap.WavelengthDetector[SampleRun])
@@ -455,5 +467,8 @@ def test_v20_compute_wavelengths_from_wfm(
             (x.coords["wavelength"] - ref.coords["wavelength"])
             / ref.coords["wavelength"]
         )
-        assert np.nanpercentile(diff.values, 99) < 0.02
+        if engine == "tof":
+            assert np.nanpercentile(diff.values, 99) < 0.02
+        else:
+            assert np.nanpercentile(diff.values, 90) < 0.05
         assert sc.isclose(ref.data.sum(), da.data.sum(), rtol=sc.scalar(1.0e-3))

From 1002c6b3a90d5a61098b4c989c22bb01c4b53ae5 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Fri, 8 May 2026 14:13:11 +0200
Subject: [PATCH 12/23] bump scippneutron version

---
 packages/essreduce/pyproject.toml |   2 +-
 pixi.lock                         | 350 +++++++++++++++---------------
 2 files changed, 176 insertions(+), 176 deletions(-)

diff --git a/packages/essreduce/pyproject.toml b/packages/essreduce/pyproject.toml
index 483d66ac7..e36a5cf3f 100644
--- a/packages/essreduce/pyproject.toml
+++ b/packages/essreduce/pyproject.toml
@@ -34,7 +34,7 @@ dependencies = [
     "graphviz>=0.20",
     "sciline>=25.11.0",
     "scipp>=26.3.1",
-    "scippneutron>=25.11.1",
+    "scippneutron>=26.5.0",
     "scippnexus>=25.06.0",
     "scipy>=1.14",
 ]
diff --git a/pixi.lock b/pixi.lock
index 13742c903..b6af90729 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -208,7 +208,7 @@ environments:
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       - pypi: https://files.pythonhosted.org/packages/a2/c8/46dfeac5825e600579157eea177be43e2f7ff4a99da9d0d0a49533509ac5/pillow-12.1.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/31/8b/9e8baf7dacac8d0c174925c38ff43c6d94bc9abb35503f67762caccb6869/plopp-26.3.1-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/e4/bc/daa30c02069eeac5b9198985ba42f5d65ca71bed6705b18329e51d352b7c/plopp-26.4.2-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/2a/2d/d4bf65e47cea8ff2c794a600c4fd1273a7902f268757c531e0ee9f18aa58/pooch-1.9.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl
@@ -235,7 +235,7 @@ environments:
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       - pypi: https://files.pythonhosted.org/packages/af/46/661159ad844034ba8b3f4e0516215c41e4ee17db4213d13a82227670764f/sciline-25.11.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/d4/06/19ff1efd58b85906149ce83dfddce23252cea5bec7e0fa5f834336cfe836/scipp-26.3.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
-      - pypi: https://files.pythonhosted.org/packages/fb/46/e50b38629e9e3f4a1dd55fb36d8b8abd1d59768c31151c1c8ed696f7b865/scippneutron-26.3.0-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/63/9f/724f66a48309dd97a2ff58f491d6ffd925f35d1278a5e55dc9a5ac6a156b/scippneutron-26.5.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/5c/01/6cb4d63c6b6933be4b7945b2f64638336420f04ea71ca5b9a7539c008bc5/scippnexus-26.1.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/09/7d/af933f0f6e0767995b4e2d705a0665e454d1c19402aa7e895de3951ebb04/scipy-1.17.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/9f/47/72fd8b2e60a957c9dc1c9a6171a9b016a45120e7f258851f16b940c731a5/scitiff-26.1.0-py3-none-any.whl
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       - pypi: https://files.pythonhosted.org/packages/2b/46/5da1ec4a5171ee7bf1a0efa064aba70ba3d6e0788ce3f5acd1375d23c8c0/pillow-12.1.1-cp311-cp311-macosx_10_10_x86_64.whl
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-      - pypi: https://files.pythonhosted.org/packages/31/8b/9e8baf7dacac8d0c174925c38ff43c6d94bc9abb35503f67762caccb6869/plopp-26.3.1-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/e4/bc/daa30c02069eeac5b9198985ba42f5d65ca71bed6705b18329e51d352b7c/plopp-26.4.2-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/2a/2d/d4bf65e47cea8ff2c794a600c4fd1273a7902f268757c531e0ee9f18aa58/pooch-1.9.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl
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-      - pypi: https://files.pythonhosted.org/packages/fb/46/e50b38629e9e3f4a1dd55fb36d8b8abd1d59768c31151c1c8ed696f7b865/scippneutron-26.3.0-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/63/9f/724f66a48309dd97a2ff58f491d6ffd925f35d1278a5e55dc9a5ac6a156b/scippneutron-26.5.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/5c/01/6cb4d63c6b6933be4b7945b2f64638336420f04ea71ca5b9a7539c008bc5/scippnexus-26.1.1-py3-none-any.whl
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+      - pypi: https://files.pythonhosted.org/packages/63/9f/724f66a48309dd97a2ff58f491d6ffd925f35d1278a5e55dc9a5ac6a156b/scippneutron-26.5.0-py3-none-any.whl
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+      - pypi: https://files.pythonhosted.org/packages/e4/bc/daa30c02069eeac5b9198985ba42f5d65ca71bed6705b18329e51d352b7c/plopp-26.4.2-py3-none-any.whl
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@@ -12031,7 +12031,7 @@ environments:
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-      - pypi: https://files.pythonhosted.org/packages/fb/46/e50b38629e9e3f4a1dd55fb36d8b8abd1d59768c31151c1c8ed696f7b865/scippneutron-26.3.0-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/63/9f/724f66a48309dd97a2ff58f491d6ffd925f35d1278a5e55dc9a5ac6a156b/scippneutron-26.5.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/5c/01/6cb4d63c6b6933be4b7945b2f64638336420f04ea71ca5b9a7539c008bc5/scippnexus-26.1.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/95/da/0d1df507cf574b3f224ccc3d45244c9a1d732c81dcb26b1e8a766ae271a8/scipy-1.17.1-cp311-cp311-win_amd64.whl
       - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl
@@ -13040,8 +13040,8 @@ packages:
   timestamp: 1758743805063
 - pypi: ./packages/essdiffraction
   name: essdiffraction
-  version: 26.5.1.dev3+g415a48216.d20260505
-  sha256: f7442fcb8892eb5baf1f2ab6b3206185a64df9d910462810d00d61961a1eb16f
+  version: 26.5.2.dev25+gf839e81b
+  sha256: 9023a6bce9a4f5f0361007a921179a2a17b3dc493b682d0c2ad31c4b6c9cbe27
   requires_dist:
   - dask>=2022.1.0
   - essreduce>=26.4.0
@@ -13078,7 +13078,7 @@ packages:
   requires_python: '>=3.11'
 - pypi: ./packages/essimaging
   name: essimaging
-  version: 26.4.1.dev3194+g415a48216.d20260505
+  version: 26.4.1.dev3218+gf839e81b
   sha256: f0070a5ae1f7957e8ed16a9a8e451dc47af25af14056a52bea18969ccdfa3aff
   requires_dist:
   - dask>=2022.1.0
@@ -13111,7 +13111,7 @@ packages:
   requires_python: '>=3.11'
 - pypi: ./packages/essnmx
   name: essnmx
-  version: 26.4.1.dev3194+g415a48216.d20260505
+  version: 26.4.1.dev3218+gf839e81b
   sha256: 55671f87213d0cad915b5def554cb8380e6bcc8f2a0af5acbcdc8a8ebcfd9531
   requires_dist:
   - dask>=2022.1.0
@@ -13161,14 +13161,14 @@ packages:
   requires_python: '>=3.11'
 - pypi: ./packages/essreduce
   name: essreduce
-  version: 26.4.2.dev1131+g415a48216.d20260505
-  sha256: 4abbc4045bccda954282bb39956f775e74f753431168e2fb3a204e4c3bf5f9f8
+  version: 26.4.2.dev1163+g351a7760.d20260508
+  sha256: 9511776fdf3c7a1d1df51683a8404f9427cb5545e06161a08cf63642e4391251
   requires_dist:
   - dask>=2022.1.0
   - graphviz>=0.20
   - sciline>=25.11.0
   - scipp>=26.3.1
-  - scippneutron>=25.11.1
+  - scippneutron>=26.5.0
   - scippnexus>=25.6.0
   - scipy>=1.14
   - ipywidgets>=8.1 ; extra == 'test'
@@ -13198,8 +13198,8 @@ packages:
   requires_python: '>=3.11'
 - pypi: ./packages/essreflectometry
   name: essreflectometry
-  version: 26.5.1.dev3+g415a48216.d20260505
-  sha256: 8ab84bdb7607fb1f62917c30c4d4165aae50a4c20b77d4aaba6e556876a9f532
+  version: 26.5.2.dev25+gf839e81b
+  sha256: 5bf2d2cf5ece7c40301c8790fe613d3f95aeb0c991b6bf45744caadaed4c4fb0
   requires_dist:
   - dask>=2022.1.0
   - python-dateutil
@@ -13240,8 +13240,8 @@ packages:
   requires_python: '>=3.11'
 - pypi: ./packages/esssans
   name: esssans
-  version: 26.4.1.dev4386+g415a48216.d20260505
-  sha256: fb92b8fbde072b0cb7861029be6ffdd4d7b42c8d6a278c6a4db77db515a4dedc
+  version: 26.4.1.dev4410+gf839e81b
+  sha256: cbcc77a9f6a13766e6845bfff61c656b99d1b1691b1fac2030c6d1da6e0cc08f
   requires_dist:
   - dask>=2022.1.0
   - graphviz>=0.20
@@ -17702,20 +17702,21 @@ packages:
   version: 4.9.4
   sha256: 68a9a4619a666ea6439f2ff250c12a853cd1cbd5158d258bd824a7df6be2f868
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/31/8b/9e8baf7dacac8d0c174925c38ff43c6d94bc9abb35503f67762caccb6869/plopp-26.3.1-py3-none-any.whl
+- pypi: https://files.pythonhosted.org/packages/e4/bc/daa30c02069eeac5b9198985ba42f5d65ca71bed6705b18329e51d352b7c/plopp-26.4.2-py3-none-any.whl
   name: plopp
-  version: 26.3.1
-  sha256: 56531f2f71fa4f7f33c172312d2423d969deb9b9dd29b2524ad3ed7e33d220eb
+  version: 26.4.2
+  sha256: 5cab99bb0905ce08a1d1d7d82f0f64cee7d594269ec1bd01a8a361bd14ab7bff
   requires_dist:
   - lazy-loader>=0.4
   - matplotlib>=3.8
-  - scipp>=25.5.0 ; extra == 'scipp'
-  - scipp>=25.5.0 ; extra == 'all'
+  - scipp>=25.8.0 ; extra == 'scipp'
+  - plopp[scipp] ; extra == 'all'
   - ipympl>0.8.4 ; extra == 'all'
   - pythreejs>=2.4.1 ; extra == 'all'
   - mpltoolbox>=24.6.0 ; extra == 'all'
   - ipywidgets>=8.1.0 ; extra == 'all'
   - graphviz>=0.20.3 ; extra == 'all'
+  - plopp[scipp] ; extra == 'test'
   - graphviz>=0.20.3 ; extra == 'test'
   - h5py>=3.12 ; extra == 'test'
   - ipympl>=0.8.4 ; extra == 'test'
@@ -17728,7 +17729,6 @@ packages:
   - pyarrow>=13.0.0 ; extra == 'test'
   - pytest>=8.0 ; extra == 'test'
   - pythreejs>=2.4.1 ; extra == 'test'
-  - scipp>=25.5.0 ; extra == 'test'
   - scipy>=1.10.0 ; extra == 'test'
   - xarray>=2024.5.0 ; extra == 'test'
   - anywidget>=0.9.0 ; extra == 'test'
@@ -18671,10 +18671,10 @@ packages:
   - nodejs ; extra == 'all'
   - pythreejs ; extra == 'all'
   requires_python: '>=3.11'
-- pypi: https://files.pythonhosted.org/packages/fb/46/e50b38629e9e3f4a1dd55fb36d8b8abd1d59768c31151c1c8ed696f7b865/scippneutron-26.3.0-py3-none-any.whl
+- pypi: https://files.pythonhosted.org/packages/63/9f/724f66a48309dd97a2ff58f491d6ffd925f35d1278a5e55dc9a5ac6a156b/scippneutron-26.5.0-py3-none-any.whl
   name: scippneutron
-  version: 26.3.0
-  sha256: 6bc9e36f68059bb792460cc897e6247236289f170134a953ed9fee8578872dd7
+  version: 26.5.0
+  sha256: e9cfad09b974867c6dc2a175cd2e575e06eaa951b2409e9ef863db237853bf99
   requires_dist:
   - python-dateutil>=2.8
   - email-validator>=2
@@ -18682,12 +18682,12 @@ packages:
   - lazy-loader>=0.4
   - mpltoolbox>=24.6.0
   - numpy>=1.20
-  - plopp>=24.9.1
+  - plopp>=26.4.1
   - pydantic>=2
-  - scipp>=24.7.0
+  - scipp>=25.8.0
   - scippnexus>=23.11.0
   - scipy>=1.7.0
-  - scipp[all]>=23.7.0 ; extra == 'all'
+  - scipp[all]>=25.8.0 ; extra == 'all'
   - pooch>=1.5 ; extra == 'all'
   - hypothesis>=6.100 ; extra == 'test'
   - ipympl>0.9.0 ; extra == 'test'

From be1a386b8e1643f5944b33da28728ffa0889b5e3 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Fri, 8 May 2026 15:11:49 +0200
Subject: [PATCH 13/23] fix NMX tests

---
 packages/essnmx/src/ess/nmx/workflows.py      | 97 ++++++-------------
 packages/essnmx/tests/executable_test.py      |  2 +
 .../essreduce/src/ess/reduce/unwrap/lut.py    |  8 +-
 3 files changed, 39 insertions(+), 68 deletions(-)

diff --git a/packages/essnmx/src/ess/nmx/workflows.py b/packages/essnmx/src/ess/nmx/workflows.py
index cdf6496a2..a3064bc6f 100644
--- a/packages/essnmx/src/ess/nmx/workflows.py
+++ b/packages/essnmx/src/ess/nmx/workflows.py
@@ -5,10 +5,11 @@
 import sciline
 import scipp as sc
 import scippnexus as snx
-import tof
 from scippneutron.conversion.tof import tof_from_wavelength
 
 from ess.reduce.nexus.types import (
+    AnyRun,
+    DiskChoppers,
     EmptyDetector,
     Filename,
     NeXusComponent,
@@ -18,15 +19,13 @@
     SampleRun,
 )
 from ess.reduce.unwrap import (
-    BeamlineComponentReading,
     GenericUnwrapWorkflow,
     LookupTableFilename,
     LookupTableRelativeErrorThreshold,
     LookupTableWorkflow,
     LtotalRange,
-    NumberOfSimulatedNeutrons,
-    SimulationResults,
-    SimulationSeed,
+    SourcePosition,
+    SourcePulse,
     WavelengthDetector,
 )
 from ess.reduce.workflow import register_workflow
@@ -45,60 +44,11 @@
     TofSimulationMaxWavelength: sc.scalar(3.6, unit='angstrom'),
     TofSimulationMinWavelength: sc.scalar(1.8, unit='angstrom'),
     LookupTableRelativeErrorThreshold: {f'detector_panel_{i}': 0.1 for i in range(5)},
+    # TODO: This should become DiskChoppers[RunType] once we add choppers
+    DiskChoppers[AnyRun]: {},
 }
 
 
-def _simulate_fixed_wavelength_tof(
-    wmin: TofSimulationMinWavelength,
-    wmax: TofSimulationMaxWavelength,
-    neutrons: NumberOfSimulatedNeutrons,
-    seed: SimulationSeed,
-) -> SimulationResults:
-    """
-    Simulate a pulse of neutrons propagating through the instrument using the
-    ``tof`` package (https://scipp.github.io/tof/).
-    This runs a simulation assuming there are no choppers in the instrument.
-
-    Parameters
-    ----------
-    wmin:
-        Minimum wavelength of the simulated neutrons.
-    wmax:
-        Maximum wavelength of the simulated neutrons.
-    neutrons:
-        Number of neutrons to simulate.
-    seed:
-        Random seed for the simulation.
-    """
-    source = tof.Source(
-        facility="ess",
-        neutrons=neutrons,
-        pulses=1,
-        seed=seed,
-        wmax=wmax,
-        wmin=wmin,
-    )
-    events = source.data.squeeze().flatten(to="event")
-
-    return SimulationResults(
-        readings={
-            "source": BeamlineComponentReading(
-                time_of_arrival=events.coords["birth_time"],
-                wavelength=events.coords["wavelength"],
-                weight=events.data,
-                distance=source.distance,
-            )
-        },
-        choppers=None,
-    )
-
-
-def _merge_panels(*da: sc.DataArray) -> sc.DataArray:
-    """Merge multiple DataArrays representing different panels into one."""
-    merged = sc.concat(da, dim='panel')
-    return merged
-
-
 def select_detector_names(*, detector_ids: Iterable[int] = (0, 1, 2)):
     import os
 
@@ -259,15 +209,32 @@ def compute_detector_tof(da: WavelengthDetector[RunType]) -> TofDetector[RunType
     )
 
 
+def _source_position_to_SourcePosition(
+    source_position: Position[snx.NXsource, SampleRun],
+) -> SourcePosition:
+    """
+    This is a temporary provider to convert the source position from the Nexus file to
+    the SourcePosition type used in the unwrapping workflow.
+    In the next iteration, we will directly use the source position from the Nexus file
+    in the unwrapping workflow and remove this provider.
+    """
+    return SourcePosition(source_position)
+
+
 @register_workflow
 def NMXWorkflow() -> sciline.Pipeline:
     generic_wf = GenericUnwrapWorkflow(run_types=[SampleRun], monitor_types=[])
 
-    generic_wf.insert(_retrieve_crystal_rotation)
-    generic_wf.insert(assemble_sample_metadata)
-    generic_wf.insert(assemble_source_metadata)
-    generic_wf.insert(assemble_detector_metadata)
-    generic_wf.insert(compute_detector_tof)
+    for provider in (
+        _retrieve_crystal_rotation,
+        assemble_sample_metadata,
+        assemble_source_metadata,
+        assemble_detector_metadata,
+        compute_detector_tof,
+        _source_position_to_SourcePosition,
+    ):
+        generic_wf.insert(provider)
+
     for key, value in default_parameters.items():
         generic_wf[key] = value
 
@@ -317,12 +284,12 @@ def initialize_nmx_workflow(*, config: WorkflowConfig) -> sciline.Pipeline:
         wf[LookupTableFilename] = config.lookup_table_file_path
     else:
         wf = _merge_workflows(base_wf=wf, merged_wf=LookupTableWorkflow())
-        wf.insert(_simulate_fixed_wavelength_tof)
         wmax = sc.scalar(config.tof_simulation_max_wavelength, unit='angstrom')
         wmin = sc.scalar(config.tof_simulation_min_wavelength, unit='angstrom')
-        wf[TofSimulationMaxWavelength] = wmax
-        wf[TofSimulationMinWavelength] = wmin
-        wf[SimulationSeed] = config.tof_simulation_seed
+        wf[SourcePulse] = SourcePulse(
+            time=(sc.scalar(0.0, unit='ms'), sc.scalar(5.0, unit='ms')),
+            wavelength=(wmin, wmax),
+        )
         ltotal_min = sc.scalar(value=config.tof_simulation_min_ltotal, unit='m')
         ltotal_max = sc.scalar(value=config.tof_simulation_max_ltotal, unit='m')
         wf[LtotalRange] = LtotalRange((ltotal_min, ltotal_max))
diff --git a/packages/essnmx/tests/executable_test.py b/packages/essnmx/tests/executable_test.py
index fa8ed8621..551b009a1 100644
--- a/packages/essnmx/tests/executable_test.py
+++ b/packages/essnmx/tests/executable_test.py
@@ -25,6 +25,7 @@
 from ess.nmx.configurations import TimeBinCoordinate, TimeBinUnit, to_command_arguments
 from ess.nmx.executables import reduction
 from ess.nmx.types import Compression, NMXLauetof
+from ess.reduce.unwrap.types import SourcePosition
 
 
 def _build_arg_list_from_pydantic_instance(*instances: pydantic.BaseModel) -> list[str]:
@@ -410,6 +411,7 @@ def lut_file_path(tmp_path: pathlib.Path):
 
     # Simply use the default workflow for testing.
     workflow = initialize_nmx_workflow(config=WorkflowConfig())
+    workflow[SourcePosition] = sc.vector([0, 0, 0], unit='m')
     lut: LookupTable = workflow.compute(LookupTable)
 
     # Change the tof range a bit for testing.
diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index 587d56fa2..d793602e3 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -87,7 +87,7 @@ def _polygon_intersections(polygons: list[np.ndarray], xs: np.ndarray) -> np.nda
         y_min = np.nanmin(y, axis=0)
         y_max = np.nanmax(y, axis=0)
 
-    # Value and spread estimate
+    # Median value and spread estimate
     return 0.5 * (y_min + y_max), 0.5 * (y_max - y_min)
 
 
@@ -198,7 +198,9 @@ def compute_frame_sequence(
 
     chops = {
         key: chopper_cascade.Chopper(
-            distance=(ch.axle_position - source_position).fields.z,
+            distance=sc.norm(
+                ch.axle_position - source_position.to(unit=ch.axle_position.unit)
+            ),
             time_open=ch.time_offset_open(
                 pulse_frequency=frequency_for_chopper_rotation
             ),
@@ -292,7 +294,7 @@ def make_wavelength_lookup_table(
 
     pieces = []
     # To avoid large RAM usage, and having to split the distances into chunks
-    # according to which component reading to use, we simply loop over distances one
+    # according to which frame to use, we simply loop over distances one
     # by one here.
     for dist in distances:
         # Find the correct simulation reading

From 0367b6490fe2f1cb0c6b336702607b98c91ad49c Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Fri, 8 May 2026 15:15:40 +0200
Subject: [PATCH 14/23] do not test for choppers until we know what to do

---
 packages/essreduce/src/ess/reduce/unwrap/lut.py  | 1 +
 packages/essreduce/tests/unwrap/workflow_test.py | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/packages/essreduce/src/ess/reduce/unwrap/lut.py b/packages/essreduce/src/ess/reduce/unwrap/lut.py
index d793602e3..648d371b8 100644
--- a/packages/essreduce/src/ess/reduce/unwrap/lut.py
+++ b/packages/essreduce/src/ess/reduce/unwrap/lut.py
@@ -334,6 +334,7 @@ def make_wavelength_lookup_table(
         distance_resolution=table.coords["distance"][1] - table.coords["distance"][0],
         time_resolution=table.coords["event_time_offset"][1]
         - table.coords["event_time_offset"][0],
+        # TODO: Do we still want to store the chopper information in the lookup table?
     )
 
 
diff --git a/packages/essreduce/tests/unwrap/workflow_test.py b/packages/essreduce/tests/unwrap/workflow_test.py
index 890166a2f..ddf2323ca 100644
--- a/packages/essreduce/tests/unwrap/workflow_test.py
+++ b/packages/essreduce/tests/unwrap/workflow_test.py
@@ -89,7 +89,7 @@ def test_LookupTableWorkflow_can_compute_lut():
     assert lut.time_resolution is not None
     assert lut.pulse_stride is not None
     assert lut.pulse_period is not None
-    assert lut.choppers is not None
+    # assert lut.choppers is not None
 
 
 def test_GenericUnwrapWorkflow_with_lut_from_tof_simulation(workflow):

From 63cbd9f35f89640239bd936930f9aa6e2607a440 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 10:07:51 +0200
Subject: [PATCH 15/23] update dream notebook

---
 .../docs/user-guide/unwrap/dream.ipynb        | 95 +++++++++++--------
 1 file changed, 57 insertions(+), 38 deletions(-)

diff --git a/packages/essreduce/docs/user-guide/unwrap/dream.ipynb b/packages/essreduce/docs/user-guide/unwrap/dream.ipynb
index 1404b5b7f..7ddda6323 100644
--- a/packages/essreduce/docs/user-guide/unwrap/dream.ipynb
+++ b/packages/essreduce/docs/user-guide/unwrap/dream.ipynb
@@ -327,7 +327,7 @@
    "source": [
     "### Building the wavelength lookup table\n",
     "\n",
-    "We use the [Tof](https://scipp.github.io/tof/) package to propagate a pulse of neutrons through the chopper system to the detectors,\n",
+    "We use [`scippneutron.tof.chopper_cascade`](https://scipp.github.io/scippneutron/user-guide/chopper/chopper-cascade.html) module to propagate a pulse of neutrons through the chopper system to the detectors,\n",
     "and predict the most likely neutron wavelength for a given time-of-arrival and distance from source.\n",
     "\n",
     "From this,\n",
@@ -358,10 +358,10 @@
    "source": [
     "### Inspecting the lookup table\n",
     "\n",
-    "The workflow first runs a simulation using the chopper parameters above,\n",
-    "and the result is stored in `SimulationResults` (see graph above).\n",
+    "The workflow first runs a calculation propagating a pulse of neutrons (represented by a polygon in time and wavelength space),\n",
+    "through a chopper cascade defined by the chopper parameters above.\n",
     "\n",
-    "From these simulated neutrons, we create a figure displaying the neutron wavelengths,\n",
+    "This can be used to create a figure displaying the neutron wavelengths,\n",
     "as a function of arrival time at the detector.\n",
     "\n",
     "This is the basis for creating our lookup table."
@@ -370,53 +370,69 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "25",
+   "id": "6f82c864-e33b-4d04-b3ca-a201eec46222",
    "metadata": {},
    "outputs": [],
    "source": [
-    "sim = lut_wf.compute(SimulationResults)\n",
+    "dist = sc.scalar(60.0, unit='m')\n",
     "\n",
-    "\n",
-    "def to_event_time_offset(sim):\n",
-    "    # Compute event_time_offset at the detector\n",
-    "    eto = (\n",
-    "        sim.time_of_arrival\n",
-    "        + ((lut_wf.compute(LtotalRange)[1] - sim.distance) / sim.speed).to(unit=\"us\")\n",
-    "    ) % sc.scalar(1e6 / 14.0, unit=\"us\")\n",
-    "    # # Compute time-of-flight at the detector\n",
-    "    # tof = (Ltotal / sim.speed).to(unit=\"us\")\n",
-    "    return sc.DataArray(\n",
-    "        data=sim.weight,\n",
-    "        coords={\"wavelength\": sim.wavelength, \"event_time_offset\": eto},\n",
-    "    )\n",
-    "\n",
-    "\n",
-    "events = to_event_time_offset(sim.readings[\"t0\"])\n",
-    "fig = events.hist(wavelength=300, event_time_offset=300).plot(norm=\"log\")\n",
-    "fig"
+    "frames = lut_wf.compute(ChopperFrameSequence)\n",
+    "at_detector = frames.propagate_to(dist)\n",
+    "fig, ax = at_detector.draw()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "26",
+   "id": "378df191-0f21-456b-9a6f-157479d83b24",
    "metadata": {},
    "source": [
-    "The lookup table is then obtained by computing the weighted mean of the wavelength inside each time-of-arrival bin.\n",
+    "The source pulse is defined as spanning 0-5 ms in time, and 0-15 Å in wavelength,\n",
+    "and is represented by the blue rectangle on the left hand side of the diagram.\n",
     "\n",
-    "This is illustrated by the orange line in the figure below:"
+    "As the pulse propagates through the system,\n",
+    "it stretches (slow neutrons take longer to reach the same distance) and gets chopped by the chopper openings,\n",
+    "creating polygons from the rectangular pulse.\n",
+    "\n",
+    "Finally, at the detector distance of 60 m, we are left with two (pink) very thin polygons,\n",
+    "representing the two packets of neutrons that are allowed through the instrument.\n",
+    "\n",
+    "The idea is to approximate these thin polygons as a single line,\n",
+    "effectively giving us a function relating neutron wavelength as a function of arrival time.\n",
+    "This is precisely how the loop table is built,\n",
+    "and if we overlay the wavelength values given by the table at a distance of 60 m,\n",
+    "we see that the black lines pass right in the middle of the polygons."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "27",
+   "id": "eed14ca5-fbbb-4ac8-b288-a04793b73f50",
    "metadata": {},
    "outputs": [],
    "source": [
     "table = lut_wf.compute(LookupTable)\n",
     "\n",
-    "# Overlay mean on the figure above\n",
-    "table.array[\"distance\", -1].plot(ax=fig.ax, color=\"C1\", ls=\"-\", marker=None)"
+    "# Overlay LUT prediction on the polygons figure\n",
+    "da = table.array[\"distance\", 352]\n",
+    "ax.plot(\n",
+    "    da.coords['event_time_offset'].values / 1000,\n",
+    "    da.values,\n",
+    "    color=\"k\",\n",
+    "    ls=\"-\",\n",
+    "    marker=None,\n",
+    ")\n",
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "daeeef2d-79d8-4dc7-84fc-5c6b75cee436",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax.set(xlim=[39.5, 41.5], ylim=[2.6, 2.72])\n",
+    "fig"
    ]
   },
   {
@@ -490,7 +506,8 @@
     "    {\n",
     "        \"wfm\": histogrammed,\n",
     "        \"ground_truth\": ground_truth.hist(wavelength=edges),\n",
-    "    }\n",
+    "    },\n",
+    "    color={\"ground_truth\": \"k\"},\n",
     ")"
    ]
   },
@@ -589,7 +606,8 @@
     "            \"wfm\": wav_wfm[\"detector_number\", i].bins.concat().hist(wavelength=edges),\n",
     "            \"ground_truth\": ground_truth[i].hist(wavelength=edges),\n",
     "        },\n",
-    "        title=f\"Pixel {i + 1}\",\n",
+    "        title=f\"detector_number {i}\",\n",
+    "        color={\"ground_truth\": \"k\", \"wfm\": f\"C{i}\"},\n",
     "    )\n",
     "    for i in range(len(Ltotal))\n",
     "]\n",
@@ -669,10 +687,10 @@
     "# Update workflow\n",
     "lut_wf[DiskChoppers[AnyRun]] = disk_choppers\n",
     "\n",
-    "sim = lut_wf.compute(SimulationResults)\n",
-    "\n",
-    "events = to_event_time_offset(sim.readings[\"t0\"])\n",
-    "events.hist(wavelength=300, event_time_offset=300).plot(norm=\"log\")"
+    "frames = lut_wf.compute(ChopperFrameSequence)\n",
+    "at_detector = frames.propagate_to(dist)\n",
+    "fig, ax = at_detector.draw()\n",
+    "ax.set(xlim=(36, 44), ylim=(2, 3))"
    ]
   },
   {
@@ -727,7 +745,7 @@
    "source": [
     "wf[LookupTable] = table\n",
     "\n",
-    "wf[LookupTableRelativeErrorThreshold] = {'dream_detector': 0.01}\n",
+    "wf[LookupTableRelativeErrorThreshold] = {'dream_detector': 0.02}\n",
     "\n",
     "masked_table = wf.compute(ErrorLimitedLookupTable[snx.NXdetector])\n",
     "masked_table.plot(ymin=65)"
@@ -768,7 +786,8 @@
     "    {\n",
     "        \"wfm\": wav_wfm.hist(wavelength=edges).squeeze(),\n",
     "        \"ground_truth\": ground_truth.hist(wavelength=edges),\n",
-    "    }\n",
+    "    },\n",
+    "    color={\"ground_truth\": \"k\"},\n",
     ")"
    ]
   }

From ae42967539be49f1288b0b3a344c238a9520ebf4 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 10:22:00 +0200
Subject: [PATCH 16/23] update frame unwrapping notebook

---
 .../docs/user-guide/unwrap/frame-unwrapping.ipynb   | 13 ++++++-------
 1 file changed, 6 insertions(+), 7 deletions(-)

diff --git a/packages/essreduce/docs/user-guide/unwrap/frame-unwrapping.ipynb b/packages/essreduce/docs/user-guide/unwrap/frame-unwrapping.ipynb
index 2cad4d856..b46037542 100644
--- a/packages/essreduce/docs/user-guide/unwrap/frame-unwrapping.ipynb
+++ b/packages/essreduce/docs/user-guide/unwrap/frame-unwrapping.ipynb
@@ -181,8 +181,8 @@
     "\n",
     "The chopper information is used to construct a lookup table that provides an estimate of the neutron wavelength as a function of time-of-arrival.\n",
     "\n",
-    "The [Tof](https://scipp.github.io/tof/) package can be used to propagate a pulse of neutrons through the chopper system to the detectors,\n",
-    "and predict the most likely neutron wavelength for a given time-of-arrival.\n",
+    "We use [`scippneutron.tof.chopper_cascade`](https://scipp.github.io/scippneutron/user-guide/chopper/chopper-cascade.html) module to propagate a pulse of neutrons through the chopper system to the detectors,\n",
+    "and predict the most likely neutron wavelength for a given time-of-arrival and distance from source.\n",
     "More advanced programs such as McStas can of course also be used for even better results.\n",
     "\n",
     "We typically have hundreds of thousands of pixels in an instrument,\n",
@@ -194,10 +194,9 @@
     "\n",
     "To create the table, we thus:\n",
     "\n",
-    "- run a simulation where a pulse of neutrons passes through the choppers and reaches the sample (or any location after the last chopper)\n",
-    "- propagate the neutrons from the sample to a range of distances that span the minimum and maximum pixel distance from the sample (assuming neutron wavelengths do not change)\n",
-    "- bin the neutrons in both distance and time-of-arrival (yielding a 2D binned data array)\n",
-    "- compute the (weighted) mean wavelength inside each bin to give our final lookup table\n",
+    "- run a calculation where a pulse of neutrons passes through the choppers and reaches the sample and detectors\n",
+    "- along the way, at regular intervals (defined by a `DistanceResolution`), extract the current state of the pulse of neutrons\n",
+    "- given number of arrival time bins (defined by a `TimeResolution`), compute the most likely (median or weighted mean) wavelength inside each arrival time bin\n",
     "\n",
     "This is done using a dedicated workflow:"
    ]
@@ -296,7 +295,7 @@
     ")\n",
     "wavs[\"true\"] = ground_truth\n",
     "\n",
-    "pp.plot(wavs)"
+    "pp.plot(wavs, color={\"true\": \"k\"})"
    ]
   },
   {

From 13dc0c7e0d2893e45198918f3afd457ab56f4751 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 11:05:43 +0200
Subject: [PATCH 17/23] merge dream and wfm ntoebooks

---
 .../docs/user-guide/unwrap/wfm.ipynb          | 775 ++++++++++++++----
 1 file changed, 600 insertions(+), 175 deletions(-)

diff --git a/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb b/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
index da09bb10d..6d5086052 100644
--- a/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
+++ b/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
@@ -5,12 +5,13 @@
    "id": "0",
    "metadata": {},
    "source": [
-    "# Wavelength frame multiplication\n",
+    "# The DREAM chopper cascade\n",
     "\n",
-    "Wavelength frame multiplication (WFM) is a technique commonly used at long-pulse facilities to improve the resolution of the results measured at the neutron detectors.\n",
-    "See for example the article by [Schmakat et al. (2020)](https://doi.org/10.1016/j.nima.2020.164467) for a description of how WFM works.\n",
+    "In this notebook, we simulate the beamline of the DREAM instrument and its pulse-shaping choppers.\n",
+    "We then show how to use `essreduce`'s `unwrap` module to compute neutron wavelengths from their arrival times at the detectors.\n",
     "\n",
-    "In this notebook, we show how to use `essreduce`'s `unwrap` module to compute an accurate wavelength coordinate for neutrons travelling through a WFM beamline."
+    "The case of DREAM is interesting because the pulse-shaping choppers can be used in a number of different modes,\n",
+    "and the number of cutouts the choppers have typically does not equal the number of frames observed at the detectors."
    ]
   },
   {
@@ -20,7 +21,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import numpy as np\n",
     "import plopp as pp\n",
     "import scipp as sc\n",
     "import scippnexus as snx\n",
@@ -41,15 +41,12 @@
     "We begin by defining the chopper settings for our beamline.\n",
     "In principle, the chopper setting could simply be read from a NeXus file.\n",
     "\n",
-    "For this example, we create choppers modeled on the [V20 ESS beamline at HZB](https://doi.org/10.1016/j.nima.2016.09.034).\n",
-    "It consists of 5 choppers:\n",
+    "The DREAM instrument has\n",
     "\n",
-    "- 2 WFM choppers\n",
-    "- 2 frame-overlap choppers\n",
-    "- 1 pulse-overlap chopper\n",
-    "\n",
-    "The first 4 choppers have 6 openings (also known as cutouts),\n",
-    "while the last one only has a single opening."
+    "- 2 pulse-shaping choppers (PSC)\n",
+    "- 1 overlap chopper (OC)\n",
+    "- 1 band-control chopper (BCC)\n",
+    "- 1 T0 chopper"
    ]
   },
   {
@@ -59,102 +56,78 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "wfm1 = DiskChopper(\n",
-    "    frequency=sc.scalar(-70.0, unit=\"Hz\"),\n",
+    "psc1 = DiskChopper(\n",
+    "    frequency=sc.scalar(14.0, unit=\"Hz\"),\n",
     "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(-47.10, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, 6.6], unit=\"m\"),\n",
+    "    phase=sc.scalar(286 - 180, unit=\"deg\"),\n",
+    "    axle_position=sc.vector(value=[0, 0, -70.405], unit=\"m\"),\n",
     "    slit_begin=sc.array(\n",
     "        dims=[\"cutout\"],\n",
-    "        values=np.array([83.71, 140.49, 193.26, 242.32, 287.91, 330.3]) + 15.0,\n",
+    "        values=[-1.23, 70.49, 84.765, 113.565, 170.29, 271.635, 286.035, 301.17],\n",
     "        unit=\"deg\",\n",
     "    ),\n",
     "    slit_end=sc.array(\n",
     "        dims=[\"cutout\"],\n",
-    "        values=np.array([94.7, 155.79, 212.56, 265.33, 314.37, 360.0]) + 15.0,\n",
+    "        values=[1.23, 73.51, 88.035, 116.835, 175.31, 275.565, 289.965, 303.63],\n",
     "        unit=\"deg\",\n",
     "    ),\n",
     "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
     "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
     ")\n",
     "\n",
-    "wfm2 = DiskChopper(\n",
-    "    frequency=sc.scalar(-70.0, unit=\"Hz\"),\n",
+    "psc2 = DiskChopper(\n",
+    "    frequency=sc.scalar(-14.0, unit=\"Hz\"),\n",
     "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(-76.76, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, 7.1], unit=\"m\"),\n",
+    "    phase=sc.scalar(-236, unit=\"deg\"),\n",
+    "    axle_position=sc.vector(value=[0, 0, -70.395], unit=\"m\"),\n",
     "    slit_begin=sc.array(\n",
     "        dims=[\"cutout\"],\n",
-    "        values=np.array([65.04, 126.1, 182.88, 235.67, 284.73, 330.32]) + 15.0,\n",
+    "        values=[-1.23, 27.0, 55.8, 142.385, 156.765, 214.115, 257.23, 315.49],\n",
     "        unit=\"deg\",\n",
     "    ),\n",
     "    slit_end=sc.array(\n",
     "        dims=[\"cutout\"],\n",
-    "        values=np.array([76.03, 141.4, 202.18, 254.97, 307.74, 360.0]) + 15.0,\n",
+    "        values=[1.23, 30.6, 59.4, 145.615, 160.035, 217.885, 261.17, 318.11],\n",
     "        unit=\"deg\",\n",
     "    ),\n",
     "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
     "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
     ")\n",
     "\n",
-    "foc1 = DiskChopper(\n",
-    "    frequency=sc.scalar(-56.0, unit=\"Hz\"),\n",
+    "oc = DiskChopper(\n",
+    "    frequency=sc.scalar(14.0, unit=\"Hz\"),\n",
     "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(-62.40, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, 8.8], unit=\"m\"),\n",
-    "    slit_begin=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=np.array([74.6, 139.6, 194.3, 245.3, 294.8, 347.2]),\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
-    "    slit_end=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=np.array([95.2, 162.8, 216.1, 263.1, 310.5, 371.6]),\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
+    "    phase=sc.scalar(297 - 180 - 90, unit=\"deg\"),\n",
+    "    axle_position=sc.vector(value=[0, 0, -70.376], unit=\"m\"),\n",
+    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-27.6 * 0.5], unit=\"deg\"),\n",
+    "    slit_end=sc.array(dims=[\"cutout\"], values=[27.6 * 0.5], unit=\"deg\"),\n",
     "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
     "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
     ")\n",
     "\n",
-    "foc2 = DiskChopper(\n",
-    "    frequency=sc.scalar(-28.0, unit=\"Hz\"),\n",
+    "bcc = DiskChopper(\n",
+    "    frequency=sc.scalar(112.0, unit=\"Hz\"),\n",
     "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(-12.27, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, 15.9], unit=\"m\"),\n",
-    "    slit_begin=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=np.array([98.0, 154.0, 206.8, 255.0, 299.0, 344.65]),\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
-    "    slit_end=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=np.array([134.6, 190.06, 237.01, 280.88, 323.56, 373.76]),\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
+    "    phase=sc.scalar(240 - 180, unit=\"deg\"),\n",
+    "    axle_position=sc.vector(value=[0, 0, -66.77], unit=\"m\"),\n",
+    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-36.875, 143.125], unit=\"deg\"),\n",
+    "    slit_end=sc.array(dims=[\"cutout\"], values=[36.875, 216.875], unit=\"deg\"),\n",
     "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
     "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
     ")\n",
     "\n",
-    "pol = DiskChopper(\n",
-    "    frequency=sc.scalar(-14.0, unit=\"Hz\"),\n",
+    "t0 = DiskChopper(\n",
+    "    frequency=sc.scalar(28.0, unit=\"Hz\"),\n",
     "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, 17.0], unit=\"m\"),\n",
-    "    slit_begin=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=np.array([40.0]),\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
-    "    slit_end=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=np.array([240.0]),\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
+    "    phase=sc.scalar(280 - 180, unit=\"deg\"),\n",
+    "    axle_position=sc.vector(value=[0, 0, -63.5], unit=\"m\"),\n",
+    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-314.9 * 0.5], unit=\"deg\"),\n",
+    "    slit_end=sc.array(dims=[\"cutout\"], values=[314.9 * 0.5], unit=\"deg\"),\n",
     "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
     "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
     ")\n",
     "\n",
-    "disk_choppers = {\"wfm1\": wfm1, \"wfm2\": wfm2, \"foc1\": foc1, \"foc2\": foc2, \"pol\": pol}"
+    "disk_choppers = {\"psc1\": psc1, \"psc2\": psc2, \"oc\": oc, \"bcc\": bcc, \"t0\": t0}"
    ]
   },
   {
@@ -172,7 +145,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "wfm1"
+    "psc2"
    ]
   },
   {
@@ -180,8 +153,7 @@
    "id": "6",
    "metadata": {},
    "source": [
-    "Define the source position which is required to compute the distance that neutrons travelled.\n",
-    "In this example, chopper positions are given relative to the source, so we set the source position to the origin."
+    "Define the source position which is required to compute the distance that neutrons travelled."
    ]
   },
   {
@@ -191,7 +163,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "source_position = sc.vector([0, 0, 0], unit=\"m\")"
+    "source_position = sc.vector([0, 0, -76.55], unit=\"m\")"
    ]
   },
   {
@@ -199,9 +171,7 @@
    "id": "8",
    "metadata": {},
    "source": [
-    "### Adding a detector\n",
-    "\n",
-    "We also have a detector, which we place 26 meters away from the source."
+    "### Adding a detector"
    ]
   },
   {
@@ -211,7 +181,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Ltotal = sc.scalar(26.0, unit=\"m\")"
+    "Ltotal = sc.scalar(76.55 + 1.125, unit=\"m\")"
    ]
   },
   {
@@ -237,7 +207,7 @@
     "    choppers=disk_choppers,\n",
     "    source_position=source_position,\n",
     "    monitors={\"detector\": Ltotal},\n",
-    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 14,\n",
+    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 4,\n",
     "    events_per_pulse=200_000,\n",
     ")"
    ]
@@ -262,9 +232,19 @@
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "id": "14",
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "ess_beamline.model_result.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "15",
+   "metadata": {},
    "source": [
     "From this fake beamline, we extract the raw neutron signal at our detector:"
    ]
@@ -272,7 +252,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "15",
+   "id": "16",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -284,7 +264,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "16",
+   "id": "17",
    "metadata": {},
    "source": [
     "The total number of neutrons in our sample data that make it through to the detector is:"
@@ -293,7 +273,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "17",
+   "id": "18",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -302,7 +282,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "18",
+   "id": "19",
    "metadata": {},
    "source": [
     "## Computing neutron wavelengths\n",
@@ -315,7 +295,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "19",
+   "id": "20",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -323,14 +303,15 @@
     "\n",
     "wf[RawDetector[SampleRun]] = raw_data\n",
     "wf[DetectorLtotal[SampleRun]] = Ltotal\n",
-    "wf[NeXusDetectorName] = \"detector\"\n",
+    "wf[NeXusDetectorName] = 'dream_detector'\n",
+    "wf[LookupTableRelativeErrorThreshold] = {'dream_detector': float(\"inf\")}\n",
     "\n",
     "wf.visualize(WavelengthDetector[SampleRun])"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "20",
+   "id": "21",
    "metadata": {},
    "source": [
     "By default, the workflow tries to load a `LookupTable` from a file.\n",
@@ -341,12 +322,12 @@
   },
   {
    "cell_type": "markdown",
-   "id": "21",
+   "id": "22",
    "metadata": {},
    "source": [
     "### Building the wavelength lookup table\n",
     "\n",
-    "We use the [Tof](https://scipp.github.io/tof/) package to propagate a pulse of neutrons through the chopper system to the detectors,\n",
+    "We use [`scippneutron.tof.chopper_cascade`](https://scipp.github.io/scippneutron/user-guide/chopper/chopper-cascade.html) module to propagate a pulse of neutrons through the chopper system to the detectors,\n",
     "and predict the most likely neutron wavelength for a given time-of-arrival and distance from source.\n",
     "\n",
     "From this,\n",
@@ -356,28 +337,31 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "22",
+   "id": "23",
    "metadata": {},
    "outputs": [],
    "source": [
     "lut_wf = LookupTableWorkflow()\n",
     "lut_wf[DiskChoppers[AnyRun]] = disk_choppers\n",
     "lut_wf[SourcePosition] = source_position\n",
-    "lut_wf[LtotalRange] = sc.scalar(5, unit='m'), sc.scalar(35, unit='m')\n",
+    "lut_wf[LtotalRange] = (\n",
+    "    sc.scalar(25.0, unit=\"m\"),\n",
+    "    sc.scalar(80.0, unit=\"m\"),\n",
+    ")\n",
     "lut_wf.visualize(LookupTable)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "23",
+   "id": "24",
    "metadata": {},
    "source": [
     "### Inspecting the lookup table\n",
     "\n",
-    "The workflow first runs a simulation using the chopper parameters above,\n",
-    "and the result is stored in `SimulationResults` (see graph above).\n",
+    "The workflow first runs a calculation propagating a pulse of neutrons (represented by a polygon in time and wavelength space),\n",
+    "through a chopper cascade defined by the chopper parameters above.\n",
     "\n",
-    "From these simulated neutrons, we create a figure displaying the neutron wavelengths,\n",
+    "This can be used to create a figure displaying the neutron wavelengths,\n",
     "as a function of arrival time at the detector.\n",
     "\n",
     "This is the basis for creating our lookup table."
@@ -386,205 +370,646 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "24",
+   "id": "6f82c864-e33b-4d04-b3ca-a201eec46222",
    "metadata": {},
    "outputs": [],
    "source": [
-    "sim = lut_wf.compute(SimulationResults)\n",
+    "dist = sc.scalar(60.0, unit='m')\n",
     "\n",
+    "frames = lut_wf.compute(ChopperFrameSequence)\n",
+    "at_detector = frames.propagate_to(dist)\n",
+    "fig, ax = at_detector.draw()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "378df191-0f21-456b-9a6f-157479d83b24",
+   "metadata": {},
+   "source": [
+    "The source pulse is defined as spanning 0-5 ms in time, and 0-15 Å in wavelength,\n",
+    "and is represented by the blue rectangle on the left hand side of the diagram.\n",
     "\n",
-    "def to_event_time_offset(sim):\n",
-    "    # Compute event_time_offset at the detector\n",
-    "    eto = (\n",
-    "        sim.time_of_arrival + ((Ltotal - sim.distance) / sim.speed).to(unit=\"us\")\n",
-    "    ) % sc.scalar(1e6 / 14.0, unit=\"us\")\n",
-    "    # Compute time-of-flight at the detector\n",
-    "    tof = (Ltotal / sim.speed).to(unit=\"us\")\n",
-    "    return sc.DataArray(\n",
-    "        data=sim.weight,\n",
-    "        coords={\"wavelength\": sim.wavelength, \"event_time_offset\": eto, \"tof\": tof},\n",
-    "    )\n",
+    "As the pulse propagates through the system,\n",
+    "it stretches (slow neutrons take longer to reach the same distance) and gets chopped by the chopper openings,\n",
+    "creating polygons from the rectangular pulse.\n",
+    "\n",
+    "Finally, at the detector distance of 60 m, we are left with two (pink) very thin polygons,\n",
+    "representing the two packets of neutrons that are allowed through the instrument.\n",
     "\n",
+    "The idea is to approximate these thin polygons as a single line,\n",
+    "effectively giving us a function relating neutron wavelength as a function of arrival time.\n",
+    "This is precisely how the loop table is built,\n",
+    "and if we overlay the wavelength values given by the table at a distance of 60 m,\n",
+    "we see that the black lines pass right in the middle of the polygons."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eed14ca5-fbbb-4ac8-b288-a04793b73f50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "table = lut_wf.compute(LookupTable)\n",
     "\n",
-    "events = to_event_time_offset(sim.readings[\"pol\"])\n",
-    "fig = events.hist(wavelength=300, event_time_offset=300).plot(norm=\"log\")\n",
+    "# Overlay LUT prediction on the polygons figure\n",
+    "da = table.array[\"distance\", 352]\n",
+    "ax.plot(\n",
+    "    da.coords['event_time_offset'].values / 1000,\n",
+    "    da.values,\n",
+    "    color=\"k\",\n",
+    "    ls=\"-\",\n",
+    "    marker=None,\n",
+    ")\n",
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "daeeef2d-79d8-4dc7-84fc-5c6b75cee436",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax.set(xlim=[39.5, 41.5], ylim=[2.6, 2.72])\n",
     "fig"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "25",
+   "id": "28",
+   "metadata": {},
+   "source": [
+    "The full table covers a range of distances, and looks like"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "29",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "table.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "30",
    "metadata": {},
    "source": [
-    "The lookup table is then obtained by computing the weighted mean of wavelength inside each time-of-arrival bin.\n",
+    "### Computing a wavelength coordinate\n",
     "\n",
-    "This is illustrated by the orange line in the figure below:"
+    "We will now update our workflow, and use it to obtain our event data with a wavelength coordinate:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "26",
+   "id": "31",
    "metadata": {},
    "outputs": [],
    "source": [
-    "table = lut_wf.compute(LookupTable)\n",
+    "# Set the computed lookup table onto the original workflow\n",
+    "wf[LookupTable] = table\n",
     "\n",
-    "# Overlay mean on the figure above\n",
-    "table.array[\"distance\", 212].plot(ax=fig.ax, color=\"C1\", ls=\"-\", marker=None)\n",
+    "# Compute wavelength of neutron events\n",
+    "wavs = wf.compute(WavelengthDetector[SampleRun])\n",
+    "edges = sc.linspace(\"wavelength\", 0.8, 4.6, 201, unit=\"angstrom\")\n",
     "\n",
-    "# Zoom in\n",
-    "fig.canvas.xrange = 40000, 50000\n",
-    "fig.canvas.yrange = 5.5, 7.5\n",
-    "fig"
+    "histogrammed = wavs.hist(wavelength=edges).squeeze()\n",
+    "histogrammed.plot()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "27",
+   "id": "32",
    "metadata": {},
    "source": [
-    "We can see that the orange lines follow the center of the colored areas.\n",
+    "### Comparing to the ground truth\n",
     "\n",
-    "We can also see that in regions where there is contamination from other chopper openings (overlapping regions in time),\n",
-    "the error bars on the orange line get larger.\n",
+    "As a consistency check, because we actually know the wavelengths of the neutrons we created,\n",
+    "we can compare the true neutron wavelengths to those we computed above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "33",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ground_truth = ess_beamline.model_result[\"detector\"].data.flatten(to=\"event\")\n",
+    "ground_truth = ground_truth[~ground_truth.masks[\"blocked_by_others\"]]\n",
+    "\n",
+    "pp.plot(\n",
+    "    {\n",
+    "        \"wfm\": histogrammed,\n",
+    "        \"ground_truth\": ground_truth.hist(wavelength=edges),\n",
+    "    },\n",
+    "    color={\"ground_truth\": \"k\"},\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "34",
+   "metadata": {},
+   "source": [
+    "## Multiple detector pixels\n",
+    "\n",
+    "It is also possible to compute the neutron wavelength for multiple detector pixels at once,\n",
+    "where every pixel has different frame bounds\n",
+    "(because every pixel is at a different distance from the source).\n",
     "\n",
-    "Another way of looking at this is to plot the entire table,\n",
-    "showing the predicted wavelength as a function of `event_time_offset` and distance.\n",
-    "We also show alongside it the standard deviation of the predicted wavelength."
+    "In our setup, we simply propagate the same neutrons to multiple detector pixels,\n",
+    "as if they were not absorbed by the first pixel they meet."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "28",
+   "id": "35",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Ltotal = sc.array(dims=[\"detector_number\"], values=[77.675, 76.0], unit=\"m\")\n",
+    "monitors = {f\"detector{i}\": ltot for i, ltot in enumerate(Ltotal)}\n",
+    "\n",
+    "ess_beamline = FakeBeamline(\n",
+    "    choppers=disk_choppers,\n",
+    "    source_position=source_position,\n",
+    "    monitors=monitors,\n",
+    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 4,\n",
+    "    events_per_pulse=200_000,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "36",
+   "metadata": {},
+   "source": [
+    "Our raw data has now a `detector_number` dimension of length 2.\n",
+    "\n",
+    "We can plot the neutron `event_time_offset` for the two detector pixels and see that the offsets are shifted to the left for the pixel that is closest to the source."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "37",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def plot_lut(table):\n",
-    "    fig = table.plot(title=\"Predicted time-of-flight\") + sc.stddevs(table.array).plot(\n",
-    "        title=\"Standard deviation\", vmax=0.5\n",
+    "raw_data = sc.concat(\n",
+    "    [ess_beamline.get_monitor(key)[0].squeeze() for key in monitors.keys()],\n",
+    "    dim=\"detector_number\",\n",
+    ")\n",
+    "\n",
+    "# Visualize\n",
+    "pp.plot(sc.collapse(raw_data.hist(event_time_offset=300), keep=\"event_time_offset\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "38",
+   "metadata": {},
+   "source": [
+    "Computing wavelength is done in the same way as above.\n",
+    "We need to remember to update our workflow:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "39",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Update workflow\n",
+    "wf[RawDetector[SampleRun]] = raw_data\n",
+    "wf[DetectorLtotal[SampleRun]] = Ltotal\n",
+    "\n",
+    "# Compute tofs and wavelengths\n",
+    "wav_wfm = wf.compute(WavelengthDetector[SampleRun])\n",
+    "\n",
+    "# Compare in plot\n",
+    "ground_truth = []\n",
+    "for det in ess_beamline.monitors:\n",
+    "    data = ess_beamline.model_result[det.name].data.flatten(to=\"event\")\n",
+    "    ground_truth.append(data[~data.masks[\"blocked_by_others\"]])\n",
+    "\n",
+    "figs = [\n",
+    "    pp.plot(\n",
+    "        {\n",
+    "            \"wfm\": wav_wfm[\"detector_number\", i].bins.concat().hist(wavelength=edges),\n",
+    "            \"ground_truth\": ground_truth[i].hist(wavelength=edges),\n",
+    "        },\n",
+    "        title=f\"detector_number {i}\",\n",
+    "        color={\"ground_truth\": \"k\", \"wfm\": f\"C{i}\"},\n",
     "    )\n",
-    "    for f in (fig[0, 0], fig[0, 1]):\n",
-    "        f.ax.axhline(Ltotal.value, ls='dashed', color='k')\n",
-    "        f.ax.text(1e3, Ltotal.value, \"detector\", va='bottom', color='k')\n",
-    "        f.ax.text(1e3, Ltotal.value, \"at 26m\", va='top', color='k')\n",
-    "    return fig\n",
+    "    for i in range(len(Ltotal))\n",
+    "]\n",
     "\n",
+    "figs[0] + figs[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "40",
+   "metadata": {},
+   "source": [
+    "## Handling time overlap between subframes\n",
+    "\n",
+    "In some (relatively rare) cases, where a chopper cascade is slightly ill-defined,\n",
+    "it is sometimes possible for some subframes to overlap in time with other subframes.\n",
+    "\n",
+    "This is basically when neutrons passed through different pulse-shaping chopper openings,\n",
+    "but arrive at the same time at the detector.\n",
     "\n",
-    "plot_lut(table)"
+    "In this case, it is actually not possible to accurately determine the wavelength of the neutrons.\n",
+    "We handle this by masking the overlapping regions and throwing away any neutrons that lie within it.\n",
+    "\n",
+    "To simulate this, we modify slightly the phase and the cutouts of the band-control chopper:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "disk_choppers[\"bcc\"] = DiskChopper(\n",
+    "    frequency=sc.scalar(112.0, unit=\"Hz\"),\n",
+    "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
+    "    phase=sc.scalar(240 - 180, unit=\"deg\"),\n",
+    "    axle_position=sc.vector(value=[0, 0, -66.77], unit=\"m\"),\n",
+    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-36.875, 143.125], unit=\"deg\"),\n",
+    "    slit_end=sc.array(dims=[\"cutout\"], values=[46.875, 216.875], unit=\"deg\"),\n",
+    "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
+    "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
+    ")\n",
+    "\n",
+    "# Go back to a single detector pixel\n",
+    "Ltotal = sc.scalar(76.55 + 1.125, unit=\"m\")\n",
+    "\n",
+    "ess_beamline = FakeBeamline(\n",
+    "    choppers=disk_choppers,\n",
+    "    source_position=source_position,\n",
+    "    monitors={\"detector\": Ltotal},\n",
+    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 4,\n",
+    "    events_per_pulse=200_000,\n",
+    ")\n",
+    "\n",
+    "ess_beamline.model_result.plot()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "29",
+   "id": "42",
    "metadata": {},
    "source": [
-    "We can see that at low distances (< 7m), before the first choppers, the uncertainties are very large.\n",
-    "Neutrons with different wavelengths, originating from different parts of the pulse, are mixing and make it very difficult to predict a good wavelength.\n",
+    "We can now see that there is no longer a gap between the two frames at the center of each pulse (green region).\n",
     "\n",
-    "As we move to larger distances, uncertainties drop overall (colors drift to blue).\n",
-    "However, we still see spikes of uncertainties inside the frames around 26 m where the detector is placed,\n",
-    "which indicates contamination from neighbouring chopper openings.\n",
+    "Another way of looking at this is looking at the wavelength vs time-of-arrival plot,\n",
+    "which also shows overlap in time at the junction between the two frames:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Update workflow\n",
+    "lut_wf[DiskChoppers[AnyRun]] = disk_choppers\n",
     "\n",
-    "#### Optionally masking out large uncertainties\n",
+    "frames = lut_wf.compute(ChopperFrameSequence)\n",
+    "at_detector = frames.propagate_to(dist)\n",
+    "fig, ax = at_detector.draw()\n",
+    "ax.set(xlim=(36, 44), ylim=(2, 3))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44",
+   "metadata": {},
+   "source": [
+    "The data in the lookup table contains both the mean wavelength for each distance and time-of-arrival bin,\n",
+    "but also the variance inside each bin.\n",
     "\n",
-    "It is actually possible to mask out regions of large uncertainty using the `LookupTableRelativeErrorThreshold` parameter.\n",
+    "In the regions where there is no time overlap,\n",
+    "the variance is small (the regions are close to a thin line).\n",
+    "However, in the central region where overlap occurs,\n",
+    "we are computing a mean between two regions which have similar 'brightness'.\n",
     "\n",
-    "Because we may want to use different uncertainty criteria for different experimental runs as well as different components in the beamline (monitors, multiple detector banks),\n",
-    "the masking is not hard-coded in the table but a parameter that is applied on-the-fly in the original workflow which computes wavelength.\n",
+    "This leads to a large variance, and this is visible when plotting the relative standard deviations on a 2D figure\n",
+    "(we zoom in on the distances corresponding to the detector banks around 75m from the source)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "table = lut_wf.compute(LookupTable)\n",
+    "table.plot(ymin=65) / (sc.stddevs(table.array) / sc.values(table.array)).plot(\n",
+    "    norm=\"linear\", ymin=55, vmax=0.05\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46",
+   "metadata": {},
+   "source": [
+    "The workflow has a parameter which is used to mask out regions where the standard deviation is above a certain threshold.\n",
     "\n",
-    "We thus first update that workflow by setting the newly computed `table` as the `LookupTable` parameter.\n",
-    "Next, we apply a threshold for the `detector` component and inspect the masked table:"
+    "It is difficult to automatically detector this threshold,\n",
+    "as it can vary a lot depending on how much signal is received by the detectors,\n",
+    "and how far the detectors are from the source.\n",
+    "It is thus more robust to simply have a user tunable parameter on the workflow."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "30",
+   "id": "47",
    "metadata": {},
    "outputs": [],
    "source": [
     "wf[LookupTable] = table\n",
-    "wf[LookupTableRelativeErrorThreshold] = {\"detector\": 0.01}\n",
     "\n",
-    "masked = wf.compute(ErrorLimitedLookupTable[snx.NXdetector])\n",
+    "wf[LookupTableRelativeErrorThreshold] = {'dream_detector': 0.02}\n",
     "\n",
-    "plot_lut(masked)"
+    "masked_table = wf.compute(ErrorLimitedLookupTable[snx.NXdetector])\n",
+    "masked_table.plot(ymin=65)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "31",
+   "id": "48",
    "metadata": {},
    "source": [
-    "As we can see in the left panel, the regions in the table with large uncertainties are now white (they have been assigned a NaN value).\n",
-    "However, the masking is not very smooth, and it would also mean that a large number of events in these white regions would be discarded in the final reduced result.\n",
+    "We can now see that the central region is masked out.\n",
+    "\n",
+    "The neutrons in that region will be discarded in the wavelength calculation\n",
+    "(in practice, they are given a NaN value as a wavelength).\n",
     "\n",
-    "The contamination from neighbouring chopper openings is actually relatively small,\n",
-    "and we instead decide to live with that uncertainty and set the threshold to infinity to remove any masking in the table."
+    "This is visible when comparing to the true neutron wavelengths,\n",
+    "where we see that some counts were lost between the two frames."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "32",
+   "id": "49",
    "metadata": {},
    "outputs": [],
    "source": [
-    "wf[LookupTableRelativeErrorThreshold] = {\"detector\": np.inf}"
+    "wf[RawDetector[SampleRun]] = ess_beamline.get_monitor(\"detector\")[0]\n",
+    "wf[DetectorLtotal[SampleRun]] = Ltotal\n",
+    "\n",
+    "# Compute wavelength\n",
+    "wav_wfm = wf.compute(WavelengthDetector[SampleRun])\n",
+    "\n",
+    "# Compare to the true wavelengths\n",
+    "ground_truth = ess_beamline.model_result[\"detector\"].data.flatten(to=\"event\")\n",
+    "ground_truth = ground_truth[~ground_truth.masks[\"blocked_by_others\"]]\n",
+    "\n",
+    "pp.plot(\n",
+    "    {\n",
+    "        \"wfm\": wav_wfm.hist(wavelength=edges).squeeze(),\n",
+    "        \"ground_truth\": ground_truth.hist(wavelength=edges),\n",
+    "    },\n",
+    "    color={\"ground_truth\": \"k\"},\n",
+    ")"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "33",
+   "id": "20a35659-2c12-4d76-8375-82fcde28751d",
    "metadata": {},
    "source": [
-    "### Computing a wavelength coordinate\n",
+    "## The ODIN instrument"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1d69bbea-5a62-4b12-95e3-cc593323c3b5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parameters = {\n",
+    "    \"WFMC_1\": {\n",
+    "        \"frequency\": 56.0,\n",
+    "        \"phase\": 93.244,\n",
+    "        \"distance\": 6.85,\n",
+    "        \"open\": [-1.9419, 49.5756, 98.9315, 146.2165, 191.5176, 234.9179],\n",
+    "        \"close\": [1.9419, 55.7157, 107.2332, 156.5891, 203.8741, 249.1752],\n",
+    "    },\n",
+    "    \"WFMC_2\": {\n",
+    "        \"frequency\": 56.0,\n",
+    "        \"phase\": 97.128,\n",
+    "        \"distance\": 7.15,\n",
+    "        \"open\": [-1.9419, 51.8318, 103.3493, 152.7052, 199.9903, 245.2914],\n",
+    "        \"close\": [1.9419, 57.9719, 111.6510, 163.0778, 212.3468, 259.5486],\n",
+    "    },\n",
+    "    \"FOC_1\": {\n",
+    "        \"frequency\": 42.0,\n",
+    "        \"phase\": 81.303297,\n",
+    "        \"distance\": 8.4,\n",
+    "        \"open\": [-5.1362, 42.5536, 88.2425, 132.0144, 173.9497, 216.7867],\n",
+    "        \"close\": [5.1362, 54.2095, 101.2237, 146.2653, 189.417, 230.7582],\n",
+    "    },\n",
+    "    \"BP_1\": {\n",
+    "        \"frequency\": 7.0,\n",
+    "        \"phase\": 31.080,\n",
+    "        \"distance\": 8.45,\n",
+    "        \"open\": [-23.6029],\n",
+    "        \"close\": [23.6029],\n",
+    "    },\n",
+    "    \"FOC_2\": {\n",
+    "        \"frequency\": 42.0,\n",
+    "        \"phase\": 107.013442,\n",
+    "        \"distance\": 12.2,\n",
+    "        \"open\": [-16.3227, 53.7401, 120.8633, 185.1701, 246.7787, 307.0165],\n",
+    "        \"close\": [16.3227, 86.8303, 154.3794, 218.7551, 280.7508, 340.3188],\n",
+    "    },\n",
+    "    \"BP_2\": {\n",
+    "        \"frequency\": 7.0,\n",
+    "        \"phase\": 44.224,\n",
+    "        \"distance\": 12.25,\n",
+    "        \"open\": [-34.4663],\n",
+    "        \"close\": [34.4663],\n",
+    "    },\n",
+    "    \"T0_alpha\": {\n",
+    "        \"frequency\": 14.0,\n",
+    "        \"phase\": 179.672,\n",
+    "        \"distance\": 13.5,\n",
+    "        \"open\": [-167.8986],\n",
+    "        \"close\": [167.8986],\n",
+    "    },\n",
+    "    \"T0_beta\": {\n",
+    "        \"frequency\": 14.0,\n",
+    "        \"phase\": 179.672,\n",
+    "        \"distance\": 13.7,\n",
+    "        \"open\": [-167.8986],\n",
+    "        \"close\": [167.8986],\n",
+    "    },\n",
+    "    \"FOC_3\": {\n",
+    "        \"frequency\": 28.0,\n",
+    "        \"phase\": 92.993,\n",
+    "        \"distance\": 17.0,\n",
+    "        \"open\": [-20.302, 45.247, 108.0457, 168.2095, 225.8489, 282.2199],\n",
+    "        \"close\": [20.302, 85.357, 147.6824, 207.3927, 264.5977, 319.4024],\n",
+    "    },\n",
+    "    \"FOC_4\": {\n",
+    "        \"frequency\": 14.0,\n",
+    "        \"phase\": 61.584,\n",
+    "        \"distance\": 23.69,\n",
+    "        \"open\": [-16.7157, 29.1882, 73.1661, 115.2988, 155.6636, 195.5254],\n",
+    "        \"close\": [16.7157, 61.8217, 105.0352, 146.4355, 186.0987, 224.0978],\n",
+    "    },\n",
+    "    \"FOC_5\": {\n",
+    "        \"frequency\": 14.0,\n",
+    "        \"phase\": 82.581,\n",
+    "        \"distance\": 33.0,\n",
+    "        \"open\": [-25.8514, 38.3239, 99.8064, 160.1254, 217.4321, 272.5426],\n",
+    "        \"close\": [25.8514, 88.4621, 147.4729, 204.0245, 257.7603, 313.7139],\n",
+    "    },\n",
+    "}\n",
+    "\n",
     "\n",
-    "We will now compute our event data with a wavelength coordinate, and histogram the results:"
+    "odin_choppers = {\n",
+    "    key: DiskChopper(\n",
+    "        frequency=-ch[\"frequency\"] * sc.Unit(\"Hz\"),\n",
+    "        beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
+    "        phase=-ch[\"phase\"] * sc.Unit(\"deg\"),\n",
+    "        axle_position=sc.vector(value=[0, 0, ch[\"distance\"]], unit=\"m\"),\n",
+    "        slit_begin=sc.array(dims=[\"cutout\"], values=ch[\"open\"], unit=\"deg\"),\n",
+    "        slit_end=sc.array(dims=[\"cutout\"], values=ch[\"close\"], unit=\"deg\"),\n",
+    "    )\n",
+    "    for key, ch in parameters.items()\n",
+    "}"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "34",
+   "id": "d6acb539-4900-4d5e-ab8c-a6c02a6f53ba",
    "metadata": {},
    "outputs": [],
    "source": [
-    "wavs = wf.compute(WavelengthDetector[SampleRun])\n",
+    "Ltotal = sc.scalar(60.0, unit=\"m\")\n",
+    "source_position = sc.vector([0, 0, 0], unit='m')\n",
     "\n",
-    "bins = sc.linspace(\"wavelength\", 2, 10, 301, unit=\"angstrom\")\n",
-    "histogrammed = wavs.hist(wavelength=bins).squeeze()\n",
-    "histogrammed.plot()"
+    "ess_beamline = FakeBeamline(\n",
+    "    choppers=odin_choppers,\n",
+    "    source_position=source_position,\n",
+    "    monitors={\"detector\": Ltotal},\n",
+    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 4,\n",
+    "    events_per_pulse=400_000,\n",
+    ")\n",
+    "\n",
+    "ess_beamline.model_result.plot()"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "35",
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b9601b26-3af7-4bd7-a8fa-ef24a20aa5bf",
    "metadata": {},
+   "outputs": [],
    "source": [
-    "### Comparing to the ground truth\n",
+    "raw_data = ess_beamline.get_monitor(\"detector\")[0]\n",
     "\n",
-    "As a consistency check, because we actually know the wavelengths of the neutrons we created,\n",
-    "we can compare the true neutron wavelengths to those we computed above."
+    "# Visualize\n",
+    "raw_data.hist(event_time_offset=300).squeeze().plot()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "36",
+   "id": "17cf7ab2-7498-432f-b238-69a413d216d4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lut_wf = LookupTableWorkflow()\n",
+    "lut_wf[DiskChoppers[AnyRun]] = odin_choppers\n",
+    "lut_wf[SourcePosition] = source_position\n",
+    "lut_wf[LtotalRange] = (\n",
+    "    sc.scalar(25.0, unit=\"m\"),\n",
+    "    sc.scalar(65.0, unit=\"m\"),\n",
+    ")\n",
+    "lut_wf[PulseStride] = 2\n",
+    "\n",
+    "frames = lut_wf.compute(ChopperFrameSequence)\n",
+    "at_detector = frames.propagate_to(Ltotal)\n",
+    "fig, ax = at_detector.draw()\n",
+    "\n",
+    "table = lut_wf.compute(LookupTable)\n",
+    "\n",
+    "# Overlay LUT prediction on the polygons figure\n",
+    "da = table.array[\"distance\", 352]\n",
+    "ax.plot(\n",
+    "    da.coords['event_time_offset'].values / 1000,\n",
+    "    da.values,\n",
+    "    color=\"k\",\n",
+    "    ls=\"-\",\n",
+    "    marker=None,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "688216fd-449d-4035-a1ed-51498a795ed3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "table.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45ba33c1-6e7b-4f04-a0b4-cdb3e1f2b05c",
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Set the computed lookup table onto the original workflow\n",
+    "wf = GenericUnwrapWorkflow(run_types=[SampleRun], monitor_types=[])\n",
+    "\n",
+    "wf[RawDetector[SampleRun]] = raw_data\n",
+    "wf[DetectorLtotal[SampleRun]] = Ltotal\n",
+    "wf[NeXusDetectorName] = 'odin_detector'\n",
+    "wf[LookupTableRelativeErrorThreshold] = {'odin_detector': float(\"inf\")}\n",
+    "\n",
+    "wf.visualize(WavelengthDetector[SampleRun])\n",
+    "wf[LookupTable] = table\n",
+    "\n",
+    "# Compute wavelength of neutron events\n",
+    "wavs = wf.compute(WavelengthDetector[SampleRun])\n",
+    "edges = sc.linspace(\"wavelength\", 0.8, 10.0, 401, unit=\"angstrom\")\n",
+    "\n",
+    "histogrammed = wavs.hist(wavelength=edges).squeeze()\n",
+    "\n",
     "ground_truth = ess_beamline.model_result[\"detector\"].data.flatten(to=\"event\")\n",
     "ground_truth = ground_truth[~ground_truth.masks[\"blocked_by_others\"]]\n",
     "\n",
     "pp.plot(\n",
     "    {\n",
     "        \"wfm\": histogrammed,\n",
-    "        \"ground_truth\": ground_truth.hist(wavelength=bins),\n",
-    "    }\n",
+    "        \"ground_truth\": ground_truth.hist(wavelength=edges),\n",
+    "    },\n",
+    "    color={\"ground_truth\": \"k\"},\n",
     ")"
    ]
   }

From bd39def492dfe989666acdec5e7ec4c629594e3f Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 18:12:22 +0200
Subject: [PATCH 18/23] finalize wfm notebook

---
 .../docs/user-guide/unwrap/dream.ipynb        | 816 ------------------
 .../essreduce/docs/user-guide/unwrap/index.md |   1 -
 .../docs/user-guide/unwrap/wfm.ipynb          | 103 ++-
 3 files changed, 75 insertions(+), 845 deletions(-)
 delete mode 100644 packages/essreduce/docs/user-guide/unwrap/dream.ipynb

diff --git a/packages/essreduce/docs/user-guide/unwrap/dream.ipynb b/packages/essreduce/docs/user-guide/unwrap/dream.ipynb
deleted file mode 100644
index 7ddda6323..000000000
--- a/packages/essreduce/docs/user-guide/unwrap/dream.ipynb
+++ /dev/null
@@ -1,816 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "0",
-   "metadata": {},
-   "source": [
-    "# The DREAM chopper cascade\n",
-    "\n",
-    "In this notebook, we simulate the beamline of the DREAM instrument and its pulse-shaping choppers.\n",
-    "We then show how to use `essreduce`'s `unwrap` module to compute neutron wavelengths from their arrival times at the detectors.\n",
-    "\n",
-    "The case of DREAM is interesting because the pulse-shaping choppers can be used in a number of different modes,\n",
-    "and the number of cutouts the choppers have typically does not equal the number of frames observed at the detectors."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import plopp as pp\n",
-    "import scipp as sc\n",
-    "import scippnexus as snx\n",
-    "from scippneutron.chopper import DiskChopper\n",
-    "from ess.reduce.nexus.types import AnyRun, RawDetector, SampleRun, NeXusDetectorName\n",
-    "from ess.reduce.unwrap import *"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2",
-   "metadata": {},
-   "source": [
-    "## Setting up the beamline\n",
-    "\n",
-    "### Creating the beamline choppers\n",
-    "\n",
-    "We begin by defining the chopper settings for our beamline.\n",
-    "In principle, the chopper setting could simply be read from a NeXus file.\n",
-    "\n",
-    "The DREAM instrument has\n",
-    "\n",
-    "- 2 pulse-shaping choppers (PSC)\n",
-    "- 1 overlap chopper (OC)\n",
-    "- 1 band-control chopper (BCC)\n",
-    "- 1 T0 chopper"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "psc1 = DiskChopper(\n",
-    "    frequency=sc.scalar(14.0, unit=\"Hz\"),\n",
-    "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(286 - 180, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, -70.405], unit=\"m\"),\n",
-    "    slit_begin=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=[-1.23, 70.49, 84.765, 113.565, 170.29, 271.635, 286.035, 301.17],\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
-    "    slit_end=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=[1.23, 73.51, 88.035, 116.835, 175.31, 275.565, 289.965, 303.63],\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
-    "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
-    "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
-    ")\n",
-    "\n",
-    "psc2 = DiskChopper(\n",
-    "    frequency=sc.scalar(-14.0, unit=\"Hz\"),\n",
-    "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(-236, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, -70.395], unit=\"m\"),\n",
-    "    slit_begin=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=[-1.23, 27.0, 55.8, 142.385, 156.765, 214.115, 257.23, 315.49],\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
-    "    slit_end=sc.array(\n",
-    "        dims=[\"cutout\"],\n",
-    "        values=[1.23, 30.6, 59.4, 145.615, 160.035, 217.885, 261.17, 318.11],\n",
-    "        unit=\"deg\",\n",
-    "    ),\n",
-    "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
-    "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
-    ")\n",
-    "\n",
-    "oc = DiskChopper(\n",
-    "    frequency=sc.scalar(14.0, unit=\"Hz\"),\n",
-    "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(297 - 180 - 90, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, -70.376], unit=\"m\"),\n",
-    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-27.6 * 0.5], unit=\"deg\"),\n",
-    "    slit_end=sc.array(dims=[\"cutout\"], values=[27.6 * 0.5], unit=\"deg\"),\n",
-    "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
-    "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
-    ")\n",
-    "\n",
-    "bcc = DiskChopper(\n",
-    "    frequency=sc.scalar(112.0, unit=\"Hz\"),\n",
-    "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(240 - 180, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, -66.77], unit=\"m\"),\n",
-    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-36.875, 143.125], unit=\"deg\"),\n",
-    "    slit_end=sc.array(dims=[\"cutout\"], values=[36.875, 216.875], unit=\"deg\"),\n",
-    "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
-    "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
-    ")\n",
-    "\n",
-    "t0 = DiskChopper(\n",
-    "    frequency=sc.scalar(28.0, unit=\"Hz\"),\n",
-    "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(280 - 180, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, -63.5], unit=\"m\"),\n",
-    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-314.9 * 0.5], unit=\"deg\"),\n",
-    "    slit_end=sc.array(dims=[\"cutout\"], values=[314.9 * 0.5], unit=\"deg\"),\n",
-    "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
-    "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
-    ")\n",
-    "\n",
-    "disk_choppers = {\"psc1\": psc1, \"psc2\": psc2, \"oc\": oc, \"bcc\": bcc, \"t0\": t0}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4",
-   "metadata": {},
-   "source": [
-    "It is possible to visualize the properties of the choppers by inspecting their `repr`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "psc2"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6",
-   "metadata": {},
-   "source": [
-    "Define the source position which is required to compute the distance that neutrons travelled."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "source_position = sc.vector([0, 0, -76.55], unit=\"m\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8",
-   "metadata": {},
-   "source": [
-    "### Adding a detector"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Ltotal = sc.scalar(76.55 + 1.125, unit=\"m\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "10",
-   "metadata": {},
-   "source": [
-    "## Creating some neutron events\n",
-    "\n",
-    "We create a semi-realistic set of neutron events based on the ESS pulse."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "11",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from ess.reduce.unwrap.fakes import FakeBeamline\n",
-    "\n",
-    "ess_beamline = FakeBeamline(\n",
-    "    choppers=disk_choppers,\n",
-    "    source_position=source_position,\n",
-    "    monitors={\"detector\": Ltotal},\n",
-    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 4,\n",
-    "    events_per_pulse=200_000,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "12",
-   "metadata": {},
-   "source": [
-    "The initial birth times and wavelengths of the generated neutrons can be visualized (for a single pulse):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "13",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "one_pulse = ess_beamline.source.data[\"pulse\", 0]\n",
-    "one_pulse.hist(birth_time=300).plot() + one_pulse.hist(wavelength=300).plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "14",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ess_beamline.model_result.plot()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "15",
-   "metadata": {},
-   "source": [
-    "From this fake beamline, we extract the raw neutron signal at our detector:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "16",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "raw_data = ess_beamline.get_monitor(\"detector\")[0]\n",
-    "\n",
-    "# Visualize\n",
-    "raw_data.hist(event_time_offset=300).squeeze().plot()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "17",
-   "metadata": {},
-   "source": [
-    "The total number of neutrons in our sample data that make it through to the detector is:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "18",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "raw_data.sum().value"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "19",
-   "metadata": {},
-   "source": [
-    "## Computing neutron wavelengths\n",
-    "\n",
-    "Next, we use a workflow that provides an estimate of the neutron wavelength as a function of neutron time-of-arrival.\n",
-    "\n",
-    "### Setting up the workflow"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "20",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "wf = GenericUnwrapWorkflow(run_types=[SampleRun], monitor_types=[])\n",
-    "\n",
-    "wf[RawDetector[SampleRun]] = raw_data\n",
-    "wf[DetectorLtotal[SampleRun]] = Ltotal\n",
-    "wf[NeXusDetectorName] = 'dream_detector'\n",
-    "wf[LookupTableRelativeErrorThreshold] = {'dream_detector': float(\"inf\")}\n",
-    "\n",
-    "wf.visualize(WavelengthDetector[SampleRun])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "21",
-   "metadata": {},
-   "source": [
-    "By default, the workflow tries to load a `LookupTable` from a file.\n",
-    "\n",
-    "In this notebook, instead of using such a pre-made file,\n",
-    "we will build our own lookup table from the chopper information and apply it to the workflow."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "22",
-   "metadata": {},
-   "source": [
-    "### Building the wavelength lookup table\n",
-    "\n",
-    "We use [`scippneutron.tof.chopper_cascade`](https://scipp.github.io/scippneutron/user-guide/chopper/chopper-cascade.html) module to propagate a pulse of neutrons through the chopper system to the detectors,\n",
-    "and predict the most likely neutron wavelength for a given time-of-arrival and distance from source.\n",
-    "\n",
-    "From this,\n",
-    "we build a lookup table on which bilinear interpolation is used to compute a wavelength for every neutron event."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "23",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "lut_wf = LookupTableWorkflow()\n",
-    "lut_wf[DiskChoppers[AnyRun]] = disk_choppers\n",
-    "lut_wf[SourcePosition] = source_position\n",
-    "lut_wf[LtotalRange] = (\n",
-    "    sc.scalar(25.0, unit=\"m\"),\n",
-    "    sc.scalar(80.0, unit=\"m\"),\n",
-    ")\n",
-    "lut_wf.visualize(LookupTable)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "24",
-   "metadata": {},
-   "source": [
-    "### Inspecting the lookup table\n",
-    "\n",
-    "The workflow first runs a calculation propagating a pulse of neutrons (represented by a polygon in time and wavelength space),\n",
-    "through a chopper cascade defined by the chopper parameters above.\n",
-    "\n",
-    "This can be used to create a figure displaying the neutron wavelengths,\n",
-    "as a function of arrival time at the detector.\n",
-    "\n",
-    "This is the basis for creating our lookup table."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6f82c864-e33b-4d04-b3ca-a201eec46222",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "dist = sc.scalar(60.0, unit='m')\n",
-    "\n",
-    "frames = lut_wf.compute(ChopperFrameSequence)\n",
-    "at_detector = frames.propagate_to(dist)\n",
-    "fig, ax = at_detector.draw()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "378df191-0f21-456b-9a6f-157479d83b24",
-   "metadata": {},
-   "source": [
-    "The source pulse is defined as spanning 0-5 ms in time, and 0-15 Å in wavelength,\n",
-    "and is represented by the blue rectangle on the left hand side of the diagram.\n",
-    "\n",
-    "As the pulse propagates through the system,\n",
-    "it stretches (slow neutrons take longer to reach the same distance) and gets chopped by the chopper openings,\n",
-    "creating polygons from the rectangular pulse.\n",
-    "\n",
-    "Finally, at the detector distance of 60 m, we are left with two (pink) very thin polygons,\n",
-    "representing the two packets of neutrons that are allowed through the instrument.\n",
-    "\n",
-    "The idea is to approximate these thin polygons as a single line,\n",
-    "effectively giving us a function relating neutron wavelength as a function of arrival time.\n",
-    "This is precisely how the loop table is built,\n",
-    "and if we overlay the wavelength values given by the table at a distance of 60 m,\n",
-    "we see that the black lines pass right in the middle of the polygons."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "eed14ca5-fbbb-4ac8-b288-a04793b73f50",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "table = lut_wf.compute(LookupTable)\n",
-    "\n",
-    "# Overlay LUT prediction on the polygons figure\n",
-    "da = table.array[\"distance\", 352]\n",
-    "ax.plot(\n",
-    "    da.coords['event_time_offset'].values / 1000,\n",
-    "    da.values,\n",
-    "    color=\"k\",\n",
-    "    ls=\"-\",\n",
-    "    marker=None,\n",
-    ")\n",
-    "fig"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "daeeef2d-79d8-4dc7-84fc-5c6b75cee436",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ax.set(xlim=[39.5, 41.5], ylim=[2.6, 2.72])\n",
-    "fig"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "28",
-   "metadata": {},
-   "source": [
-    "The full table covers a range of distances, and looks like"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "29",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "table.plot()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "30",
-   "metadata": {},
-   "source": [
-    "### Computing a wavelength coordinate\n",
-    "\n",
-    "We will now update our workflow, and use it to obtain our event data with a wavelength coordinate:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "31",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Set the computed lookup table onto the original workflow\n",
-    "wf[LookupTable] = table\n",
-    "\n",
-    "# Compute wavelength of neutron events\n",
-    "wavs = wf.compute(WavelengthDetector[SampleRun])\n",
-    "edges = sc.linspace(\"wavelength\", 0.8, 4.6, 201, unit=\"angstrom\")\n",
-    "\n",
-    "histogrammed = wavs.hist(wavelength=edges).squeeze()\n",
-    "histogrammed.plot()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "32",
-   "metadata": {},
-   "source": [
-    "### Comparing to the ground truth\n",
-    "\n",
-    "As a consistency check, because we actually know the wavelengths of the neutrons we created,\n",
-    "we can compare the true neutron wavelengths to those we computed above."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "33",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ground_truth = ess_beamline.model_result[\"detector\"].data.flatten(to=\"event\")\n",
-    "ground_truth = ground_truth[~ground_truth.masks[\"blocked_by_others\"]]\n",
-    "\n",
-    "pp.plot(\n",
-    "    {\n",
-    "        \"wfm\": histogrammed,\n",
-    "        \"ground_truth\": ground_truth.hist(wavelength=edges),\n",
-    "    },\n",
-    "    color={\"ground_truth\": \"k\"},\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "34",
-   "metadata": {},
-   "source": [
-    "## Multiple detector pixels\n",
-    "\n",
-    "It is also possible to compute the neutron wavelength for multiple detector pixels at once,\n",
-    "where every pixel has different frame bounds\n",
-    "(because every pixel is at a different distance from the source).\n",
-    "\n",
-    "In our setup, we simply propagate the same neutrons to multiple detector pixels,\n",
-    "as if they were not absorbed by the first pixel they meet."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "35",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Ltotal = sc.array(dims=[\"detector_number\"], values=[77.675, 76.0], unit=\"m\")\n",
-    "monitors = {f\"detector{i}\": ltot for i, ltot in enumerate(Ltotal)}\n",
-    "\n",
-    "ess_beamline = FakeBeamline(\n",
-    "    choppers=disk_choppers,\n",
-    "    source_position=source_position,\n",
-    "    monitors=monitors,\n",
-    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 4,\n",
-    "    events_per_pulse=200_000,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "36",
-   "metadata": {},
-   "source": [
-    "Our raw data has now a `detector_number` dimension of length 2.\n",
-    "\n",
-    "We can plot the neutron `event_time_offset` for the two detector pixels and see that the offsets are shifted to the left for the pixel that is closest to the source."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "37",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "raw_data = sc.concat(\n",
-    "    [ess_beamline.get_monitor(key)[0].squeeze() for key in monitors.keys()],\n",
-    "    dim=\"detector_number\",\n",
-    ")\n",
-    "\n",
-    "# Visualize\n",
-    "pp.plot(sc.collapse(raw_data.hist(event_time_offset=300), keep=\"event_time_offset\"))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "38",
-   "metadata": {},
-   "source": [
-    "Computing wavelength is done in the same way as above.\n",
-    "We need to remember to update our workflow:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "39",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Update workflow\n",
-    "wf[RawDetector[SampleRun]] = raw_data\n",
-    "wf[DetectorLtotal[SampleRun]] = Ltotal\n",
-    "\n",
-    "# Compute tofs and wavelengths\n",
-    "wav_wfm = wf.compute(WavelengthDetector[SampleRun])\n",
-    "\n",
-    "# Compare in plot\n",
-    "ground_truth = []\n",
-    "for det in ess_beamline.monitors:\n",
-    "    data = ess_beamline.model_result[det.name].data.flatten(to=\"event\")\n",
-    "    ground_truth.append(data[~data.masks[\"blocked_by_others\"]])\n",
-    "\n",
-    "figs = [\n",
-    "    pp.plot(\n",
-    "        {\n",
-    "            \"wfm\": wav_wfm[\"detector_number\", i].bins.concat().hist(wavelength=edges),\n",
-    "            \"ground_truth\": ground_truth[i].hist(wavelength=edges),\n",
-    "        },\n",
-    "        title=f\"detector_number {i}\",\n",
-    "        color={\"ground_truth\": \"k\", \"wfm\": f\"C{i}\"},\n",
-    "    )\n",
-    "    for i in range(len(Ltotal))\n",
-    "]\n",
-    "\n",
-    "figs[0] + figs[1]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "40",
-   "metadata": {},
-   "source": [
-    "## Handling time overlap between subframes\n",
-    "\n",
-    "In some (relatively rare) cases, where a chopper cascade is slightly ill-defined,\n",
-    "it is sometimes possible for some subframes to overlap in time with other subframes.\n",
-    "\n",
-    "This is basically when neutrons passed through different pulse-shaping chopper openings,\n",
-    "but arrive at the same time at the detector.\n",
-    "\n",
-    "In this case, it is actually not possible to accurately determine the wavelength of the neutrons.\n",
-    "We handle this by masking the overlapping regions and throwing away any neutrons that lie within it.\n",
-    "\n",
-    "To simulate this, we modify slightly the phase and the cutouts of the band-control chopper:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "41",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "disk_choppers[\"bcc\"] = DiskChopper(\n",
-    "    frequency=sc.scalar(112.0, unit=\"Hz\"),\n",
-    "    beam_position=sc.scalar(0.0, unit=\"deg\"),\n",
-    "    phase=sc.scalar(240 - 180, unit=\"deg\"),\n",
-    "    axle_position=sc.vector(value=[0, 0, -66.77], unit=\"m\"),\n",
-    "    slit_begin=sc.array(dims=[\"cutout\"], values=[-36.875, 143.125], unit=\"deg\"),\n",
-    "    slit_end=sc.array(dims=[\"cutout\"], values=[46.875, 216.875], unit=\"deg\"),\n",
-    "    slit_height=sc.scalar(10.0, unit=\"cm\"),\n",
-    "    radius=sc.scalar(30.0, unit=\"cm\"),\n",
-    ")\n",
-    "\n",
-    "# Go back to a single detector pixel\n",
-    "Ltotal = sc.scalar(76.55 + 1.125, unit=\"m\")\n",
-    "\n",
-    "ess_beamline = FakeBeamline(\n",
-    "    choppers=disk_choppers,\n",
-    "    source_position=source_position,\n",
-    "    monitors={\"detector\": Ltotal},\n",
-    "    run_length=sc.scalar(1 / 14, unit=\"s\") * 4,\n",
-    "    events_per_pulse=200_000,\n",
-    ")\n",
-    "\n",
-    "ess_beamline.model_result.plot()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "42",
-   "metadata": {},
-   "source": [
-    "We can now see that there is no longer a gap between the two frames at the center of each pulse (green region).\n",
-    "\n",
-    "Another way of looking at this is looking at the wavelength vs time-of-arrival plot,\n",
-    "which also shows overlap in time at the junction between the two frames:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "43",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Update workflow\n",
-    "lut_wf[DiskChoppers[AnyRun]] = disk_choppers\n",
-    "\n",
-    "frames = lut_wf.compute(ChopperFrameSequence)\n",
-    "at_detector = frames.propagate_to(dist)\n",
-    "fig, ax = at_detector.draw()\n",
-    "ax.set(xlim=(36, 44), ylim=(2, 3))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "44",
-   "metadata": {},
-   "source": [
-    "The data in the lookup table contains both the mean wavelength for each distance and time-of-arrival bin,\n",
-    "but also the variance inside each bin.\n",
-    "\n",
-    "In the regions where there is no time overlap,\n",
-    "the variance is small (the regions are close to a thin line).\n",
-    "However, in the central region where overlap occurs,\n",
-    "we are computing a mean between two regions which have similar 'brightness'.\n",
-    "\n",
-    "This leads to a large variance, and this is visible when plotting the relative standard deviations on a 2D figure\n",
-    "(we zoom in on the distances corresponding to the detector banks around 75m from the source)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "45",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "table = lut_wf.compute(LookupTable)\n",
-    "table.plot(ymin=65) / (sc.stddevs(table.array) / sc.values(table.array)).plot(\n",
-    "    norm=\"linear\", ymin=55, vmax=0.05\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "46",
-   "metadata": {},
-   "source": [
-    "The workflow has a parameter which is used to mask out regions where the standard deviation is above a certain threshold.\n",
-    "\n",
-    "It is difficult to automatically detector this threshold,\n",
-    "as it can vary a lot depending on how much signal is received by the detectors,\n",
-    "and how far the detectors are from the source.\n",
-    "It is thus more robust to simply have a user tunable parameter on the workflow."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "47",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "wf[LookupTable] = table\n",
-    "\n",
-    "wf[LookupTableRelativeErrorThreshold] = {'dream_detector': 0.02}\n",
-    "\n",
-    "masked_table = wf.compute(ErrorLimitedLookupTable[snx.NXdetector])\n",
-    "masked_table.plot(ymin=65)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "48",
-   "metadata": {},
-   "source": [
-    "We can now see that the central region is masked out.\n",
-    "\n",
-    "The neutrons in that region will be discarded in the wavelength calculation\n",
-    "(in practice, they are given a NaN value as a wavelength).\n",
-    "\n",
-    "This is visible when comparing to the true neutron wavelengths,\n",
-    "where we see that some counts were lost between the two frames."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "49",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "wf[RawDetector[SampleRun]] = ess_beamline.get_monitor(\"detector\")[0]\n",
-    "wf[DetectorLtotal[SampleRun]] = Ltotal\n",
-    "\n",
-    "# Compute wavelength\n",
-    "wav_wfm = wf.compute(WavelengthDetector[SampleRun])\n",
-    "\n",
-    "# Compare to the true wavelengths\n",
-    "ground_truth = ess_beamline.model_result[\"detector\"].data.flatten(to=\"event\")\n",
-    "ground_truth = ground_truth[~ground_truth.masks[\"blocked_by_others\"]]\n",
-    "\n",
-    "pp.plot(\n",
-    "    {\n",
-    "        \"wfm\": wav_wfm.hist(wavelength=edges).squeeze(),\n",
-    "        \"ground_truth\": ground_truth.hist(wavelength=edges),\n",
-    "    },\n",
-    "    color={\"ground_truth\": \"k\"},\n",
-    ")"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "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": "3.12.12"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/packages/essreduce/docs/user-guide/unwrap/index.md b/packages/essreduce/docs/user-guide/unwrap/index.md
index 137d5dbda..a185fbb14 100644
--- a/packages/essreduce/docs/user-guide/unwrap/index.md
+++ b/packages/essreduce/docs/user-guide/unwrap/index.md
@@ -7,5 +7,4 @@ maxdepth: 1
 
 frame-unwrapping
 wfm
-dream
 ```
diff --git a/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb b/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
index 6d5086052..5da6770e0 100644
--- a/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
+++ b/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
@@ -2,13 +2,24 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "0",
+   "id": "0f321dd3-e3d0-4789-9062-b7a48963c01e",
    "metadata": {},
    "source": [
-    "# The DREAM chopper cascade\n",
+    "# Wavelength frame multiplication\n",
     "\n",
-    "In this notebook, we simulate the beamline of the DREAM instrument and its pulse-shaping choppers.\n",
-    "We then show how to use `essreduce`'s `unwrap` module to compute neutron wavelengths from their arrival times at the detectors.\n",
+    "Wavelength frame multiplication (WFM) is a technique commonly used at long-pulse facilities to improve the resolution of the results measured at the neutron detectors.\n",
+    "See for example the article by [Schmakat et al. (2020)](https://doi.org/10.1016/j.nima.2020.164467) for a description of how WFM works.\n",
+    "\n",
+    "In this notebook, we show how to use `essreduce`'s `unwrap` module to compute an accurate wavelength coordinate for neutrons travelling through two WFM beamlines:\n",
+    "the DREAM and ODIN instruments."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0",
+   "metadata": {},
+   "source": [
+    "## The DREAM chopper cascade\n",
     "\n",
     "The case of DREAM is interesting because the pulse-shaping choppers can be used in a number of different modes,\n",
     "and the number of cutouts the choppers have typically does not equal the number of frames observed at the detectors."
@@ -34,8 +45,6 @@
    "id": "2",
    "metadata": {},
    "source": [
-    "## Setting up the beamline\n",
-    "\n",
     "### Creating the beamline choppers\n",
     "\n",
     "We begin by defining the chopper settings for our beamline.\n",
@@ -189,7 +198,7 @@
    "id": "10",
    "metadata": {},
    "source": [
-    "## Creating some neutron events\n",
+    "### Creating some neutron events\n",
     "\n",
     "We create a semi-realistic set of neutron events based on the ESS pulse."
    ]
@@ -285,11 +294,11 @@
    "id": "19",
    "metadata": {},
    "source": [
-    "## Computing neutron wavelengths\n",
+    "### Computing neutron wavelengths\n",
     "\n",
     "Next, we use a workflow that provides an estimate of the neutron wavelength as a function of neutron time-of-arrival.\n",
     "\n",
-    "### Setting up the workflow"
+    "#### Setting up the workflow"
    ]
   },
   {
@@ -325,7 +334,7 @@
    "id": "22",
    "metadata": {},
    "source": [
-    "### Building the wavelength lookup table\n",
+    "#### Building the wavelength lookup table\n",
     "\n",
     "We use [`scippneutron.tof.chopper_cascade`](https://scipp.github.io/scippneutron/user-guide/chopper/chopper-cascade.html) module to propagate a pulse of neutrons through the chopper system to the detectors,\n",
     "and predict the most likely neutron wavelength for a given time-of-arrival and distance from source.\n",
@@ -356,7 +365,7 @@
    "id": "24",
    "metadata": {},
    "source": [
-    "### Inspecting the lookup table\n",
+    "#### Inspecting the lookup table\n",
     "\n",
     "The workflow first runs a calculation propagating a pulse of neutrons (represented by a polygon in time and wavelength space),\n",
     "through a chopper cascade defined by the chopper parameters above.\n",
@@ -458,7 +467,7 @@
    "id": "30",
    "metadata": {},
    "source": [
-    "### Computing a wavelength coordinate\n",
+    "#### Computing a wavelength coordinate\n",
     "\n",
     "We will now update our workflow, and use it to obtain our event data with a wavelength coordinate:"
    ]
@@ -486,7 +495,7 @@
    "id": "32",
    "metadata": {},
    "source": [
-    "### Comparing to the ground truth\n",
+    "#### Comparing to the ground truth\n",
     "\n",
     "As a consistency check, because we actually know the wavelengths of the neutrons we created,\n",
     "we can compare the true neutron wavelengths to those we computed above."
@@ -516,7 +525,7 @@
    "id": "34",
    "metadata": {},
    "source": [
-    "## Multiple detector pixels\n",
+    "### Multiple detector pixels\n",
     "\n",
     "It is also possible to compute the neutron wavelength for multiple detector pixels at once,\n",
     "where every pixel has different frame bounds\n",
@@ -620,7 +629,7 @@
    "id": "40",
    "metadata": {},
    "source": [
-    "## Handling time overlap between subframes\n",
+    "### Handling time overlap between subframes\n",
     "\n",
     "In some (relatively rare) cases, where a chopper cascade is slightly ill-defined,\n",
     "it is sometimes possible for some subframes to overlap in time with other subframes.\n",
@@ -796,7 +805,18 @@
    "id": "20a35659-2c12-4d76-8375-82fcde28751d",
    "metadata": {},
    "source": [
-    "## The ODIN instrument"
+    "## The ODIN instrument\n",
+    "\n",
+    "The second example is the ODIN instrument;\n",
+    "it is a more classical case in the sense that the WFM choppers have 6 openings and produce 6 neutron frames at the detector.\n",
+    "\n",
+    "However, it uses a technique called 'pulse-skipping' where a chopper rotating at half the source frequency blocks (or 'skips') every other pulse.\n",
+    "This allows the range of wavelengths recorded at the detector to be much wider,\n",
+    "because overlap between consecutive pulses has been reduced by a factor of 2.\n",
+    "\n",
+    "### Setting up the beamline and data\n",
+    "\n",
+    "We begin by defining the chopper parameters and creating fake events, as we did previously for DREAM."
    ]
   },
   {
@@ -886,7 +906,6 @@
     "    },\n",
     "}\n",
     "\n",
-    "\n",
     "odin_choppers = {\n",
     "    key: DiskChopper(\n",
     "        frequency=-ch[\"frequency\"] * sc.Unit(\"Hz\"),\n",
@@ -897,16 +916,8 @@
     "        slit_end=sc.array(dims=[\"cutout\"], values=ch[\"close\"], unit=\"deg\"),\n",
     "    )\n",
     "    for key, ch in parameters.items()\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d6acb539-4900-4d5e-ab8c-a6c02a6f53ba",
-   "metadata": {},
-   "outputs": [],
-   "source": [
+    "}\n",
+    "\n",
     "Ltotal = sc.scalar(60.0, unit=\"m\")\n",
     "source_position = sc.vector([0, 0, 0], unit='m')\n",
     "\n",
@@ -934,6 +945,18 @@
     "raw_data.hist(event_time_offset=300).squeeze().plot()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "ddce6d88-9f57-4010-80c4-ec7217edb45a",
+   "metadata": {},
+   "source": [
+    "### Creating the lookup table for ODIN\n",
+    "\n",
+    "We use once again the `LookupTableWorkflow` to compute the wavelength lookup table.\n",
+    "\n",
+    "Because ODIN uses a pulse-skipping chopper, we need to set `PulseStride = 2` on the workflow."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -967,6 +990,21 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "522246a6-c778-4ea9-b04f-2bbc53a6867d",
+   "metadata": {},
+   "source": [
+    "The final relation between time-of-arrival and wavelength at the detector is represented by the black lines that accurately trace the green polygons\n",
+    "(zooming in on the figure may be required to even see the polygons at 60 m).\n",
+    "\n",
+    "Also note that because of the pulse skipping, we consider two source pulses (blue rectangles) instead of one in the DREAM case.\n",
+    "Both pulses generate sets of polygons up to 8.4 m, but beyond that only the first pulses continues to travel down the beamline,\n",
+    "while the second pulse got blocked by the 7 Hz chopper.\n",
+    "\n",
+    "The full wavelength lookup table is plotted below."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -977,6 +1015,16 @@
     "table.plot()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "c0ebaad8-bb67-41c1-b0f2-aeed52dc527b",
+   "metadata": {},
+   "source": [
+    "### Computing wavelengths for ODIN\n",
+    "\n",
+    "Computing wavelengths is done in exactly the same way as for DREAM above."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -984,7 +1032,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Set the computed lookup table onto the original workflow\n",
     "wf = GenericUnwrapWorkflow(run_types=[SampleRun], monitor_types=[])\n",
     "\n",
     "wf[RawDetector[SampleRun]] = raw_data\n",

From 39c17bdb23fc1a9b0288b85643f21c935f9cd26e Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 18:13:10 +0200
Subject: [PATCH 19/23] lint

---
 .../docs/user-guide/unwrap/wfm.ipynb          | 122 +++++++++---------
 1 file changed, 61 insertions(+), 61 deletions(-)

diff --git a/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb b/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
index 5da6770e0..516eea94b 100644
--- a/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
+++ b/packages/essreduce/docs/user-guide/unwrap/wfm.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "0f321dd3-e3d0-4789-9062-b7a48963c01e",
+   "id": "0",
    "metadata": {},
    "source": [
     "# Wavelength frame multiplication\n",
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0",
+   "id": "1",
    "metadata": {},
    "source": [
     "## The DREAM chopper cascade\n",
@@ -28,7 +28,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1",
+   "id": "2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -42,7 +42,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2",
+   "id": "3",
    "metadata": {},
    "source": [
     "### Creating the beamline choppers\n",
@@ -61,7 +61,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3",
+   "id": "4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -141,7 +141,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4",
+   "id": "5",
    "metadata": {},
    "source": [
     "It is possible to visualize the properties of the choppers by inspecting their `repr`:"
@@ -150,7 +150,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5",
+   "id": "6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6",
+   "id": "7",
    "metadata": {},
    "source": [
     "Define the source position which is required to compute the distance that neutrons travelled."
@@ -168,7 +168,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7",
+   "id": "8",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -177,7 +177,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8",
+   "id": "9",
    "metadata": {},
    "source": [
     "### Adding a detector"
@@ -186,7 +186,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9",
+   "id": "10",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -195,7 +195,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "10",
+   "id": "11",
    "metadata": {},
    "source": [
     "### Creating some neutron events\n",
@@ -206,7 +206,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "11",
+   "id": "12",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -223,7 +223,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "12",
+   "id": "13",
    "metadata": {},
    "source": [
     "The initial birth times and wavelengths of the generated neutrons can be visualized (for a single pulse):"
@@ -232,7 +232,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "13",
+   "id": "14",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -243,7 +243,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "14",
+   "id": "15",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -252,7 +252,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "15",
+   "id": "16",
    "metadata": {},
    "source": [
     "From this fake beamline, we extract the raw neutron signal at our detector:"
@@ -261,7 +261,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "16",
+   "id": "17",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -273,7 +273,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "17",
+   "id": "18",
    "metadata": {},
    "source": [
     "The total number of neutrons in our sample data that make it through to the detector is:"
@@ -282,7 +282,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "18",
+   "id": "19",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -291,7 +291,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "19",
+   "id": "20",
    "metadata": {},
    "source": [
     "### Computing neutron wavelengths\n",
@@ -304,7 +304,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "20",
+   "id": "21",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -320,7 +320,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "21",
+   "id": "22",
    "metadata": {},
    "source": [
     "By default, the workflow tries to load a `LookupTable` from a file.\n",
@@ -331,7 +331,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22",
+   "id": "23",
    "metadata": {},
    "source": [
     "#### Building the wavelength lookup table\n",
@@ -346,7 +346,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "23",
+   "id": "24",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -362,7 +362,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24",
+   "id": "25",
    "metadata": {},
    "source": [
     "#### Inspecting the lookup table\n",
@@ -379,7 +379,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6f82c864-e33b-4d04-b3ca-a201eec46222",
+   "id": "26",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -392,7 +392,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "378df191-0f21-456b-9a6f-157479d83b24",
+   "id": "27",
    "metadata": {},
    "source": [
     "The source pulse is defined as spanning 0-5 ms in time, and 0-15 Å in wavelength,\n",
@@ -415,7 +415,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "eed14ca5-fbbb-4ac8-b288-a04793b73f50",
+   "id": "28",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -436,7 +436,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "daeeef2d-79d8-4dc7-84fc-5c6b75cee436",
+   "id": "29",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -446,7 +446,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "28",
+   "id": "30",
    "metadata": {},
    "source": [
     "The full table covers a range of distances, and looks like"
@@ -455,7 +455,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "29",
+   "id": "31",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -464,7 +464,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "30",
+   "id": "32",
    "metadata": {},
    "source": [
     "#### Computing a wavelength coordinate\n",
@@ -475,7 +475,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "31",
+   "id": "33",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -492,7 +492,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "32",
+   "id": "34",
    "metadata": {},
    "source": [
     "#### Comparing to the ground truth\n",
@@ -504,7 +504,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "33",
+   "id": "35",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -522,7 +522,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "34",
+   "id": "36",
    "metadata": {},
    "source": [
     "### Multiple detector pixels\n",
@@ -538,7 +538,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "35",
+   "id": "37",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -556,7 +556,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36",
+   "id": "38",
    "metadata": {},
    "source": [
     "Our raw data has now a `detector_number` dimension of length 2.\n",
@@ -567,7 +567,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "37",
+   "id": "39",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -582,7 +582,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "38",
+   "id": "40",
    "metadata": {},
    "source": [
     "Computing wavelength is done in the same way as above.\n",
@@ -592,7 +592,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "39",
+   "id": "41",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -626,7 +626,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "40",
+   "id": "42",
    "metadata": {},
    "source": [
     "### Handling time overlap between subframes\n",
@@ -646,7 +646,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "41",
+   "id": "43",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -677,7 +677,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42",
+   "id": "44",
    "metadata": {},
    "source": [
     "We can now see that there is no longer a gap between the two frames at the center of each pulse (green region).\n",
@@ -689,7 +689,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "43",
+   "id": "45",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -704,7 +704,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44",
+   "id": "46",
    "metadata": {},
    "source": [
     "The data in the lookup table contains both the mean wavelength for each distance and time-of-arrival bin,\n",
@@ -722,7 +722,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "45",
+   "id": "47",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -734,7 +734,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "46",
+   "id": "48",
    "metadata": {},
    "source": [
     "The workflow has a parameter which is used to mask out regions where the standard deviation is above a certain threshold.\n",
@@ -748,7 +748,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "47",
+   "id": "49",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -762,7 +762,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "48",
+   "id": "50",
    "metadata": {},
    "source": [
     "We can now see that the central region is masked out.\n",
@@ -777,7 +777,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "49",
+   "id": "51",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -802,7 +802,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "20a35659-2c12-4d76-8375-82fcde28751d",
+   "id": "52",
    "metadata": {},
    "source": [
     "## The ODIN instrument\n",
@@ -822,7 +822,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1d69bbea-5a62-4b12-95e3-cc593323c3b5",
+   "id": "53",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -935,7 +935,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b9601b26-3af7-4bd7-a8fa-ef24a20aa5bf",
+   "id": "54",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -947,7 +947,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ddce6d88-9f57-4010-80c4-ec7217edb45a",
+   "id": "55",
    "metadata": {},
    "source": [
     "### Creating the lookup table for ODIN\n",
@@ -960,7 +960,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "17cf7ab2-7498-432f-b238-69a413d216d4",
+   "id": "56",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -992,7 +992,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "522246a6-c778-4ea9-b04f-2bbc53a6867d",
+   "id": "57",
    "metadata": {},
    "source": [
     "The final relation between time-of-arrival and wavelength at the detector is represented by the black lines that accurately trace the green polygons\n",
@@ -1008,7 +1008,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "688216fd-449d-4035-a1ed-51498a795ed3",
+   "id": "58",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1017,7 +1017,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c0ebaad8-bb67-41c1-b0f2-aeed52dc527b",
+   "id": "59",
    "metadata": {},
    "source": [
     "### Computing wavelengths for ODIN\n",
@@ -1028,7 +1028,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "45ba33c1-6e7b-4f04-a0b4-cdb3e1f2b05c",
+   "id": "60",
    "metadata": {},
    "outputs": [],
    "source": [

From 4cd93a2574289423450cc56dceb0ff2ec9d22e3c Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 21:01:36 +0200
Subject: [PATCH 20/23] drop use of tof for lut in most places

---
 .../dream-make-wavelength-lookup-table.ipynb  |  1 -
 .../tests/dream/geant4_reduction_test.py      |  2 -
 .../odin-make-wavelength-lookup-table.ipynb   |  2 -
 .../tbl-make-wavelength-lookup-table.ipynb    |  2 -
 .../tests/tbl/data_reduction_test.py          |  2 -
 .../essreduce/tests/unwrap/workflow_test.py   | 43 ++++++++-----------
 ...create-estia-wavelength-lookup-table.ipynb |  1 -
 .../loki-make-wavelength-lookup-table.ipynb   |  2 -
 8 files changed, 19 insertions(+), 36 deletions(-)

diff --git a/packages/essdiffraction/docs/user-guide/dream/dream-make-wavelength-lookup-table.ipynb b/packages/essdiffraction/docs/user-guide/dream/dream-make-wavelength-lookup-table.ipynb
index 05047add4..98fd30bc5 100644
--- a/packages/essdiffraction/docs/user-guide/dream/dream-make-wavelength-lookup-table.ipynb
+++ b/packages/essdiffraction/docs/user-guide/dream/dream-make-wavelength-lookup-table.ipynb
@@ -63,7 +63,6 @@
     "wf = unwrap.LookupTableWorkflow()\n",
     "\n",
     "wf[unwrap.LtotalRange] = sc.scalar(5.0, unit=\"m\"), sc.scalar(80.0, unit=\"m\")\n",
-    "wf[unwrap.NumberOfSimulatedNeutrons] = 200_000  # Increase this number for more reliable results\n",
     "wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')\n",
     "wf[unwrap.DiskChoppers[AnyRun]] = disk_choppers\n",
     "wf[unwrap.DistanceResolution] = sc.scalar(0.1, unit=\"m\")\n",
diff --git a/packages/essdiffraction/tests/dream/geant4_reduction_test.py b/packages/essdiffraction/tests/dream/geant4_reduction_test.py
index bb71eaa7b..1d3f0926a 100644
--- a/packages/essdiffraction/tests/dream/geant4_reduction_test.py
+++ b/packages/essdiffraction/tests/dream/geant4_reduction_test.py
@@ -123,8 +123,6 @@ def dream_lookup_table():
         dream.beamline.InstrumentConfiguration.high_flux_BC215
     )
     lut_wf[unwrap.SourcePosition] = sc.vector(value=[0, 0, -76.55], unit="m")
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 500_000
-    lut_wf[unwrap.SimulationSeed] = 555
     lut_wf[unwrap.PulseStride] = 1
     lut_wf[unwrap.LtotalRange] = (
         sc.scalar(60.0, unit="m"),
diff --git a/packages/essimaging/docs/odin/odin-make-wavelength-lookup-table.ipynb b/packages/essimaging/docs/odin/odin-make-wavelength-lookup-table.ipynb
index 9781f50f5..5a6114684 100644
--- a/packages/essimaging/docs/odin/odin-make-wavelength-lookup-table.ipynb
+++ b/packages/essimaging/docs/odin/odin-make-wavelength-lookup-table.ipynb
@@ -42,8 +42,6 @@
     "wf = unwrap.LookupTableWorkflow()\n",
     "wf[unwrap.DiskChoppers[AnyRun]] = disk_choppers\n",
     "wf[unwrap.SourcePosition] = source_position\n",
-    "wf[unwrap.NumberOfSimulatedNeutrons] = 200_000  # Increase this number for more reliable results\n",
-    "wf[unwrap.SimulationSeed] = 1234\n",
     "wf[unwrap.PulseStride] = 2\n",
     "wf[unwrap.LtotalRange] = sc.scalar(5.0, unit=\"m\"), sc.scalar(65.0, unit=\"m\")\n",
     "wf[unwrap.DistanceResolution] = sc.scalar(0.1, unit=\"m\")\n",
diff --git a/packages/essimaging/docs/tbl/tbl-make-wavelength-lookup-table.ipynb b/packages/essimaging/docs/tbl/tbl-make-wavelength-lookup-table.ipynb
index 674ad6db0..30a4116ef 100644
--- a/packages/essimaging/docs/tbl/tbl-make-wavelength-lookup-table.ipynb
+++ b/packages/essimaging/docs/tbl/tbl-make-wavelength-lookup-table.ipynb
@@ -40,8 +40,6 @@
     "wf = unwrap.LookupTableWorkflow()\n",
     "wf[unwrap.DiskChoppers[AnyRun]] = {}\n",
     "wf[unwrap.SourcePosition] = source_position\n",
-    "wf[unwrap.NumberOfSimulatedNeutrons] = 200_000  # Increase this number for more reliable results\n",
-    "wf[unwrap.SimulationSeed] = 1234\n",
     "wf[unwrap.PulseStride] = 1\n",
     "wf[unwrap.LtotalRange] = sc.scalar(5.0, unit=\"m\"), sc.scalar(35.0, unit=\"m\")\n",
     "wf[unwrap.DistanceResolution] = sc.scalar(0.1, unit=\"m\")\n",
diff --git a/packages/essimaging/tests/tbl/data_reduction_test.py b/packages/essimaging/tests/tbl/data_reduction_test.py
index 0a96b648c..368356f55 100644
--- a/packages/essimaging/tests/tbl/data_reduction_test.py
+++ b/packages/essimaging/tests/tbl/data_reduction_test.py
@@ -29,8 +29,6 @@ def wavelength_lookup_table() -> sl.Pipeline:
     lut_wf = unwrap.LookupTableWorkflow()
     lut_wf[unwrap.DiskChoppers[AnyRun]] = {}
     lut_wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit="m")
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 200_000
-    lut_wf[unwrap.SimulationSeed] = 333
     lut_wf[unwrap.PulseStride] = 1
     lut_wf[unwrap.LtotalRange] = (sc.scalar(25.0, unit="m"), sc.scalar(35.0, unit="m"))
     return lut_wf.compute(LookupTable)
diff --git a/packages/essreduce/tests/unwrap/workflow_test.py b/packages/essreduce/tests/unwrap/workflow_test.py
index ddf2323ca..08dda4e41 100644
--- a/packages/essreduce/tests/unwrap/workflow_test.py
+++ b/packages/essreduce/tests/unwrap/workflow_test.py
@@ -20,6 +20,7 @@
 )
 from ess.reduce.unwrap import (
     GenericUnwrapWorkflow,
+    LookupTableFromTof,
     LookupTableWorkflow,
     fakes,
 )
@@ -74,14 +75,15 @@ def workflow() -> GenericUnwrapWorkflow:
     return wf
 
 
-def test_LookupTableWorkflow_can_compute_lut():
-    wf = LookupTableWorkflow()
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
+def test_LookupTableWorkflow_can_compute_lut(engine):
+    if engine == "tof":
+        wf = LookupTableFromTof()
+        wf[unwrap.NumberOfSimulatedNeutrons] = 10_000
+    else:
+        wf = LookupTableWorkflow()
     wf[DiskChoppers[AnyRun]] = fakes.psc_choppers()
-    wf[unwrap.NumberOfSimulatedNeutrons] = 10_000
-    wf[unwrap.LtotalRange] = (
-        sc.scalar(75.0, unit="m"),
-        sc.scalar(85.0, unit="m"),
-    )
+    wf[unwrap.LtotalRange] = (sc.scalar(75.0, unit="m"), sc.scalar(85.0, unit="m"))
     wf[unwrap.SourcePosition] = fakes.source_position()
     lut = wf.compute(unwrap.LookupTable)
     assert lut.array is not None
@@ -92,7 +94,8 @@ def test_LookupTableWorkflow_can_compute_lut():
     # assert lut.choppers is not None
 
 
-def test_GenericUnwrapWorkflow_with_lut_from_tof_simulation(workflow):
+@pytest.mark.parametrize("engine", ["tof", "analytical"])
+def test_GenericUnwrapWorkflow_with_lut_from_tof_simulation(workflow, engine):
     # Should be able to compute DetectorData without chopper and simulation params
     # This contains event_time_offset (time-of-arrival).
     _ = workflow.compute(RawDetector[SampleRun])
@@ -102,13 +105,13 @@ def test_GenericUnwrapWorkflow_with_lut_from_tof_simulation(workflow):
     with pytest.raises(sciline.UnsatisfiedRequirement):
         _ = workflow.compute(unwrap.WavelengthDetector[SampleRun])
 
-    lut_wf = LookupTableWorkflow()
+    if engine == "tof":
+        lut_wf = LookupTableFromTof()
+        lut_wf[unwrap.NumberOfSimulatedNeutrons] = 10_000
+    else:
+        lut_wf = LookupTableWorkflow()
     lut_wf[DiskChoppers[AnyRun]] = fakes.psc_choppers()
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 10_000
-    lut_wf[unwrap.LtotalRange] = (
-        sc.scalar(75.0, unit="m"),
-        sc.scalar(85.0, unit="m"),
-    )
+    lut_wf[unwrap.LtotalRange] = (sc.scalar(75.0, unit="m"), sc.scalar(85.0, unit="m"))
     lut_wf[unwrap.SourcePosition] = fakes.source_position()
     table = lut_wf.compute(unwrap.LookupTable)
 
@@ -122,11 +125,7 @@ def test_GenericUnwrapWorkflow_with_lut_from_file(
 ):
     lut_wf = LookupTableWorkflow()
     lut_wf[DiskChoppers[AnyRun]] = fakes.psc_choppers()
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 10_000
-    lut_wf[unwrap.LtotalRange] = (
-        sc.scalar(75.0, unit="m"),
-        sc.scalar(85.0, unit="m"),
-    )
+    lut_wf[unwrap.LtotalRange] = (sc.scalar(75.0, unit="m"), sc.scalar(85.0, unit="m"))
     lut_wf[unwrap.SourcePosition] = fakes.source_position()
     lut = lut_wf.compute(unwrap.LookupTable)
     lut.save_hdf5(filename=tmp_path / "lut.h5")
@@ -150,11 +149,7 @@ def test_GenericUnwrapWorkflow_with_lut_from_file_old_format(
 ):
     lut_wf = LookupTableWorkflow()
     lut_wf[DiskChoppers[AnyRun]] = fakes.psc_choppers()
-    lut_wf[unwrap.NumberOfSimulatedNeutrons] = 10_000
-    lut_wf[unwrap.LtotalRange] = (
-        sc.scalar(75.0, unit="m"),
-        sc.scalar(85.0, unit="m"),
-    )
+    lut_wf[unwrap.LtotalRange] = (sc.scalar(75.0, unit="m"), sc.scalar(85.0, unit="m"))
     lut_wf[unwrap.SourcePosition] = fakes.source_position()
     lut = lut_wf.compute(unwrap.LookupTable)
     old_lut = sc.DataArray(
diff --git a/packages/essreflectometry/docs/user-guide/estia/create-estia-wavelength-lookup-table.ipynb b/packages/essreflectometry/docs/user-guide/estia/create-estia-wavelength-lookup-table.ipynb
index b27330140..3096faae0 100644
--- a/packages/essreflectometry/docs/user-guide/estia/create-estia-wavelength-lookup-table.ipynb
+++ b/packages/essreflectometry/docs/user-guide/estia/create-estia-wavelength-lookup-table.ipynb
@@ -78,7 +78,6 @@
     "wf = unwrap.LookupTableWorkflow()\n",
     "\n",
     "wf[unwrap.LtotalRange] = sc.scalar(35., unit=\"m\"), sc.scalar(45.0, unit=\"m\")\n",
-    "wf[unwrap.NumberOfSimulatedNeutrons] = 10_000_000\n",
     "wf[unwrap.SourcePosition] = sc.vector([0, 0, 0], unit='m')\n",
     "wf[unwrap.DiskChoppers[AnyRun]] = disk_choppers\n",
     "wf[unwrap.DistanceResolution] = sc.scalar(0.05, unit=\"m\")\n",
diff --git a/packages/esssans/docs/user-guide/loki/loki-make-wavelength-lookup-table.ipynb b/packages/esssans/docs/user-guide/loki/loki-make-wavelength-lookup-table.ipynb
index 69ac77540..1ba16d709 100644
--- a/packages/esssans/docs/user-guide/loki/loki-make-wavelength-lookup-table.ipynb
+++ b/packages/esssans/docs/user-guide/loki/loki-make-wavelength-lookup-table.ipynb
@@ -43,8 +43,6 @@
     "wf = unwrap.LookupTableWorkflow()\n",
     "wf[unwrap.DiskChoppers[AnyRun]] = {}\n",
     "wf[unwrap.SourcePosition] = source_position\n",
-    "wf[unwrap.NumberOfSimulatedNeutrons] = 200_000  # Increase this number for more reliable results\n",
-    "wf[unwrap.SimulationSeed] = 1234\n",
     "wf[unwrap.PulseStride] = 1\n",
     "wf[unwrap.LtotalRange] = sc.scalar(9.0, unit=\"m\"), sc.scalar(35.0, unit=\"m\")\n",
     "wf[unwrap.DistanceResolution] = sc.scalar(0.1, unit=\"m\")\n",

From 1a26290f815ef33f0f16aa186e057324a54ae91b Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 21:14:57 +0200
Subject: [PATCH 21/23] try suggestions from copilot for pixi.toml

---
 pixi.toml | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/pixi.toml b/pixi.toml
index db6eed47c..64a1d18d9 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -112,28 +112,28 @@ cmd = "python -m sphinx -v -b html -d packages/esssans/.docs_doctrees packages/e
 default = { features = ["dev", "essreduce", "essimaging", "essnmx", "essreflectometry", "essdiffraction", "esssans"], solve-group = "default" }
 
 # Per-package test environments (include workspace dep features)
-essreduce = { features = ["essreduce"], solve-group = "default" }
-essimaging = { features = ["essimaging", "essreduce"], solve-group = "default" }
-essnmx = { features = ["essnmx", "essreduce"], solve-group = "default" }
-essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "default" }
-essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "default" }
-esssans = { features = ["esssans", "essreduce"], solve-group = "default" }
+essreduce = { features = ["essreduce"], solve-group = "essreduce" }
+essimaging = { features = ["essimaging", "essreduce"], solve-group = "essimaging" }
+essnmx = { features = ["essnmx", "essreduce"], solve-group = "essnmx" }
+essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "essreflectometry" }
+essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "essdiffraction" }
+esssans = { features = ["esssans", "essreduce"], solve-group = "esssans" }
 
 # Lower-bound test environments (separate resolution)
-lb-essreduce = { features = ["essreduce"], solve-group = "lower-bound" }
-lb-essimaging = { features = ["essimaging", "essreduce"], solve-group = "lower-bound" }
-lb-essnmx = { features = ["essnmx", "essreduce"], solve-group = "lower-bound" }
-lb-essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "lower-bound" }
-lb-essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "lower-bound" }
-lb-esssans = { features = ["esssans", "essreduce"], solve-group = "lower-bound" }
+lb-essreduce = { features = ["essreduce"], solve-group = "lb-essreduce" }
+lb-essimaging = { features = ["essimaging", "essreduce"], solve-group = "lb-essimaging" }
+lb-essnmx = { features = ["essnmx", "essreduce"], solve-group = "lb-essnmx" }
+lb-essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "lb-essreflectometry" }
+lb-essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "lb-essdiffraction" }
+lb-esssans = { features = ["esssans", "essreduce"], solve-group = "lb-esssans" }
 
 # Docs environments (package with docs extra + pandoc)
-docs-essreduce = { features = ["docs-essreduce", "docs"], solve-group = "default" }
-docs-essimaging = { features = ["docs-essimaging", "docs-essreduce", "docs"], solve-group = "default" }
-docs-essnmx = { features = ["docs-essnmx", "docs-essreduce", "docs"], solve-group = "default" }
-docs-essreflectometry = { features = ["docs-essreflectometry", "docs-essreduce", "docs"], solve-group = "default" }
-docs-essdiffraction = { features = ["docs-essdiffraction", "docs-essreduce", "docs"], solve-group = "default" }
-docs-esssans = { features = ["docs-esssans", "docs-essreduce", "docs"], solve-group = "default" }
+docs-essreduce = { features = ["docs-essreduce", "docs"], solve-group = "docs-essreduce" }
+docs-essimaging = { features = ["docs-essimaging", "docs-essreduce", "docs"], solve-group = "docs-essimaging" }
+docs-essnmx = { features = ["docs-essnmx", "docs-essreduce", "docs"], solve-group = "docs-essnmx" }
+docs-essreflectometry = { features = ["docs-essreflectometry", "docs-essreduce", "docs"], solve-group = "docs-essreflectometry" }
+docs-essdiffraction = { features = ["docs-essdiffraction", "docs-essreduce", "docs"], solve-group = "docs-essdiffraction" }
+docs-esssans = { features = ["docs-esssans", "docs-essreduce", "docs"], solve-group = "docs-esssans" }
 
 # Lint environment (standalone, no package deps)
 lint = { features = ["lint"], solve-group = "lint" }

From 9481acf72f72d641e5e9649865c14497f11d48f9 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 21:15:16 +0200
Subject: [PATCH 22/23] update lock file

---
 pixi.lock | 1456 ++---------------------------------------------------
 1 file changed, 28 insertions(+), 1428 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index b6af90729..b41508e2d 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -10,105 +10,28 @@ environments:
     packages:
       linux-64:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/adwaita-icon-theme-49.0-unix_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/at-spi2-atk-2.38.0-h0630a04_3.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/at-spi2-core-2.40.3-h0630a04_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/atk-1.0-2.38.0-h04ea711_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.4-he90730b_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h24cb091_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/epoxy-1.5.10-hb03c661_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_3.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/fontconfig-2.17.1-h27c8c51_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-hc364b38_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.16-hb03c661_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gdk-pixbuf-2.44.5-h2b0a6b4_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/glib-tools-2.86.4-hf516916_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.14-hecca717_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/graphviz-14.1.2-h8b86629_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gtk3-3.24.52-ha5ea40c_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gts-0.7.6-h977cf35_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/harfbuzz-13.2.1-h6083320_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/hicolor-icon-theme-0.17-ha770c72_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-hb9d3cd8_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/krb5-1.22.2-ha1258a1_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_102.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/lerc-4.1.0-hdb68285_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcups-2.3.3-h7a8fb5f_6.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.25-h17f619e_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdrm-2.4.125-hb03c661_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20250104-pl5321h7949ede_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libegl-1.7.0-ha4b6fd6_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libegl-devel-1.7.0-ha4b6fd6_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype-2.14.3-ha770c72_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype6-2.14.3-h73754d4_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_18.conda
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@@ -9575,6 +8174,7 @@ environments:
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+      - pypi: https://files.pythonhosted.org/packages/91/4c/e0ce1ef95d4000ebc1c11801f9b944fa5910ecc15b5e351865763d8657f8/graphviz-0.21-py3-none-any.whl
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From 636a2f3f5ef5d8f5cafd624d8cc8d166442ccde1 Mon Sep 17 00:00:00 2001
From: Neil Vaytet <neil.vaytet@ess.eu>
Date: Sat, 9 May 2026 21:24:50 +0200
Subject: [PATCH 23/23] revert changes in pixi.toml

---
 pixi.toml | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/pixi.toml b/pixi.toml
index 64a1d18d9..db6eed47c 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -112,28 +112,28 @@ cmd = "python -m sphinx -v -b html -d packages/esssans/.docs_doctrees packages/e
 default = { features = ["dev", "essreduce", "essimaging", "essnmx", "essreflectometry", "essdiffraction", "esssans"], solve-group = "default" }
 
 # Per-package test environments (include workspace dep features)
-essreduce = { features = ["essreduce"], solve-group = "essreduce" }
-essimaging = { features = ["essimaging", "essreduce"], solve-group = "essimaging" }
-essnmx = { features = ["essnmx", "essreduce"], solve-group = "essnmx" }
-essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "essreflectometry" }
-essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "essdiffraction" }
-esssans = { features = ["esssans", "essreduce"], solve-group = "esssans" }
+essreduce = { features = ["essreduce"], solve-group = "default" }
+essimaging = { features = ["essimaging", "essreduce"], solve-group = "default" }
+essnmx = { features = ["essnmx", "essreduce"], solve-group = "default" }
+essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "default" }
+essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "default" }
+esssans = { features = ["esssans", "essreduce"], solve-group = "default" }
 
 # Lower-bound test environments (separate resolution)
-lb-essreduce = { features = ["essreduce"], solve-group = "lb-essreduce" }
-lb-essimaging = { features = ["essimaging", "essreduce"], solve-group = "lb-essimaging" }
-lb-essnmx = { features = ["essnmx", "essreduce"], solve-group = "lb-essnmx" }
-lb-essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "lb-essreflectometry" }
-lb-essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "lb-essdiffraction" }
-lb-esssans = { features = ["esssans", "essreduce"], solve-group = "lb-esssans" }
+lb-essreduce = { features = ["essreduce"], solve-group = "lower-bound" }
+lb-essimaging = { features = ["essimaging", "essreduce"], solve-group = "lower-bound" }
+lb-essnmx = { features = ["essnmx", "essreduce"], solve-group = "lower-bound" }
+lb-essreflectometry = { features = ["essreflectometry", "essreduce"], solve-group = "lower-bound" }
+lb-essdiffraction = { features = ["essdiffraction", "essreduce"], solve-group = "lower-bound" }
+lb-esssans = { features = ["esssans", "essreduce"], solve-group = "lower-bound" }
 
 # Docs environments (package with docs extra + pandoc)
-docs-essreduce = { features = ["docs-essreduce", "docs"], solve-group = "docs-essreduce" }
-docs-essimaging = { features = ["docs-essimaging", "docs-essreduce", "docs"], solve-group = "docs-essimaging" }
-docs-essnmx = { features = ["docs-essnmx", "docs-essreduce", "docs"], solve-group = "docs-essnmx" }
-docs-essreflectometry = { features = ["docs-essreflectometry", "docs-essreduce", "docs"], solve-group = "docs-essreflectometry" }
-docs-essdiffraction = { features = ["docs-essdiffraction", "docs-essreduce", "docs"], solve-group = "docs-essdiffraction" }
-docs-esssans = { features = ["docs-esssans", "docs-essreduce", "docs"], solve-group = "docs-esssans" }
+docs-essreduce = { features = ["docs-essreduce", "docs"], solve-group = "default" }
+docs-essimaging = { features = ["docs-essimaging", "docs-essreduce", "docs"], solve-group = "default" }
+docs-essnmx = { features = ["docs-essnmx", "docs-essreduce", "docs"], solve-group = "default" }
+docs-essreflectometry = { features = ["docs-essreflectometry", "docs-essreduce", "docs"], solve-group = "default" }
+docs-essdiffraction = { features = ["docs-essdiffraction", "docs-essreduce", "docs"], solve-group = "default" }
+docs-esssans = { features = ["docs-esssans", "docs-essreduce", "docs"], solve-group = "default" }
 
 # Lint environment (standalone, no package deps)
 lint = { features = ["lint"], solve-group = "lint" }