We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
... And which side of the loop is chosen depends on whether the SciPy version used is 1.10 or earlier or 1.11 or later. 😕
Here's a reproducible example:
import napari import numpy as np from skimage.draw import random_shapes from skimage.morphology import skeletonize from skan import Skeleton, summarize # Generate a random skeletons, first is a skeleton with a closed loop with side branches kwargs = {"image_shape": (128, 128), "max_shapes": 20, "channel_axis": None, "shape": None, "rng": 1, "allow_overlap": True, "min_size": 20} kwargs["rng"] = 13588686514 kwargs["min_size"] = 20 random_images, _ = random_shapes(**kwargs) mask = np.where(random_images != 255, 1, 0) skeleton_linear1 = skeletonize(mask) viewer = napari.Viewer() layer = viewer.add_labels(skeleton_linear1) skeleton = Skeleton(skeleton_linear1) all_paths = [skeleton.path_coordinates(i) for i in range(skeleton.n_paths)] paths_table = summarize(skeleton, separator='_') paths_table.reset_index(inplace=True, names='branch-id') shp_layer = viewer.add_shapes( all_paths, shape_type='path', features=paths_table, metadata={'skeleton': skeleton}, ) shp_layer.edge_color = 'branch-id' shp_layer.edge_color_cycle = [ 'red', 'green', 'blue', 'cyan', 'magenta', 'yellow' ] napari.run()
This is the output on SciPy 1.10:
The same code with SciPy 1.11 produces:
Both are wrong (both loops should be completely closed).
The text was updated successfully, but these errors were encountered:
Mark test as failing under 3.8
5d50eb6
Discovered that single skeleton > networkx failing under Python 3.8 is due to spurious edge detection . See jni#225 for further details.
SciPy changes to investigate re the change in behaviour, based on the 1.11 release notes: scipy/scipy#16936 / scipy/scipy#16929
Sorry, something went wrong.
No branches or pull requests
... And which side of the loop is chosen depends on whether the SciPy version used is 1.10 or earlier or 1.11 or later. 😕
Here's a reproducible example:
This is the output on SciPy 1.10:
The same code with SciPy 1.11 produces:
Both are wrong (both loops should be completely closed).
The text was updated successfully, but these errors were encountered: