skan v0.12.2
This minor release added an important bug fix from Neil Shephard
(#235), preventing a crash when
working with float32 images.
skan v0.12.1
This minor release fixed issues with the version switcher in the documentation.
skan v0.12.0
This release adds NumPy 2.0 compatibility (while remaining compatible with 1.x)
(#229). It also lays the groundwork for
new skeleton editing features with bidirectional Skeleton to NetworkX
conversion functions (#224.
We also have a minor deprecation that should improve quality of life in the
future: column names in the summary dataframe can now use _ as the separator
(instead of -), which allows one to use the pandas attribute access for
columns (for example, summary.branch_distance instead of
summary['branch-distance']. Use the separator='_' keyword argument to
summarize to take advantage of this feature (which will become the default in
a future version), or separator='-' to maintain the current behavior even
when new versions come out (#215).
The napari plugin now lets you make a Shapes layer fully backed by a Skeleton
dataset, including coloring the edges by features in the summary table
(#201).
Thanks to Neil Shephard,
James Ryan,
Jarod Hanko, and
Tim Monko for their contributions to this
release! 🙏 You can find the full list of changes below:
API changes
- #215: The separators used for column
names are configurable, and will transition to_in the future. This is to
make it easier to use the dataframe attribute interface, e.g.
summary.branch_distance
New features
- #229: NumPy 2 compatibility
- #224: Create a networkx summary graph
from a Skeleton - #201: Add napari widget to generate
shapes layer from a skeletonized label layer
Improvements
- #220: Allow mean pixel value
calculation from integer values, not just floats - #212: Improved error reporting and
tests for prune_paths methods
Bug fixes
- #221: Fix documentation builds
- #210: Cache skeleton_image shape for
use by the path_label_image method
Documentation
- #231: Add 0.12 release notes