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fix: real-valued high BC anisotropy on NumPy >= 2 #133

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Merged
cbueth merged 1 commit into from
Aug 24, 2026
Merged

fix: real-valued high BC anisotropy on NumPy >= 2 #133

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14 changes: 8 additions & 6 deletions superblockify/metrics/measures.py
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Original file line number Diff line number Diff line change
Expand Up @@ -755,12 +755,14 @@ def __calculate_high_bc_anisotropy(coord_high_bc):
)
# Covariance matrix
cov = np.cov(coord_high_bc.T)
# Eigenvalues
eigvals = np.linalg.eigvals(cov)
# Sort eigenvalues
eigvals = np.sort(eigvals)[::-1]
# Anisotropy
return eigvals[0] / eigvals[1]
# Eigenvalues - the covariance matrix is symmetric, so use eigvalsh, which
# always returns real eigenvalues in ascending order (eigvals returns them as
# complex dtype on NumPy >= 2)
eigvals = np.linalg.eigvalsh(cov)
# Anisotropy - ratio of largest to smallest eigenvalue, infinite if degenerate;
# clip numerical-noise negative eigenvalues to zero
with np.errstate(divide="ignore", invalid="ignore"):
return float(eigvals[-1] / max(eigvals[0], 0.0))


def add_ltn_means(components, edge_attr):
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