mathutils/image items: code refactoring

Author: PierreRaybaut

plotpy/coords.py

@@ -7,20 +7,32 @@
 Plot coordinates
 ----------------
 
+Overview
+^^^^^^^^
+
 The :mod:`plotpy.coords` module provides functions to convert coordinates
 between canvas and axes coordinates systems.
 
+The following functions are available:
+
+* :py:func:`.canvas_to_axes`
+* :py:func:`.axes_to_canvas`
+* :py:func:`.pixelround`
+
 Reference
-~~~~~~~~~
+^^^^^^^^^
 
 .. autofunction:: canvas_to_axes
 .. autofunction:: axes_to_canvas
+.. autofunction:: pixelround
 """
 
 from __future__ import annotations
 
 from typing import TYPE_CHECKING
 
+import numpy as np
+
 if TYPE_CHECKING:  # pragma: no cover
     from qtpy.QtCore import QPointF
     from qwt import QwtPlot, QwtPlotItem
@@ -59,3 +71,23 @@ def axes_to_canvas(item: QwtPlotItem, x: float, y: float) -> tuple[float, float]
     plot: QwtPlot = item.plot()
     ax, ay = item.xAxis(), item.yAxis()
     return plot.transform(ax, x), plot.transform(ay, y)
+
+
+def pixelround(x: float, corner: str | None = None) -> int:
+    """Get pixel index from pixel coordinate
+
+    Args:
+        x: Pixel coordinate
+        corner: None (not a corner), 'TL' (top-left corner),
+         'BR' (bottom-right corner)
+
+    Returns:
+        int: Pixel index
+    """
+    assert corner is None or corner in ("TL", "BR")
+    if corner is None:
+        return np.floor(x)
+    elif corner == "BR":
+        return np.ceil(x)
+    elif corner == "TL":
+        return np.floor(x)

plotpy/items/image/base.py

@@ -27,6 +27,7 @@
 )
 from plotpy.config import _
 from plotpy.constants import LUTAlpha
+from plotpy.coords import pixelround
 from plotpy.interfaces import (
     IBaseImageItem,
     IBasePlotItem,
@@ -42,6 +43,7 @@
 )
 from plotpy.items.shape.rectangle import RectangleShape
 from plotpy.lutrange import lut_range_threshold
+from plotpy.mathutils.arrayfuncs import get_nan_range
 from plotpy.mathutils.colormap import FULLRANGE, get_cmap, get_cmap_name
 from plotpy.styles.image import RawImageParam
 
@@ -60,60 +62,6 @@
 LUT_MAX = float(LUT_SIZE - 1)
 
 
-def _nanmin(data: np.ndarray) -> float:
-    """Return minimum value of data, ignoring NaNs
-
-    Args:
-        data: Data array
-
-    Returns:
-        float: Minimum value of data, ignoring NaNs
-    """
-    if isinstance(data, np.ma.MaskedArray):
-        data = data.data
-    if data.dtype.name in ("float32", "float64", "float128"):
-        return np.nanmin(data)
-    else:
-        return data.min()
-
-
-def _nanmax(data: np.ndarray) -> float:
-    """Return maximum value of data, ignoring NaNs
-
-    Args:
-        data: Data array
-
-    Returns:
-        float: Maximum value of data, ignoring NaNs
-    """
-    if isinstance(data, np.ma.MaskedArray):
-        data = data.data
-    if data.dtype.name in ("float32", "float64", "float128"):
-        return np.nanmax(data)
-    else:
-        return data.max()
-
-
-def pixelround(x: float, corner: str | None = None) -> int:
-    """Get pixel index from pixel coordinate
-
-    Args:
-        x: Pixel coordinate
-        corner: None (not a corner), 'TL' (top-left corner),
-         'BR' (bottom-right corner)
-
-    Returns:
-        int: Pixel index
-    """
-    assert corner is None or corner in ("TL", "BR")
-    if corner is None:
-        return np.floor(x)
-    elif corner == "BR":
-        return np.ceil(x)
-    elif corner == "TL":
-        return np.floor(x)
-
-
 class BaseImageItem(QwtPlotItem):
     """Base class for image items
 
@@ -391,7 +339,7 @@ def set_data(
         if lut_range is not None:
             _min, _max = lut_range
         else:
-            _min, _max = _nanmin(data), _nanmax(data)
+            _min, _max = get_nan_range(data)
 
         self.data = data
         self.histogram_cache = None
@@ -592,7 +540,7 @@ def get_lut_range_full(self) -> tuple[float, float]:
         Returns:
             tuple[float, float]: Lut range, tuple(min, max)
         """
-        return _nanmin(self.data), _nanmax(self.data)
+        return get_nan_range(self.data)
 
     def get_lut_range_max(self) -> tuple[float, float]:
         """Get maximum range for this dataset
@@ -1019,8 +967,7 @@ def get_histogram(self, nbins: int) -> tuple[np.ndarray, np.ndarray]:
                 res = np.histogram(self.data[~np.isnan(self.data)], nbins)
             else:
                 # TODO: _histogram is faster, but caching is buggy in this version
-                _min = _nanmin(self.data)
-                _max = _nanmax(self.data)
+                _min, _max = get_nan_range(self.data)
                 if self.data.dtype in (np.float64, np.float32):
                     bins = np.unique(
                         np.array(

plotpy/items/image/image_items.py

@@ -13,7 +13,7 @@
 from plotpy import io
 from plotpy.config import _
 from plotpy.constants import LUTAlpha
-from plotpy.coords import canvas_to_axes
+from plotpy.coords import canvas_to_axes, pixelround
 from plotpy.interfaces import (
     IBaseImageItem,
     IBasePlotItem,
@@ -26,9 +26,8 @@
     ITrackableItemType,
     IVoiImageItemType,
 )
-from plotpy.items.image.base import RawImageItem, pixelround
+from plotpy.items.image.base import RawImageItem
 from plotpy.items.image.filter import XYImageFilterItem, to_bins
-from plotpy.mathutils.geometry import colvector
 from plotpy.styles.image import ImageParam, RGBImageParam, XYImageParam
 
 if TYPE_CHECKING:  # pragma: no cover

plotpy/items/image/misc.py

@@ -25,8 +25,9 @@
     ITrackableItemType,
     IVoiImageItemType,
 )
-from plotpy.items.image.base import BaseImageItem, RawImageItem, _nanmax, _nanmin
+from plotpy.items.image.base import BaseImageItem, RawImageItem
 from plotpy.items.image.transform import TrImageItem
+from plotpy.mathutils.arrayfuncs import get_nan_range
 from plotpy.styles import Histogram2DParam, ImageParam, QuadGridParam
 
 try:
@@ -136,7 +137,7 @@ def set_data(
         if lut_range is not None:
             _min, _max = lut_range
         else:
-            _min, _max = _nanmin(data), _nanmax(data)
+            _min, _max = get_nan_range(data)
 
         self.data = data
         self.histogram_cache = None
@@ -330,8 +331,7 @@ def draw_image(
             else:
                 self.data[self.data_tmp == 0.0] = np.nan
         if self.histparam.auto_lut:
-            nmin = _nanmin(self.data)
-            nmax = _nanmax(self.data)
+            nmin, nmax = get_nan_range(self.data)
             self.set_lut_range([nmin, nmax])
             self.plot().update_colormap_axis(self)
         src_rect = (0, 0, self.nx_bins, self.ny_bins)
@@ -417,8 +417,7 @@ def get_histogram(self, nbins: int) -> tuple[np.ndarray, np.ndarray]:
         """
         if self.data is None:
             return [0], [0, 1]
-        _min = _nanmin(self.data)
-        _max = _nanmax(self.data)
+        _min, _max = get_nan_range(self.data)
         if self.data.dtype in (np.float64, np.float32):
             bins = np.unique(
                 np.array(np.linspace(_min, _max, nbins + 1), dtype=self.data.dtype)

plotpy/mathutils/arrayfuncs.py

@@ -0,0 +1,74 @@
+# -*- coding: utf-8 -*-
+
+"""
+Array functions
+---------------
+
+Overview
+^^^^^^^^
+
+The :py:mod:`.arrayfuncs` module provides miscellaneous array functions.
+
+The following functions are available:
+
+* :py:func:`.get_nan_min`
+* :py:func:`.get_nan_max`
+* :py:func:`.get_nan_range`
+
+Reference
+^^^^^^^^^
+
+.. autofunction:: get_nan_min
+.. autofunction:: get_nan_max
+.. autofunction:: get_nan_range
+"""
+
+from __future__ import annotations
+
+import numpy as np
+
+
+def get_nan_min(data: np.ndarray | np.ma.MaskedArray) -> float:
+    """Return minimum value of data, ignoring NaNs
+
+    Args:
+        data: Data array (or masked array)
+
+    Returns:
+        float: Minimum value of data, ignoring NaNs
+    """
+    if isinstance(data, np.ma.MaskedArray):
+        data = data.data
+    if data.dtype.name in ("float32", "float64", "float128"):
+        return np.nanmin(data)
+    else:
+        return data.min()
+
+
+def get_nan_max(data: np.ndarray | np.ma.MaskedArray) -> float:
+    """Return maximum value of data, ignoring NaNs
+
+    Args:
+        data: Data array (or masked array)
+
+    Returns:
+        float: Maximum value of data, ignoring NaNs
+    """
+    if isinstance(data, np.ma.MaskedArray):
+        data = data.data
+    if data.dtype.name in ("float32", "float64", "float128"):
+        return np.nanmax(data)
+    else:
+        return data.max()
+
+
+def get_nan_range(data: np.ndarray | np.ma.MaskedArray) -> tuple[float, float]:
+    """Return range of data, i.e. (min, max), ignoring NaNs
+
+    Args:
+        data: Data array (or masked array)
+
+    Returns:
+        tuple: Minimum and maximum value of data, ignoring NaNs
+    """
+    return get_nan_min(data), get_nan_max(data)