Fix quaternion averaging #587
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Use np.linalg.eigh instead of np.linalg.eig for the symmetric matrix Q.T @ Q. eigh is designed for symmetric matrices and guarantees real eigenvalues/eigenvectors, whereas eig can return complex values due to numerical precision. This fixes a dtype mismatch error in scipy's Rotation.from_quat which now strictly validates input types.
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Pull request overview
This PR fixes a bug in quaternion averaging that was causing dtype mismatch errors in scipy's Rotation.from_quat method. The fix uses the mathematically correct np.linalg.eigh function for symmetric matrices instead of np.linalg.eig, which can return complex values due to numerical precision issues.
Changes:
- Replaced
np.linalg.eigwithnp.linalg.eighfor computing eigenvalues/eigenvectors of the symmetric matrix Q.T @ Q - Updated to use the last eigenvector (largest eigenvalue) by indexing with
[-1]instead of usingargmax() - Changed from in-place array multiplication to explicit assignment for clarity
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Use np.linalg.eigh instead of np.linalg.eig for the symmetric matrix Q.T @ Q. eigh is designed for symmetric matrices and guarantees real eigenvalues/eigenvectors, whereas eig can return complex values due to numerical precision. This fixes a dtype mismatch error in scipy's Rotation.from_quat which now strictly validates input types.