Hisogram of features

import napari
import numpy as np
import numpy.typing as npt
from skimage.measure import regionprops_table

# make a test label image
label_image: npt.NDArray[np.uint16] = np.zeros((100, 100), dtype=np.uint16)

label_image[10:20, 10:20] = 1
label_image[50:70, 50:70] = 2

feature_table_1 = regionprops_table(
    label_image, properties=("label", "area", "perimeter")
)
feature_table_1["index"] = feature_table_1["label"]

# make the points data
n_points = 100
points_data = 100 * np.random.random((100, 2))
points_features = {
    "feature_0": np.random.random((n_points,)),
    "feature_1": np.random.random((n_points,)),
    "feature_2": np.random.random((n_points,)),
}

# create the viewer
viewer = napari.Viewer()
viewer.add_labels(label_image, features=feature_table_1)
viewer.add_points(points_data, features=points_features)

# make the widget
viewer.window.add_plugin_dock_widget(
    plugin_name="napari-matplotlib", widget_name="FeaturesHistogram"
)

if __name__ == "__main__":
    napari.run()