Note
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Points over time#
import dask.array as da
import numpy as np
import napari
image4d = da.random.random(
(4000, 32, 256, 256),
chunks=(1, 32, 256, 256),
)
pts_coordinates = np.random.random((50000, 3)) * image4d.shape[1:]
pts_values = da.random.random((50000, 4000), chunks=(50000, 1))
viewer = napari.Viewer(ndisplay=3)
image_layer = viewer.add_image(
image4d, opacity=0.5
)
pts_layer = viewer.add_points(
pts_coordinates,
features={'value': np.asarray(pts_values[:, 0])},
face_color='value',
size=2,
)
def set_pts_features(pts_layer, values_table, step):
# step is a 4D coordinate with the current slider position for each dim
column = step[0] # grab the leading ("time") coordinate
pts_layer.features['value'] = np.asarray(values_table[:, column])
pts_layer.face_color = 'value' # force features refresh
viewer.dims.events.current_step.connect(
lambda event: set_pts_features(pts_layer, pts_values, event.value)
)
if __name__ == '__main__':
napari.run()