BUG: numpy 1.16 doesn't support @np.vectorize decorator syntax

[Zeroto521]

closes #1159
A lower numpy version, like 1.16, doesn't support the @np.vectorize decorator.

[Copilot]

Pull request overview

This PR fixes a compatibility issue with NumPy 1.16 where the @np.vectorize decorator syntax was not supported. The fix refactors the code to use np.vectorize as a function call instead of a decorator, and reverts the minimum NumPy version requirement from 1.19.0 back to 1.16.0.

Changes:

• Refactored _core_dot_2d to use np.vectorize as a function assignment instead of as a decorator
• Reverted minimum NumPy version from 1.19.0 to 1.16.0 in pyproject.toml
• Removed the changelog entry about the NumPy version increase

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 2 comments.

File	Description
src/pyscipopt/matrix.pxi	Refactored _core_dot_2d from decorator-style to function-call-style np.vectorize, changed function signature to cdef, and updated a parameter documentation
pyproject.toml	Reverted minimum NumPy version requirement from 1.19.0 to 1.16.0
CHANGELOG.md	Removed the entry about NumPy version increase that was previously added

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[Zeroto521]

Since PR CI only has one environment, I'm not sure it's okay to master the branch.
So I'll build a local env to test this later.

[Joao-Dionisio]

Thank you @Zeroto521 , please let me know if it passes in your local env.

[Zeroto521]

Thank you @Zeroto521 , please let me know if it passes in your local env.

This PR is fine. Local tests are passed.
But there is another problem with numpy. #1164 (comment)

[Joao-Dionisio]

Fingers crossed!

[Joao-Dionisio]

Nope, now it breaks something else: https://github.com/scipopt/PySCIPOpt/actions/runs/21245818764/job/61134718269

[Zeroto521]

It's still a version compatibility problem. Only fails on window 3.8
Let's see which numpy feature cases this.

[gw2] linux -- Python 3.8.18 /opt/hostedtoolcache/Python/3.8.18/x64/bin/python

    def test_ranged_matrix_cons_with_expr():
        m = Model()
        x = m.addMatrixVar(3)
        var = m.addVar(vtype="B", ub=0)
    
        # test MatrixExprCons vs Variable
        with pytest.raises(TypeError):
            m.addMatrixCons((x <= 1) >= var)
    
        # test "==" operator
        with pytest.raises(NotImplementedError):
>           m.addMatrixCons((x <= 1) == 1)

tests/test_matrix_variable.py:594: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   raise TypeError("given constraint is not MatrixExprCons nor ExprCons but %s" % cons.__class__.__name__)
E   TypeError: given constraint is not MatrixExprCons nor ExprCons but bool

src/pyscipopt/scip.pxi:6223: TypeError