1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
|
"""
nD vectors
==========
Display two vectors layers ontop of a 4-D image layer. One of the vectors
layers is 3D and "sliced" with a different set of vectors appearing on
different 3D slices. Another is 2D and "broadcast" with the same vectors
apprearing on each slice.
.. tags:: visualization-nD
"""
import numpy as np
from skimage import data
import napari
blobs = np.stack(
[
data.binary_blobs(
length=128, blob_size_fraction=0.05, n_dim=3, volume_fraction=f
)
for f in np.linspace(0.05, 0.5, 10)
],
axis=0,
)
viewer = napari.Viewer()
layer = viewer.add_image(blobs.astype(float))
# sample vector coord-like data
n = 200
pos = np.zeros((n, 2, 2), dtype=np.float32)
phi_space = np.linspace(0, 4 * np.pi, n)
radius_space = np.linspace(0, 20, n)
# assign x-y position
pos[:, 0, 0] = radius_space * np.cos(phi_space) + 64
pos[:, 0, 1] = radius_space * np.sin(phi_space) + 64
# assign x-y projection
pos[:, 1, 0] = 2 * radius_space * np.cos(phi_space)
pos[:, 1, 1] = 2 * radius_space * np.sin(phi_space)
planes = np.round(np.linspace(0, 128, n)).astype(int)
planes = np.concatenate(
(planes.reshape((n, 1, 1)), np.zeros((n, 1, 1))), axis=1
)
vectors = np.concatenate((planes, pos), axis=2)
# add the sliced vectors
layer = viewer.add_vectors(
vectors, edge_width=0.4, name='sliced vectors', edge_color='blue'
)
viewer.dims.ndisplay = 3
if __name__ == '__main__':
napari.run()
|
