Reject boolean NumPy multinomial sizes

[FlorianPfaff]

Summary

• add NumPy-backend validation for random.multinomial(..., size=...) so booleans are not silently treated as sample dimensions
• add regression coverage for Python, NumPy-scalar, tuple/list, and object-array boolean size inputs
• keep integer-like scalar size arguments accepted

Bug fixed

np.random.multinomial accepts Python True and False for size, producing (1, k) or (0, k) output shapes. PyRecEst already rejects booleans for sample counts and most random-backend size dimensions; this patch closes the NumPy multinomial gap so boolean size values do not silently change the number of draws.

Validation

• Inspected the branch diff with GitHub compare: only src/pyrecest/_backend/numpy/random.py and tests/backend/test_numpy_random_backend.py changed.
• Locally exercised the added size validator against the new boolean cases and an integer-like NumPy scalar size. The execution sandbox cannot resolve github.com, so I could not clone/install the full repository for a complete pytest run.

[github-actions]

✅MegaLinter analysis: Success

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