.github/workflows/test_and_deploy.yml

@@ -20,7 +20,7 @@ jobs:
       fail-fast: false
       matrix:
         platform: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ['3.8', '3.9', '3.10']
+        python-version: ['3.9', '3.10', '3.11']
 
     steps:
       - uses: actions/checkout@v3

.pre-commit-config.yaml

@@ -1,13 +1,13 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
       - id: check-docstring-first
       - id: end-of-file-fixer
       - id: trailing-whitespace
 
   - repo: https://github.com/psf/black
-    rev: 23.7.0
+    rev: 23.10.1
     hooks:
       - id: black
 
@@ -17,14 +17,14 @@ repos:
       - id: napari-plugin-checks
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.5.1
+    rev: v1.6.1
     hooks:
      - id: mypy
        additional_dependencies: [numpy, matplotlib]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.0.285'
+    rev: 'v0.1.3'
     hooks:
       - id: ruff
 

README.md

@@ -15,32 +15,7 @@ A plugin to create Matplotlib plots from napari layers
 ## Introduction
 `napari-matplotlib` is a bridge between `napari` and `matplotlib`, making it easy to create publication quality `Matplotlib` plots based on the data loaded in `napari` layers.
 
-## Available widgets
-
-### `Slice`
-Plots 1D slices of data along a specified axis.
-![](https://raw.githubusercontent.com/matplotlib/napari-matplotlib/main/examples/slice.png)
-
-### `Histogram`
-Plots histograms of individual image layers, or RGB histograms of an RGB image
-![](https://raw.githubusercontent.com/matplotlib/napari-matplotlib/main/examples/hist.png)
-
-### `Scatter`
-Scatters the values of two similarly sized images layers against each other.
-![](https://raw.githubusercontent.com/matplotlib/napari-matplotlib/main/examples/scatter.png)
-
-## Installation
-
-You can install `napari-matplotlib` via [pip]:
-
-    pip install napari-matplotlib
-
-
-
-To install latest development version :
-
-    pip install git+https://github.com/matplotlib/napari-matplotlib.git
-
+Documentaiton can be found at https://napari-matplotlib.github.io/
 
 ## Contributing
 

docs/changelog.rst

@@ -1,5 +1,13 @@
 Changelog
 =========
+1.2.0
+-----
+Changes
+~~~~~~~
+- Dropped support for Python 3.8, and added support for Python 3.11.
+- Histogram plots of points and vector layers are now coloured with their napari colourmap.
+- Added support for Matplotlib 3.8
+
 1.1.0
 -----
 Additions

pyproject.toml

@@ -23,7 +23,7 @@ profile = "black"
 line_length = 79
 
 [tool.ruff]
-target-version = "py38"
+target-version = "py39"
 select = ["I", "UP", "F", "E", "W", "D"]
 ignore = [
     "D100", # Missing docstring in public module
@@ -45,7 +45,7 @@ fix = true
 convention = "numpy"
 
 [tool.mypy]
-python_version = "3.8"
+python_version = "3.9"
 # Block below are checks that form part of mypy 'strict' mode
 warn_unused_configs = true
 warn_redundant_casts = true

setup.cfg

@@ -9,7 +9,7 @@ author_email = d.stansby@ucl.ac.uk
 license = BSD-3-Clause
 license_files = LICENSE
 classifiers =
-    Development Status :: 3 - Alpha
+    Development Status :: 5 - Production/Stable
     Framework :: napari
     Intended Audience :: Developers
     License :: OSI Approved :: BSD License
@@ -31,7 +31,7 @@ install_requires =
     napari
     numpy
     tinycss2
-python_requires = >=3.8
+python_requires = >=3.9
 include_package_data = True
 package_dir =
     =src
@@ -49,6 +49,7 @@ napari.manifest =
 docs =
     napari[all]==0.4.17
     numpydoc
+    pydantic<2
     pydata-sphinx-theme
     qtgallery
     sphinx

src/napari_matplotlib/base.py

@@ -1,12 +1,12 @@
 import os
 from pathlib import Path
-from typing import List, Optional, Tuple
+from typing import Optional
 
 import matplotlib
 import matplotlib.style as mplstyle
 import napari
-from matplotlib.backends.backend_qtagg import (
-    FigureCanvas,
+from matplotlib.backends.backend_qtagg import (  # type: ignore[attr-defined]
+    FigureCanvasQTAgg,
     NavigationToolbar2QT,
 )
 from matplotlib.figure import Figure
@@ -49,12 +49,10 @@ def __init__(
 
         # Sets figure.* style
         with mplstyle.context(self.mpl_style_sheet_path):
-            self.canvas = FigureCanvas()
+            self.canvas = FigureCanvasQTAgg()  # type: ignore[no-untyped-call]
 
         self.canvas.figure.set_layout_engine("constrained")
-        self.toolbar = NapariNavigationToolbar(
-            self.canvas, parent=self
-        )  # type: ignore[no-untyped-call]
+        self.toolbar = NapariNavigationToolbar(self.canvas, parent=self)
         self._replace_toolbar_icons()
         # callback to update when napari theme changed
         # TODO: this isn't working completely (see issue #140)
@@ -97,7 +95,7 @@ def add_single_axes(self) -> None:
         # Sets axes.* style.
         # Does not set any text styling set by axes.* keys
         with mplstyle.context(self.mpl_style_sheet_path):
-            self.axes = self.figure.subplots()
+            self.axes = self.figure.add_subplot()
 
     def _on_napari_theme_changed(self) -> None:
         """
@@ -184,7 +182,7 @@ class NapariMPLWidget(BaseNapariMPLWidget):
     #: Number of layers taken as input
     n_layers_input = Interval(None, None)
     #: Type of layer taken as input
-    input_layer_types: Tuple[napari.layers.Layer, ...] = (napari.layers.Layer,)
+    input_layer_types: tuple[napari.layers.Layer, ...] = (napari.layers.Layer,)
 
     def __init__(
         self,
@@ -193,7 +191,7 @@ def __init__(
     ):
         super().__init__(napari_viewer=napari_viewer, parent=parent)
         self._setup_callbacks()
-        self.layers: List[napari.layers.Layer] = []
+        self.layers: list[napari.layers.Layer] = []
 
         helper_text = self.n_layers_input._helper_text
         if helper_text is not None:
@@ -260,7 +258,7 @@ def _draw(self) -> None:
             isinstance(layer, self.input_layer_types) for layer in self.layers
         ):
             self.draw()
-        self.canvas.draw()
+        self.canvas.draw()  # type: ignore[no-untyped-call]
 
     def clear(self) -> None:
         """
@@ -309,8 +307,8 @@ def clear(self) -> None:
 class NapariNavigationToolbar(NavigationToolbar2QT):
     """Custom Toolbar style for Napari."""
 
-    def __init__(self, *args, **kwargs):  # type: ignore[no-untyped-def]
-        super().__init__(*args, **kwargs)
+    def __init__(self, *args, **kwargs) -> None:  # type: ignore[no-untyped-def]
+        super().__init__(*args, **kwargs)  # type: ignore[no-untyped-call]
         self.setIconSize(
             from_napari_css_get_size_of(
                 "QtViewerPushButton", fallback=(28, 28)
@@ -319,7 +317,7 @@ def __init__(self, *args, **kwargs):  # type: ignore[no-untyped-def]
 
     def _update_buttons_checked(self) -> None:
         """Update toggle tool icons when selected/unselected."""
-        super()._update_buttons_checked()
+        super()._update_buttons_checked()  # type: ignore[no-untyped-call]
         icon_dir = self.parentWidget()._get_path_to_icon()
 
         # changes pan/zoom icons depending on state (checked or not)

src/napari_matplotlib/histogram.py

@@ -1,8 +1,9 @@
-from typing import Any, List, Optional, Tuple
+from typing import Any, Optional, cast
 
 import napari
 import numpy as np
 import numpy.typing as npt
+from matplotlib.container import BarContainer
 from qtpy.QtWidgets import QComboBox, QLabel, QVBoxLayout, QWidget
 
 from .base import SingleAxesWidget
@@ -107,7 +108,7 @@ def _set_axis_keys(self, x_axis_key: str) -> None:
         self._x_axis_key = x_axis_key
         self._draw()
 
-    def _get_valid_axis_keys(self) -> List[str]:
+    def _get_valid_axis_keys(self) -> list[str]:
         """
         Get the valid axis keys from the layer FeatureTable.
 
@@ -122,7 +123,7 @@ def _get_valid_axis_keys(self) -> List[str]:
         else:
             return self.layers[0].features.keys()
 
-    def _get_data(self) -> Tuple[Optional[npt.NDArray[Any]], str]:
+    def _get_data(self) -> tuple[Optional[npt.NDArray[Any]], str]:
         """Get the plot data.
 
         Returns
@@ -162,12 +163,39 @@ def on_update_layers(self) -> None:
 
     def draw(self) -> None:
         """Clear the axes and histogram the currently selected layer/slice."""
+        # get the colormap from the layer depending on its type
+        if isinstance(self.layers[0], napari.layers.Points):
+            colormap = self.layers[0].face_colormap
+            self.layers[0].face_color = self.x_axis_key
+        elif isinstance(self.layers[0], napari.layers.Vectors):
+            colormap = self.layers[0].edge_colormap
+            self.layers[0].edge_color = self.x_axis_key
+        else:
+            colormap = None
+
+        # apply new colors to the layer
+        self.viewer.layers[self.layers[0].name].refresh_colors(True)
+        self.viewer.layers[self.layers[0].name].refresh()
+
+        # Draw the histogram
         data, x_axis_name = self._get_data()
 
         if data is None:
             return
 
-        self.axes.hist(data, bins=50, edgecolor="white", linewidth=0.3)
+        _, bins, patches = self.axes.hist(
+            data, bins=50, edgecolor="white", linewidth=0.3
+        )
+        patches = cast(BarContainer, patches)
+
+        # recolor the histogram plot
+        if colormap is not None:
+            self.bins_norm = (bins - bins.min()) / (bins.max() - bins.min())
+            colors = colormap.map(self.bins_norm)
+
+            # Set histogram style:
+            for idx, patch in enumerate(patches):
+                patch.set_facecolor(colors[idx])
 
         # set ax labels
         self.axes.set_xlabel(x_axis_name)

src/napari_matplotlib/scatter.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, Optional, Union
 
 import napari
 import numpy.typing as npt
@@ -40,7 +40,7 @@ def draw(self) -> None:
         self.axes.set_xlabel(x_axis_name)
         self.axes.set_ylabel(y_axis_name)
 
-    def _get_data(self) -> Tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
+    def _get_data(self) -> tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
         """
         Get the plot data.
 
@@ -67,7 +67,7 @@ class ScatterWidget(ScatterBaseWidget):
     n_layers_input = Interval(2, 2)
     input_layer_types = (napari.layers.Image,)
 
-    def _get_data(self) -> Tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
+    def _get_data(self) -> tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
         """
         Get the plot data.
 
@@ -106,7 +106,7 @@ def __init__(
 
         self.layout().addLayout(QVBoxLayout())
 
-        self._selectors: Dict[str, QComboBox] = {}
+        self._selectors: dict[str, QComboBox] = {}
         for dim in ["x", "y"]:
             self._selectors[dim] = QComboBox()
             # Re-draw when combo boxes are updated
@@ -147,7 +147,7 @@ def y_axis_key(self, key: str) -> None:
         self._selectors["y"].setCurrentText(key)
         self._draw()
 
-    def _get_valid_axis_keys(self) -> List[str]:
+    def _get_valid_axis_keys(self) -> list[str]:
         """
         Get the valid axis keys from the layer FeatureTable.
 
@@ -186,7 +186,7 @@ def draw(self) -> None:
         if self._ready_to_scatter():
             super().draw()
 
-    def _get_data(self) -> Tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
+    def _get_data(self) -> tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
         """
         Get the plot data from the ``features`` attribute of the first
         selected layer.

src/napari_matplotlib/slice.py

@@ -1,4 +1,4 @@
-from typing import Any, List, Optional, Tuple
+from typing import Any, Optional
 
 import matplotlib.ticker as mticker
 import napari
@@ -99,7 +99,7 @@ def current_dim_index(self) -> int:
         return self._dim_names.index(self.current_dim_name)
 
     @property
-    def _dim_names(self) -> List[str]:
+    def _dim_names(self) -> list[str]:
         """
         List of dimension names. This is a property as it varies depending on the
         dimensionality of the currently selected data.
@@ -111,7 +111,7 @@ def _dim_names(self) -> List[str]:
         else:
             raise RuntimeError("Don't know how to handle ndim != 2 or 3")
 
-    def _get_xy(self) -> Tuple[npt.NDArray[Any], npt.NDArray[Any]]:
+    def _get_xy(self) -> tuple[npt.NDArray[Any], npt.NDArray[Any]]:
         """
         Get data for plotting.
         """

src/napari_matplotlib/tests/scatter/test_scatter_features.py

@@ -1,5 +1,5 @@
 from copy import deepcopy
-from typing import Any, Dict, Tuple
+from typing import Any
 
 import numpy as np
 import numpy.typing as npt
@@ -34,7 +34,7 @@ def test_features_scatter_widget_2D(
 
 
 def make_labels_layer_with_features() -> (
-    Tuple[npt.NDArray[np.uint16], Dict[str, Any]]
+    tuple[npt.NDArray[np.uint16], dict[str, Any]]
 ):
     label_image: npt.NDArray[np.uint16] = np.zeros((100, 100), dtype=np.uint16)
     for label_value, start_index in enumerate([10, 30, 50], start=1):