Changelog

Changelog#

All notable changes to CRANTpy will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]#

Added#

  • Initial changelog file

  • Backward compatibility for parse_neuroncriteria import from crantpy.queries.neurons

  • Offline unit tests for crantpy.viz.skeletonize (tests/test_skeletonize.py) covering the SWC dict-to-TreeNeuron conversion, soma detection, and get_skeletons deduplication (no CAVE credentials required)

  • dataset parameter on skeletonize_neuron and skeletonize_neurons_parallel so the on-demand mesh fetch uses the same dataset as the rest of the call

Changed#

  • BREAKING: parse_neuroncriteria has been moved from crantpy.queries.neurons to crantpy.utils.decorators

    • Backward compatibility maintained with deprecation warning

    • Users should update imports: from crantpy.utils.decorators import parse_neuroncriteria

    • Old import location will be removed in a future version

  • get_skeletons now deduplicates root_ids before fetching and iterates fetches as they complete (as_completed), reporting the failing root id on error

  • skeletonize_neuron treats save_to as an output directory when given multiple root IDs, writing one <root_id>.swc per neuron instead of overwriting a single file

Deprecated#

  • Importing parse_neuroncriteria from crantpy.queries.neurons (use crantpy.utils.decorators instead)

Fixed#

  • Import error in tests for parse_neuroncriteria function

  • Skeleton topology: _create_node_info_dict now rebuilds parent pointers from undirected connectivity, fixing inverted roots and dropped branch-point children (meshparty emits [child, parent] edges) that produced fragmented skeletons in both the pcg_skel and precomputed-fetch paths

  • Wrong-dataset meshes: the skeletor fallback in skeletonize_neuron now fetches the CloudVolume for the client’s dataset instead of always the default dataset

  • Soma detection: detect_soma_skeleton no longer skips a segment whose only large-radius node is at position 0; detect_soma_mesh neighbour counting is now vectorized (was O(n²))

  • skeletonize_neurons_parallel colour generation aligns colours to the returned neurons and uses plt.get_cmap (compatible with current matplotlib); the precomputed-fetch failure reason in get_skeletons is now logged instead of silently swallowed

Support#

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