Bump scipy from 1.11.4 to 1.12.0

Bumps scipy from 1.11.4 to 1.12.0.

Release notes

Sourced from scipy's releases.

SciPy 1.12.0 Release Notes

SciPy 1.12.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for DeprecationWarning s). Our development attention will now shift to bug-fix releases on the 1.12.x branch, and on adding new features on the main branch.

This release requires Python 3.9+ and NumPy 1.22.4 or greater.

For running on PyPy, PyPy3 6.0+ is required.

Highlights of this release

• Experimental support for the array API standard has been added to part of scipy.special, and to all of scipy.fft and scipy.cluster. There are likely to be bugs and early feedback for usage with CuPy arrays, PyTorch tensors, and other array API compatible libraries is appreciated. Use the SCIPY_ARRAY_API environment variable for testing.
• A new class, ShortTimeFFT, provides a more versatile implementation of the short-time Fourier transform (STFT), its inverse (ISTFT) as well as the (cross-) spectrogram. It utilizes an improved algorithm for calculating the ISTFT.
• Several new constructors have been added for sparse arrays, and many operations now additionally support sparse arrays, further facilitating the migration from sparse matrices.
• A large portion of the scipy.stats API now has improved support for handling NaN values, masked arrays, and more fine-grained shape-handling. The accuracy and performance of a number of stats methods have been improved, and a number of new statistical tests and distributions have been added.

New features

scipy.cluster improvements

• Experimental support added for the array API standard; PyTorch tensors, CuPy arrays and array API compatible array libraries are now accepted (GPU support is limited to functions with pure Python implementations). CPU arrays which can be converted to and from NumPy are supported module-wide and returned arrays will match the input type. This behaviour is enabled by setting the SCIPY_ARRAY_API environment variable before importing scipy. This experimental support is still under development and likely to contain bugs - testing is very welcome.

... (truncated)

Commits

• 4edfcaa REL: SciPy 1.12.0 release commit [wheel build]
• e3cff26 Merge pull request #19922 from tylerjereddy/treddy_1_12_0_final_prep
• bf02582 DOC: PR 19922 revisions [wheel build]
• 41ed3d6 Revert "ENH: stats.wasserstein_distance: multivariate Wasserstein distance/EM...
• db2cb8c DOC: update 1.12.0 relnotes
• c76bedf BLD: ensure the name of the installed scipy package is lower-case
• aedbb2b DEP: reflect extended deprecations also in release notes (#19903)
• 0b4c8dc DEP: extend some announced deprecations due to out-of-band 1.13 release (#19892)
• 82dddc5 DOC: 1.12 release notes tweaks (#19877)
• e22a5ff REL: 1.12.0 final unreleased
• Additional commits viewable in compare view

requirements.txt

@@ -11,6 +11,6 @@ outlier-utils==0.0.5
 pyarrow==14.0.2
 pandas==2.1.4
 scikit-learn==1.3.2
-scipy==1.11.4
+scipy==1.12.0
 typing_extensions==4.5.0
 fancy-collections==0.2.1