5ded2b734290836869a549a7c0e4be7d46d4bde4,scipy/sparse/linalg/eigen/lobpcg/lobpcg.py,,_b_orthonormalize,#Any#Any#Any#Any#,86

Before Change

            blockVectorBV = blockVectorV  // Shared data!!!
    gramVBV = np.dot(blockVectorV.T.conj(), blockVectorBV)
    gramVBV = cholesky(gramVBV)
    gramVBV = inv(gramVBV, overwrite_a=True)
    // gramVBV is now R^{-1}.
    blockVectorV = np.dot(blockVectorV, gramVBV)
    if B is not None:
        blockVectorBV = np.dot(blockVectorBV, gramVBV)

After Change

def _b_orthonormalize(B, blockVectorV, blockVectorBV=None, retInvR=False):
    normalization = blockVectorV.max(axis=0)
    blockVectorV = blockVectorV / normalization
    if blockVectorBV is None:
        if B is not None:
            blockVectorBV = B(blockVectorV)
        else:
            blockVectorBV = blockVectorV  // Shared data!!!
    else:
        blockVectorBV = blockVectorBV / normalization
    VBV = blockVectorV.T.conj() @ blockVectorBV
    try:
        // VBV is a Cholesky factor from now on...
        VBV = cholesky(VBV, overwrite_a=True)
        VBV = inv(VBV, overwrite_a=True)
        blockVectorV = blockVectorV @ VBV
        // blockVectorV = (cho_solve((VBV.T, True), blockVectorV.T)).T
        if B is not None:
            blockVectorBV = blockVectorBV @ VBV
            // blockVectorBV = (cho_solve((VBV.T, True), blockVectorBV.T)).T

Instances