Fix transformation equality for mismatched axes

[yyli-leo]

Fixes #1205.

Comparing Translation, Scale, or Affine objects with different axis counts can raise a NumPy broadcasting ValueError before the axis comparison returns False. Check the ordered axes before calling np.allclose, preserving the existing type checks and numerical tolerances. Affine already validates matrix dimensions against its input/output axes during construction.

Add 31 parameterized regression and control cases covering mismatched axis counts in both operand orders, independent Affine input/output mismatches, ==/!=, Sequence comparisons, numerical tolerances, axis order/names, and unrelated types.

Validation on Linux, Python 3.12.15, NumPy 2.4.6, at ea93a37203d187020c5d50a7f984dbf8c264a3ae:

• Original production code with the new tests: 10 intended broadcasting failures, 21 passed.
• Patched production code with the same test IDs: 31 passed.
• Full suite with pytest -q -n 2 --dist worksteal --run-network: 1458 passed, 7 skipped, 2 xfailed. The skips and expected failures cover existing unsupported cases.
• Ruff lint/format checks on both changed files, configured mypy over 58 source files, pip check, and git diff --check: passed.

The full Python/OS/dependency matrix and the reported Xenium end-to-end workflow were not run locally.

AI assistance was used to prepare and validate this change.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 91.42%. Comparing base (ea93a37) to head (52d471a).

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1269      +/-   ##
==========================================
+ Coverage   91.40%   91.42%   +0.01%     
==========================================
  Files          53       53              
  Lines        8381     8381              
==========================================
+ Hits         7661     7662       +1     
+ Misses        720      719       -1     

Files with missing lines	Coverage Δ
src/spatialdata/transformations/transformations.py	84.28% <100.00%> (+0.16%)	⬆️

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