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Warn when covariance matrix is PSD but ill-conditioned#726
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Add a RuntimeWarning in fix_nonpositive_semidefinite() when the matrix passes the PSD check but has a condition number exceeding 1e10. This alerts users to potential numerical instability in downstream optimization without altering the matrix. Closes PyPortfolio#694
@atharvajoshi01
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Clean addition. The 1e10 condition number threshold is reasonable — typical rule of thumb in numerical linear algebra. The try/except around np.linalg.cond handles degenerate cases. Test coverage is solid with both the warning and no-warning paths.
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Summary
Adds a
RuntimeWarninginfix_nonpositive_semidefinite()when the covariance matrix passes the positive semidefinite check but has a condition number exceeding 1e10, indicating potential numerical instability in downstream portfolio optimization.Changes:
np.linalg.cond(matrix)after the PSD gate infix_nonpositive_semidefinite()RuntimeWarningwith the computed condition number when threshold is exceededtry/except LinAlgErrorfor robustnessTest coverage:
Closes #694