Releases: stonerlab/Stoner-PythonCode
Releases · stonerlab/Stoner-PythonCode
v0.11.1 Stable branch release
What's Changed
- Bump actions/download-artifact from 2 to 4.1.7 in /.github/workflows by @dependabot[bot] in #27
- [WIP] Refactor add_column function to reduce complexity by @Copilot in #29
- Speed up CI: enable micromamba environment caching by @Copilot in #30
- Convert packaging to pyproject.toml, rebase onto stable (v0.11.1, Python 3.14) by @Copilot in #31
- Make DataArray a descriptor to enforce Data.data type invariant by @Copilot in #32
- Make ImageArray a descriptor to enforce ImageFile.image type invariant by @Copilot in #33
- Fix Python 3.11 test failures and mask-free CI failure reporting by @Copilot in #34
- Make
Setasa descriptor; addColumnHeadersDescriptor; merge stable by @Copilot in #35 - Fix typos in docstrings, RST documentation, and source comments by @Copilot in #36
- Add GitHub Actions workflow to build Sphinx documentation by @Copilot in #37
New Contributors
- @dependabot[bot] made their first contribution in #27
- @Copilot made their first contribution in #29
Full Changelog: v0.11.0...v0.11.1
v0.11.0 New stable branch
First release of a new stable branch with refactored functional implementations.
Full Changelog: v0.10.11...v0.11.0
v0.10.12 Minor features
Full Changelog: v0.10.11...v0.10.12
- Improve PCAR fitting code
- Refactor decompose methods to include hysteretic analysis
- Add deduplicate method
v0.10.11
Release 0.10.11 - Update for newer versions of dependencies
Update codebase to handle numpy 2.0+, scipy.1.14+ and newer versions of github actions.
Full Changelog: v0.10.10...v0.10.11
v0.10.10
Fix GenXFile to read GenX version 3 files as well
Full Changelog: v0.10.9...v0.10.10
Release 0.10.9
Bug fix and minor tweaks to testing
Release 0.10.8
Resync pip and conda versions
Stable Relase v0.10.7
Built for Python 3.11
Release v0.10.6
Update codebase to work with Python 3.10
v0.10.5 Maintainence Release
- Minor fix to deal with changes in neweer scipy.
- Fix problem when decomposing data if the original data maximum negative value is bigger than maximum positive value