Note
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nD shapesΒΆ
Display one 4-D image layer using the add_image API
sliced: nshapes 128, mask shape (128, 128, 128, 128), labels_shape (128, 128, 128), array_shape, (128, 5, 3)
broadcast: nshapes 1, mask shape (1, 128, 128), labels_shape (128, 128), array_shape, (1, 4, 2)
import numpy as np
from skimage import data
import napari
blobs = data.binary_blobs(
length=128, blob_size_fraction=0.05, n_dim=3, volume_fraction=0.1
).astype(float)
viewer = napari.view_image(blobs.astype(float))
# create one random polygon per "plane"
planes = np.tile(np.arange(128).reshape((128, 1, 1)), (1, 5, 1))
np.random.seed(0)
corners = np.random.uniform(0, 128, size=(128, 5, 2))
shapes = np.concatenate((planes, corners), axis=2)
base_cols = ['red', 'green', 'blue', 'white', 'yellow', 'magenta', 'cyan']
colors = np.random.choice(base_cols, size=128)
layer = viewer.add_shapes(
np.array(shapes),
shape_type='polygon',
face_color=colors,
name='sliced',
)
masks = layer.to_masks(mask_shape=(128, 128, 128))
labels = layer.to_labels(labels_shape=(128, 128, 128))
shape_array = np.array(layer.data)
print(
f'sliced: nshapes {layer.nshapes}, mask shape {masks.shape}, '
f'labels_shape {labels.shape}, array_shape, {shape_array.shape}'
)
corners = np.random.uniform(0, 128, size=(2, 2))
layer = viewer.add_shapes(corners, shape_type='rectangle', name='broadcasted')
masks = layer.to_masks(mask_shape=(128, 128))
labels = layer.to_labels(labels_shape=(128, 128))
shape_array = np.array(layer.data)
print(
f'broadcast: nshapes {layer.nshapes}, mask shape {masks.shape}, '
f'labels_shape {labels.shape}, array_shape, {shape_array.shape}'
)
if __name__ == '__main__':
napari.run()