Merge branch 'main' into feat/hist-bin-params

Author: p-j-smith

.pre-commit-config.yaml

@@ -7,7 +7,7 @@ repos:
       - id: trailing-whitespace
 
   - repo: https://github.com/psf/black
-    rev: 23.12.1
+    rev: 24.1.1
     hooks:
       - id: black
 
@@ -24,7 +24,7 @@ repos:
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.1.11'
+    rev: 'v0.2.1'
     hooks:
       - id: ruff
 

docs/changelog.rst

@@ -1,5 +1,13 @@
 Changelog
 =========
+2.0.1
+-----
+Bug fixes
+~~~~~~~~~
+- Fixed using the ``HistogramWidget`` with layers containing multiscale data.
+- Make sure ``HistogramWidget`` uses 100 bins (not 99) when floating point data is
+  selected.
+
 2.0.0
 -----
 Changes to custom theming

examples/histogram.py

@@ -2,6 +2,7 @@
 Histograms
 ==========
 """
+
 import napari
 
 viewer = napari.Viewer()

examples/scatter.py

@@ -2,6 +2,7 @@
 Scatter plots
 =============
 """
+
 import napari
 
 viewer = napari.Viewer()

examples/slice.py

@@ -2,6 +2,7 @@
 1D slices
 =========
 """
+
 import napari
 
 viewer = napari.Viewer()

pyproject.toml

@@ -6,14 +6,15 @@ build-backend = "setuptools.build_meta"
 write_to = "src/napari_matplotlib/_version.py"
 
 [tool.pytest.ini_options]
-qt_api = "pyqt6"
-addopts = "--mpl --mpl-baseline-relative"
 filterwarnings = [
     "error",
+    "ignore:(?s).*Pyarrow will become a required dependency of pandas",
     # Coming from vispy
     "ignore:distutils Version classes are deprecated:DeprecationWarning",
     "ignore:`np.bool8` is a deprecated alias for `np.bool_`:DeprecationWarning",
 ]
+qt_api = "pyqt6"
+addopts = "--mpl --mpl-baseline-relative"
 
 [tool.black]
 line-length = 79

src/napari_matplotlib/histogram.py

@@ -4,6 +4,8 @@
 import numpy as np
 import numpy.typing as npt
 from matplotlib.container import BarContainer
+from napari.layers import Image
+from napari.layers._multiscale_data import MultiScaleData
 from qtpy.QtWidgets import (
     QAbstractSpinBox,
     QComboBox,
@@ -31,8 +33,9 @@ def _get_bins(data: npt.NDArray[Any]) -> npt.NDArray[Any]:
         step = np.ceil(np.ptp(data) / 100)
         return np.arange(np.min(data), np.max(data) + step, step)
     else:
-        # For other data types, just have 99 evenly spaced bins
-        return np.linspace(np.min(data), np.max(data), 100)
+        # For other data types, just have 100 evenly spaced bins
+        # (and 101 bin edges)
+        return np.linspace(np.min(data), np.max(data), 101)
 
 
 class HistogramWidget(SingleAxesWidget):
@@ -112,7 +115,7 @@ def on_update_layers(self) -> None:
         if not self.layers:
             return
 
-        # Reset to bin start, stop and step
+        # Reset the bin start, stop and step values based on new layer data
         layer_data = self._get_layer_data(self.layers[0])
         self.autoset_widget_bins(data=layer_data)
 
@@ -189,12 +192,16 @@ def bins_num(self, num: int) -> None:
 
     def _get_layer_data(self, layer: napari.layers.Layer) -> npt.NDArray[Any]:
         """Get the data associated with a given layer"""
-        if layer.data.ndim - layer.rgb == 3:
+        data = layer.data
+
+        if isinstance(layer.data, MultiScaleData):
+            data = data[layer.data_level]
+
+        if layer.ndim - layer.rgb == 3:
             # 3D data, can be single channel or RGB
-            data = layer.data[self.current_z]
+            # Slice in z dimension
+            data = data[self.current_z]
             self.axes.set_title(f"z={self.current_z}")
-        else:
-            data = layer.data
 
         # Read data into memory if it's a dask array
         data = np.asarray(data)
@@ -205,7 +212,7 @@ def draw(self) -> None:
         """
         Clear the axes and histogram the currently selected layer/slice.
         """
-        layer = self.layers[0]
+        layer: Image = self.layers[0]
         data = self._get_layer_data(layer)
 
         # Important to calculate bins after slicing 3D data, to avoid reading

src/napari_matplotlib/tests/baseline/test_feature_histogram_points.png

@@ -69,7 +69,10 @@ def test_fallback_if_missing_dimensions(mocker):
     test_css = " Flobble { background-color: rgb(0, 97, 163); } "
     mocker.patch("napari.qt.get_current_stylesheet").return_value = test_css
     with pytest.warns(RuntimeWarning, match="Unable to find DimensionToken"):
-        assert from_napari_css_get_size_of("Flobble", (1, 2)) == QSize(1, 2)
+        with pytest.warns(RuntimeWarning, match="Unable to find Flobble"):
+            assert from_napari_css_get_size_of("Flobble", (1, 2)) == QSize(
+                1, 2
+            )
 
 
 def test_fallback_if_prelude_not_in_css():