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Guarantee GaussianKernel regularization matrix is PD #264

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Merged
Jammy2211 merged 1 commit into from
Apr 10, 2026
Merged

Guarantee GaussianKernel regularization matrix is PD #264

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17 changes: 16 additions & 1 deletion autoarray/inversion/regularization/gaussian_kernel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,4 +115,19 @@ def regularization_matrix_from(self, linear_obj: LinearObj, xp=np) -> np.ndarray
xp=xp,
)

return self.coefficient * xp.linalg.inv(covariance_matrix)
regularization_matrix = self.coefficient * xp.linalg.inv(covariance_matrix)

# inv() loses exact symmetry and can introduce tiny negative eigenvalues
# when the covariance matrix is near-singular (e.g. scale >> pixel
# spacing). Symmetrise and add a trace-scaled diagonal jitter so the
# downstream cholesky in log_det_regularization_matrix_term cannot
# fail on floating-point noise.
regularization_matrix = 0.5 * (regularization_matrix + regularization_matrix.T)
N = regularization_matrix.shape[0]
diag_mean = xp.mean(xp.diag(regularization_matrix))
jitter = 1e-8 * xp.abs(diag_mean)
regularization_matrix = regularization_matrix + xp.eye(
N, dtype=regularization_matrix.dtype
) * jitter

return regularization_matrix
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