chore(deps): update numpy requirement from >=1.22.2 to >=2.5.4

[dependabot]

Updates the requirements on numpy to permit the latest version.

Release notes

Sourced from numpy's releases.

v2.5.4 (Oct 10, 2026)

NumPy 2.5.4 Release Notes

Released on 2026-10-10.

NumPy 2.5.4 is a patch release that fixes bugs discovered after the 2.5.3 release. Highlights are:

• Many typing fixes and improvements,
• A workaround for the MSVC 19.51 bug, see below.

This release supports Python versions 3.12-3.15.

Improvements

• numpy.linalg.svd and numpy.linalg.lstsq now raise for inputs containing infinities instead of returning garbage results.

• Fixed hangs in numpy.linalg.svd and numpy.linalg.lstsq for certain inputs containing infinities for recent versions of some LAPACK implementations.

• numpy.linalg.cond now handles non-finite inputs more consistently.

(gh-32593)

StringDType hashing with NaN sentinels

StringDType instances with equivalent floating-point NaN sentinels now have equal hashes. Previously, distinct NaN objects could produce equal dtype instances with different hashes, causing dictionary lookups and set deduplication to fail.

(gh-32563)

Changes

MaskedArray resets a fill_value that cannot be represented in a new dtype

A fill_value copied from a source array is now reset to the default fill_value for the new dtype when it cannot be represented in that dtype. Previously the copied value could be stale: ufuncs that change dtype left the result holding a fill_value typed for the old dtype, which raised a TypeError only when something later validated it (such as .view()), and a floating point fill_value that overflows an integer dtype was kept as an out-of-range value together with a RuntimeWarning. Both now fall back to the default, including when a masked array is passed to MaskedArray with a different dtype. A fill_value given explicitly by the user is still validated and raises as before. This can now raise a ComplexWarning if the fill_value is complex and the new dtype is real.

... (truncated)

Changelog

Sourced from numpy's changelog.

This is a walkthrough of the NumPy 2.4.0 release on Linux, which will be the first feature release using the numpy/numpy-release <https://github.com/numpy/numpy-release>__ repository.

The commands can be copied into the command line, but be sure to replace 2.4.0 with the correct version. This should be read together with the :ref:general release guide <prepare_release>.

Facility preparation

Before beginning to make a release, use the dependency groups from pyproject.toml to ensure that you have the needed software. Most software can be installed with pip, but some will require apt-get, dnf, or whatever your system uses for software. You will also need a GitHub personal access token (PAT) to push the documentation. There are a few ways to streamline things:

• Git can be set up to use a keyring to store your GitHub personal access token. Search online for the details.

Prior to release

Add/drop Python versions

When adding or dropping Python versions, multiple config and CI files need to be edited in addition to changing the minimum version in pyproject.toml. Make these changes in an ordinary PR against main and backport if necessary. We currently release wheels for new Python versions after the first Python RC once manylinux and cibuildwheel support that new Python version.

Backport pull requests

Changes that have been marked for this release must be backported to the maintenance/2.4.x branch.

Update 2.4.0 milestones

Look at the issues/prs with 2.4.0 milestones and either push them off to a later version, or maybe remove the milestone. You may need to add a milestone.

Check the numpy-release repo

... (truncated)

Commits

• a3d0ef1 Merge pull request #32969 from charris/prepare-2.5.4
• 087b536 MAINT: Make OpenBLAS version check use 2.5.x branch.
• 91acd87 REL: Prepare for the NumPy 2.5.4 release.
• 9cc555b Merge pull request #32956 from charris/backport-typing-1
• e04b972 TYP: dtype[void].names: allow setting with list (#32943)
• d929969 TYP: timedelta64: datetime.timedelta construction isn't deprecated (#...
• 839467f TYP: ma.getmaskarray: accept array-likes (#32934)
• 64b721b TYP: polynomial: accept scalar coef in the poly constructors (#32931)
• 06b7ad2 TYP: void: accept any dtype: str in constructor calls (#32928)
• c7bcd2c TYP: place: widen mask (#32926)
• Additional commits viewable in compare view

[coderabbitai]

Important

Review skipped

Bot user detected.

To trigger a single review, invoke the @coderabbitai review command.

⚙️ Run configuration

• Configuration used: Organization UI
• Review profile: CHILL
• Plan: Advanced
• Run ID: 0e985a17-aedf-441d-b897-1ea4a478a336

You can disable this status message by setting the reviews.review_status to false in the CodeRabbit configuration file.

Use the checkbox below for a quick retry:

• 🔍 Trigger review

• Autofix · Keep fixing CodeRabbit findings and required CI, and resolving merge conflicts

_{Comment @coderabbitai help to get the list of available commands.}

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 38%. Comparing base (f72f1ca) to head (7ca3af8).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@          Coverage Diff          @@
##            main    #570   +/-   ##
=====================================
  Coverage     38%     38%           
=====================================
  Files        822     822           
  Lines      41098   41098           
  Branches    9044    9044           
=====================================
  Hits       15622   15622           
  Misses     23404   23404           
  Partials    2072    2072           

🚀 New features to boost your workflow:

• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.