fix: support mixed bool and float in maxp

[samay2504]

This PR fixes issue #498 by normalising MaxP covariate input to a numeric array before distance computation, which allows mixed bool and float columns to be used safely without triggering SciPy object-dtype errors, and it adds a regression test that builds a mixed bool+float attribute set and verifies MaxPHeuristic.solve() completes and returns labels for all observations.

[Copilot]

Pull request overview

Fixes MaxPHeuristic failing when attrs_name contains mixed bool + numeric columns by ensuring the attribute matrix passed into SciPy distance computation is always numeric, and adds a regression test for the reported scenario (issue #498).

Changes:

• Cast gdf[attrs_name] to a float NumPy array prior to pdist to avoid object-dtype failures when boolean columns are included.
• Add a regression test that constructs a mixed bool+float attribute set and asserts solve() returns labels for all observations.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
spopt/region/maxp.py	Normalizes covariate inputs to a numeric (float) array before computing distances.
spopt/tests/test_region/test_maxp.py	Adds regression coverage for mixed boolean + float covariates in MaxPHeuristic.solve().

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 76.9%. Comparing base (9b36063) to head (fb90ff5).
⚠️ Report is 7 commits behind head on main.

Additional details and impacted files

@@          Coverage Diff          @@
##            main    #519   +/-   ##
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  Coverage   76.9%   76.9%           
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  Files         29      29           
  Lines       3700    3700           
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  Hits        2846    2846           
  Misses       854     854           

Files with missing lines	Coverage Δ
spopt/region/maxp.py	98.0% <100.0%> (ø)

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