diff --git a/baseline/test_feature_histogram2.png b/baseline/test_feature_histogram2.png
new file mode 100644
index 00000000..b7bb19e0
Binary files /dev/null and b/baseline/test_feature_histogram2.png differ
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 2304fecf..6f77e0c3 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -1,7 +1,11 @@
Changelog
=========
-1.0.3
+1.1.0
-----
+Additions
+~~~~~~~~~
+- Added a widget to draw a histogram of features.
+
Changes
~~~~~~~
- The slice widget is now limited to slicing along the x/y dimensions. Support
diff --git a/docs/user_guide.rst b/docs/user_guide.rst
index 0872e540..fbd48db1 100644
--- a/docs/user_guide.rst
+++ b/docs/user_guide.rst
@@ -30,6 +30,7 @@ These widgets plot the data stored in the ``.features`` attribute of individual
Currently available are:
- 2D scatter plots of two features against each other.
+- Histograms of individual features.
To use these:
diff --git a/src/napari_matplotlib/features.py b/src/napari_matplotlib/features.py
new file mode 100644
index 00000000..34abf104
--- /dev/null
+++ b/src/napari_matplotlib/features.py
@@ -0,0 +1,9 @@
+from napari.layers import Labels, Points, Shapes, Tracks, Vectors
+
+FEATURES_LAYER_TYPES = (
+ Labels,
+ Points,
+ Shapes,
+ Tracks,
+ Vectors,
+)
diff --git a/src/napari_matplotlib/histogram.py b/src/napari_matplotlib/histogram.py
index ab098f38..66aa7acc 100644
--- a/src/napari_matplotlib/histogram.py
+++ b/src/napari_matplotlib/histogram.py
@@ -1,13 +1,15 @@
-from typing import Optional
+from typing import Any, List, Optional, Tuple
import napari
import numpy as np
-from qtpy.QtWidgets import QWidget
+import numpy.typing as npt
+from qtpy.QtWidgets import QComboBox, QLabel, QVBoxLayout, QWidget
from .base import SingleAxesWidget
+from .features import FEATURES_LAYER_TYPES
from .util import Interval
-__all__ = ["HistogramWidget"]
+__all__ = ["HistogramWidget", "FeaturesHistogramWidget"]
_COLORS = {"r": "tab:red", "g": "tab:green", "b": "tab:blue"}
@@ -61,3 +63,112 @@ def draw(self) -> None:
self.axes.hist(data.ravel(), bins=bins, label=layer.name)
self.axes.legend()
+
+
+class FeaturesHistogramWidget(SingleAxesWidget):
+ """
+ Display a histogram of selected feature attached to selected layer.
+ """
+
+ n_layers_input = Interval(1, 1)
+ # All layers that have a .features attributes
+ input_layer_types = FEATURES_LAYER_TYPES
+
+ def __init__(
+ self,
+ napari_viewer: napari.viewer.Viewer,
+ parent: Optional[QWidget] = None,
+ ):
+ super().__init__(napari_viewer, parent=parent)
+
+ self.layout().addLayout(QVBoxLayout())
+ self._key_selection_widget = QComboBox()
+ self.layout().addWidget(QLabel("Key:"))
+ self.layout().addWidget(self._key_selection_widget)
+
+ self._key_selection_widget.currentTextChanged.connect(
+ self._set_axis_keys
+ )
+
+ self._update_layers(None)
+
+ @property
+ def x_axis_key(self) -> Optional[str]:
+ """Key to access x axis data from the FeaturesTable"""
+ return self._x_axis_key
+
+ @x_axis_key.setter
+ def x_axis_key(self, key: Optional[str]) -> None:
+ self._x_axis_key = key
+ self._draw()
+
+ def _set_axis_keys(self, x_axis_key: str) -> None:
+ """Set both axis keys and then redraw the plot"""
+ self._x_axis_key = x_axis_key
+ self._draw()
+
+ def _get_valid_axis_keys(self) -> List[str]:
+ """
+ Get the valid axis keys from the layer FeatureTable.
+
+ Returns
+ -------
+ axis_keys : List[str]
+ The valid axis keys in the FeatureTable. If the table is empty
+ or there isn't a table, returns an empty list.
+ """
+ if len(self.layers) == 0 or not (hasattr(self.layers[0], "features")):
+ return []
+ else:
+ return self.layers[0].features.keys()
+
+ def _get_data(self) -> Tuple[Optional[npt.NDArray[Any]], str]:
+ """Get the plot data.
+
+ Returns
+ -------
+ data : List[np.ndarray]
+ List contains X and Y columns from the FeatureTable. Returns
+ an empty array if nothing to plot.
+ x_axis_name : str
+ The title to display on the x axis. Returns
+ an empty string if nothing to plot.
+ """
+ if not hasattr(self.layers[0], "features"):
+ # if the selected layer doesn't have a featuretable,
+ # skip draw
+ return None, ""
+
+ feature_table = self.layers[0].features
+
+ if (len(feature_table) == 0) or (self.x_axis_key is None):
+ return None, ""
+
+ data = feature_table[self.x_axis_key]
+ x_axis_name = self.x_axis_key.replace("_", " ")
+
+ return data, x_axis_name
+
+ def on_update_layers(self) -> None:
+ """
+ Called when the layer selection changes by ``self.update_layers()``.
+ """
+ # reset the axis keys
+ self._x_axis_key = None
+
+ # Clear combobox
+ self._key_selection_widget.clear()
+ self._key_selection_widget.addItems(self._get_valid_axis_keys())
+
+ def draw(self) -> None:
+ """Clear the axes and histogram the currently selected layer/slice."""
+ data, x_axis_name = self._get_data()
+
+ if data is None:
+ return
+
+ self.axes.hist(data, bins=50, edgecolor="white", linewidth=0.3)
+
+ # set ax labels
+ self.axes.set_xlabel(x_axis_name)
+ self.axes.set_ylabel("Counts [#]")
diff --git a/src/napari_matplotlib/napari.yaml b/src/napari_matplotlib/napari.yaml
index b736592b..71af0ca6 100644
--- a/src/napari_matplotlib/napari.yaml
+++ b/src/napari_matplotlib/napari.yaml
@@ -14,6 +14,10 @@ contributions:
python_name: napari_matplotlib:FeaturesScatterWidget
title: Make a scatter plot of layer features
+ - id: napari-matplotlib.features_histogram
+ python_name: napari_matplotlib:FeaturesHistogramWidget
+ title: Plot feature histograms
+
- id: napari-matplotlib.slice
python_name: napari_matplotlib:SliceWidget
title: Plot a 1D slice
@@ -28,5 +32,8 @@ contributions:
- command: napari-matplotlib.features_scatter
display_name: FeaturesScatter
+ - command: napari-matplotlib.features_histogram
+ display_name: FeaturesHistogram
+
- command: napari-matplotlib.slice
display_name: 1D slice
diff --git a/src/napari_matplotlib/scatter.py b/src/napari_matplotlib/scatter.py
index db86c7f3..a4148bd2 100644
--- a/src/napari_matplotlib/scatter.py
+++ b/src/napari_matplotlib/scatter.py
@@ -5,6 +5,7 @@
from qtpy.QtWidgets import QComboBox, QLabel, QVBoxLayout, QWidget
from .base import SingleAxesWidget
+from .features import FEATURES_LAYER_TYPES
from .util import Interval
__all__ = ["ScatterBaseWidget", "ScatterWidget", "FeaturesScatterWidget"]
@@ -94,13 +95,7 @@ class FeaturesScatterWidget(ScatterBaseWidget):
n_layers_input = Interval(1, 1)
# All layers that have a .features attributes
- input_layer_types = (
- napari.layers.Labels,
- napari.layers.Points,
- napari.layers.Shapes,
- napari.layers.Tracks,
- napari.layers.Vectors,
- )
+ input_layer_types = FEATURES_LAYER_TYPES
def __init__(
self,
diff --git a/src/napari_matplotlib/tests/baseline/test_feature_histogram.png b/src/napari_matplotlib/tests/baseline/test_feature_histogram.png
new file mode 100644
index 00000000..1892af44
Binary files /dev/null and b/src/napari_matplotlib/tests/baseline/test_feature_histogram.png differ
diff --git a/src/napari_matplotlib/tests/baseline/test_feature_histogram2.png b/src/napari_matplotlib/tests/baseline/test_feature_histogram2.png
new file mode 100644
index 00000000..b7bb19e0
Binary files /dev/null and b/src/napari_matplotlib/tests/baseline/test_feature_histogram2.png differ
diff --git a/src/napari_matplotlib/tests/test_histogram.py b/src/napari_matplotlib/tests/test_histogram.py
index 4d170014..006c042f 100644
--- a/src/napari_matplotlib/tests/test_histogram.py
+++ b/src/napari_matplotlib/tests/test_histogram.py
@@ -1,8 +1,13 @@
from copy import deepcopy
+import numpy as np
import pytest
-from napari_matplotlib import HistogramWidget
+from napari_matplotlib import FeaturesHistogramWidget, HistogramWidget
+from napari_matplotlib.tests.helpers import (
+ assert_figures_equal,
+ assert_figures_not_equal,
+)
@pytest.mark.mpl_image_compare
@@ -28,3 +33,90 @@ def test_histogram_3D(make_napari_viewer, brain_data):
# Need to return a copy, as original figure is too eagerley garbage
# collected by the widget
return deepcopy(fig)
+
+
+def test_feature_histogram(make_napari_viewer):
+ n_points = 1000
+ random_points = np.random.random((n_points, 3)) * 10
+ feature1 = np.random.random(n_points)
+ feature2 = np.random.normal(size=n_points)
+
+ viewer = make_napari_viewer()
+ viewer.add_points(
+ random_points,
+ properties={"feature1": feature1, "feature2": feature2},
+ name="points1",
+ )
+ viewer.add_points(
+ random_points,
+ properties={"feature1": feature1, "feature2": feature2},
+ name="points2",
+ )
+
+ widget = FeaturesHistogramWidget(viewer)
+ viewer.window.add_dock_widget(widget)
+
+ # Check whether changing the selected key changes the plot
+ widget._set_axis_keys("feature1")
+ fig1 = deepcopy(widget.figure)
+
+ widget._set_axis_keys("feature2")
+ assert_figures_not_equal(widget.figure, fig1)
+
+ # check whether selecting a different layer produces the same plot
+ viewer.layers.selection.clear()
+ viewer.layers.selection.add(viewer.layers[1])
+ assert_figures_equal(widget.figure, fig1)
+
+
+@pytest.mark.mpl_image_compare
+def test_feature_histogram2(make_napari_viewer):
+ import numpy as np
+
+ np.random.seed(0)
+ n_points = 1000
+ random_points = np.random.random((n_points, 3)) * 10
+ feature1 = np.random.random(n_points)
+ feature2 = np.random.normal(size=n_points)
+
+ viewer = make_napari_viewer()
+ viewer.add_points(
+ random_points,
+ properties={"feature1": feature1, "feature2": feature2},
+ name="points1",
+ )
+ viewer.add_points(
+ random_points,
+ properties={"feature1": feature1, "feature2": feature2},
+ name="points2",
+ )
+
+ widget = FeaturesHistogramWidget(viewer)
+ viewer.window.add_dock_widget(widget)
+ widget._set_axis_keys("feature1")
+
+ fig = FeaturesHistogramWidget(viewer).figure
+ return deepcopy(fig)
+
+
+def test_change_layer(make_napari_viewer, brain_data, astronaut_data):
+ viewer = make_napari_viewer()
+ widget = HistogramWidget(viewer)
+
+ viewer.add_image(brain_data[0], **brain_data[1])
+ viewer.add_image(astronaut_data[0], **astronaut_data[1])
+
+ # Select first layer
+ viewer.layers.selection.clear()
+ viewer.layers.selection.add(viewer.layers[0])
+ fig1 = deepcopy(widget.figure)
+
+ # Re-selecting first layer should produce identical plot
+ viewer.layers.selection.clear()
+ viewer.layers.selection.add(viewer.layers[0])
+ assert_figures_equal(widget.figure, fig1)
+
+ # Plotting the second layer should produce a different plot
+ viewer.layers.selection.clear()
+ viewer.layers.selection.add(viewer.layers[1])
+ assert_figures_not_equal(widget.figure, fig1)