Update scipy requirement from <1.15 to <1.16

[dependabot]

Updates the requirements on scipy to permit the latest version.

Release notes

Sourced from scipy's releases.

SciPy 1.15.0 Release Notes

SciPy 1.15.0 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 1.15.x branch, and on adding new features on the main branch.

This release requires Python 3.10-3.13 and NumPy 1.23.5 or greater.

Highlights of this release

• Sparse arrays are now fully functional for 1-D and 2-D arrays. We recommend that all new code use sparse arrays instead of sparse matrices and that developers start to migrate their existing code from sparse matrix to sparse array: migration_to_sparray. Both sparse.linalg and sparse.csgraph work with either sparse matrix or sparse array and work internally with sparse array.

• Sparse arrays now provide basic support for n-D arrays in the COO format including add, subtract, reshape, transpose, matmul, dot, tensordot and others. More functionality is coming in future releases.

• Preliminary support for free-threaded Python 3.13.

• New probability distribution features in scipy.stats can be used to improve the speed and accuracy of existing continuous distributions and perform new probability calculations.

• Several new features support vectorized calculations with Python Array API Standard compatible input (see "Array API Standard Support" below):

  • scipy.differentiate is a new top-level submodule for accurate estimation of derivatives of black box functions.
  • scipy.optimize.elementwise contains new functions for root-finding and minimization of univariate functions.
  • scipy.integrate offers new functions cubature, tanhsinh, and nsum for multivariate integration, univariate integration, and univariate series summation, respectively.

• scipy.interpolate.AAA adds the AAA algorithm for barycentric rational approximation of real or complex functions.

• scipy.special adds new functions offering improved Legendre function implementations with a more consistent interface.

... (truncated)

Commits

• 6e246d0 REL: 1.15.0 "final" rel commit [wheel build]
• ed7c850 Merge pull request #22233 from tylerjereddy/treddy_backports_1.15.0_final
• 2e2f2cd MAINT: PR 22233 wheel build [wheel build]
• f05c622 DOC: Update 1.15.0 relnotes
• 7348d92 Update scipy/differentiate/_differentiate.py
• 56b1f7e DOC: differentiate.jacobian: correct/improve documentation about callable int...
• 30077e7 DEP: linalg.solve_toeplitz/matmul_toeplitz: warn on n-D c, r (#22193)
• 256c1a2 Merge pull request #22181 from tylerjereddy/treddy_prep_scipy_1.15.0rc3
• f046276 REL: set 1.15.0rc3 unreleased
• a3d40a8 REL: 1.15.0rc2 rel commit [wheel build]
• Additional commits viewable in compare view

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Summary by Sourcery

Chores:

• Bump the scipy dependency to allow versions up to 1.16.

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📚 Documentation preview 📚: https://jaxspec--214.org.readthedocs.build/en/214/

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request updates the version requirement for the scipy package from <1.15 to <1.16. This change allows the use of newer versions of SciPy with bug fixes, new features, performance improvements, and expanded compatibility with Python 3.10-3.13 and NumPy 1.23.5 or greater.

Class diagram highlighting new SciPy 1.15 features

classDiagram
    class scipy {
        +differentiate
        +optimize
        +integrate
        +interpolate
        +special
    }
    class differentiate {
        +jacobian()
    }
    class optimize {
        +elementwise
    }
    class integrate {
        +cubature()
        +tanhsinh()
        +nsum()
    }
    class interpolate {
        +AAA()
    }
    scipy --> differentiate: new
    scipy --> optimize
    scipy --> integrate
    scipy --> interpolate
    note for differentiate "New top-level submodule"
    note for integrate "New integration methods"
    note for interpolate "New AAA algorithm"

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File-Level Changes

Change	Details	Files
Updated the scipy requirement	Changed the scipy version from <1.15 to <1.16 in pyproject.toml	pyproject.toml

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We have skipped reviewing this pull request. Here's why:

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