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test_scatter.py
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from typing import Any, Dict, Tuple
import numpy as np
import numpy.typing as npt
from napari_matplotlib import FeaturesScatterWidget, ScatterWidget
def test_scatter(make_napari_viewer):
# Smoke test adding a scatter widget
viewer = make_napari_viewer()
viewer.add_image(np.random.random((100, 100)))
viewer.add_image(np.random.random((100, 100)))
ScatterWidget(viewer)
def test_features_scatter_widget(make_napari_viewer):
# Smoke test adding a features scatter widget
viewer = make_napari_viewer()
viewer.add_image(np.random.random((100, 100)))
viewer.add_labels(np.random.randint(0, 5, (100, 100)))
FeaturesScatterWidget(viewer)
def make_labels_layer_with_features() -> (
Tuple[npt.NDArray[np.uint16], Dict[str, Any]]
):
label_image = np.zeros((100, 100), dtype=np.uint16)
for label_value, start_index in enumerate([10, 30, 50], start=1):
end_index = start_index + 10
label_image[start_index:end_index, start_index:end_index] = label_value
feature_table = {
"index": [1, 2, 3],
"feature_0": np.random.random((3,)),
"feature_1": np.random.random((3,)),
"feature_2": np.random.random((3,)),
}
return label_image, feature_table
def test_features_scatter_get_data(make_napari_viewer):
"""Test the get data method"""
# make the label image
label_image, feature_table = make_labels_layer_with_features()
viewer = make_napari_viewer()
labels_layer = viewer.add_labels(label_image, features=feature_table)
scatter_widget = FeaturesScatterWidget(viewer)
# select the labels layer
viewer.layers.selection = [labels_layer]
x_column = "feature_0"
scatter_widget.x_axis_key = x_column
y_column = "feature_2"
scatter_widget.y_axis_key = y_column
data, x_axis_name, y_axis_name = scatter_widget._get_data()
np.testing.assert_allclose(
data, np.stack((feature_table[x_column], feature_table[y_column]))
)
assert x_axis_name == x_column.replace("_", " ")
assert y_axis_name == y_column.replace("_", " ")
def test_get_valid_axis_keys(make_napari_viewer):
"""Test the values returned from
FeaturesScatterWidget._get_valid_keys() when there
are valid keys.
"""
# make the label image
label_image, feature_table = make_labels_layer_with_features()
viewer = make_napari_viewer()
labels_layer = viewer.add_labels(label_image, features=feature_table)
scatter_widget = FeaturesScatterWidget(viewer)
viewer.layers.selection = [labels_layer]
valid_keys = scatter_widget._get_valid_axis_keys()
assert set(valid_keys) == set(feature_table.keys())
def test_get_valid_axis_keys_no_valid_keys(make_napari_viewer):
"""Test the values returned from
FeaturesScatterWidget._get_valid_keys() when there
are not valid keys.
"""
# make the label image
label_image, _ = make_labels_layer_with_features()
viewer = make_napari_viewer()
labels_layer = viewer.add_labels(label_image)
image_layer = viewer.add_image(np.random.random((100, 100)))
scatter_widget = FeaturesScatterWidget(viewer)
# no features in a label image
viewer.layers.selection = [labels_layer]
valid_keys = scatter_widget._get_valid_axis_keys()
assert set(valid_keys) == set()
# image layer doesn't have features
viewer.layers.selection = [image_layer]
valid_keys = scatter_widget._get_valid_axis_keys()
assert set(valid_keys) == set()