Add feature histogram widget

src/napari_matplotlib/__init__.py

@@ -4,6 +4,7 @@
     __version__ = "unknown"
 
 
+from .feature_histogram import *  # NoQA
 from .histogram import *  # NoQA
 from .scatter import *  # NoQA
 from .slice import *  # NoQA

src/napari_matplotlib/feature_histogram.py

@@ -0,0 +1,82 @@
+import numpy as np
+
+from .base import NapariMPLWidget
+from qtpy.QtWidgets import QComboBox, QLabel, QCheckBox
+from qtpy.QtCore import QSize
+
+__all__ = ["FeatureHistogramWidget"]
+
+import napari
+
+from .util import Interval
+
+
+class FeatureHistogramWidget(NapariMPLWidget):
+    """
+    Display a histogram of the features stored in the currently selected layer.
+    """
+
+    n_layers_input = Interval(1, 1)
+    input_layer_types = (napari.layers.Image, napari.layers.Labels, napari.layers.Points, napari.layers.Surface)
+
+    def __init__(self, napari_viewer: napari.viewer.Viewer, column_name: str = None):
+        super().__init__(napari_viewer)
+        self.axes = self.canvas.figure.subplots()
+
+        # Feature selection
+        self.layout().addWidget(QLabel("Feature:"))
+        self.plot_column_name = QComboBox()
+        self.plot_column_name.currentIndexChanged.connect(self._draw)
+        self.layout().addWidget(self.plot_column_name)
+
+        # Logarithmic plot yes/no
+        self.logarithmic_plot = QCheckBox("Logarithmic")
+        self.logarithmic_plot.stateChanged.connect(self._draw)
+        self.layout().addWidget(self.logarithmic_plot)
+
+        # listen to laer changed
+        napari_viewer.layers.selection.events.changed.connect(self.update_available_columns)
+
+        # setup GUI
+        self.setMinimumSize(QSize(400, 400))
+        self.update_layers(None)
+        self.update_available_columns()
+
+    def update_available_columns(self):
+        """
+        Update the feature list pulldown as soon as the user changes the selected layer
+        """
+        selected_layer = self.layers[0]
+
+        former_plot_column_index = self.plot_column_name.currentIndex()
+
+        if selected_layer is not None:
+            features = selected_layer.features
+            if features is not None:
+                self.plot_column_name.clear()
+                self.plot_column_name.addItems(list(features.keys()))
+
+        self.plot_column_name.setCurrentIndex(former_plot_column_index)
+
+    def clear(self) -> None:
+        self.axes.clear()
+
+    def draw(self) -> None:
+        """
+        Clear the axes and histogram the currently selected feature.
+        """
+        layer = self.layers[0]
+        if layer is None:
+            self.clear()
+            return
+
+        selected_column = self.plot_column_name.currentText()
+        if selected_column is not None and len(selected_column) > 0:
+            data = layer.features[selected_column]
+            bins = np.linspace(np.min(data), np.max(data), 100)
+            self.clear()
+            self.axes.hist(data,
+                           bins=bins,
+                           label=layer.name + " / " + selected_column,
+                           log=self.logarithmic_plot.isChecked())
+            self.axes.legend()

src/napari_matplotlib/napari.yaml

@@ -2,6 +2,10 @@ name: napari-matplotlib
 display_name: napari Matplotlib
 contributions:
   commands:
+    - id: napari-matplotlib.feature_histogram
+      python_name: napari_matplotlib:FeatureHistogramWidget
+      title: Make a feature histogram
+
     - id: napari-matplotlib.histogram
       python_name: napari_matplotlib:HistogramWidget
       title: Make a histogram
@@ -19,6 +23,9 @@ contributions:
       title: Plot a 1D slice
 
   widgets:
+    - command: napari-matplotlib.feature_histogram
+      display_name: Feature Histogram
+
     - command: napari-matplotlib.histogram
       display_name: Histogram
 

src/napari_matplotlib/tests/test_feature_histogram.py

@@ -0,0 +1,22 @@
+from napari_matplotlib import FeatureHistogramWidget
+import numpy as np
+
+def test_example_q_widget(make_napari_viewer):
+    # Smoke test adding a histogram widget
+    viewer = make_napari_viewer()
+
+    image = np.asarray([[0, 1], [2, 1]])
+    labels = image.astype(int)
+
+
+    viewer.add_image(image)
+
+    labels_layer = viewer.add_labels(labels)
+
+    labels_layer.features = {
+        'labels': [1, 2],
+        'area': [2, 1],
+        'aspect_ratio': [2, 1]
+    }
+
+    FeatureHistogramWidget(viewer)