# scipy.linalg.qr_multiply¶

scipy.linalg.qr_multiply(a, c, mode='right', pivoting=False, conjugate=False, overwrite_a=False, overwrite_c=False)[source]

Calculate the QR decomposition and multiply Q with a matrix.

Calculate the decomposition A = Q R where Q is unitary/orthogonal and R upper triangular. Multiply Q with a vector or a matrix c.

New in version 0.11.0.

Parameters : a : ndarray, shape (M, N) Matrix to be decomposed c : ndarray, one- or two-dimensional calculate the product of c and q, depending on the mode: mode : {‘left’, ‘right’}, optional dot(Q, c) is returned if mode is ‘left’, dot(c, Q) is returned if mode is ‘right’. The shape of c must be appropriate for the matrix multiplications, if mode is ‘left’, min(a.shape) == c.shape, if mode is ‘right’, a.shape == c.shape. pivoting : bool, optional Whether or not factorization should include pivoting for rank-revealing qr decomposition, see the documentation of qr. conjugate : bool, optional Whether Q should be complex-conjugated. This might be faster than explicit conjugation. overwrite_a : bool, optional Whether data in a is overwritten (may improve performance) overwrite_c : bool, optional Whether data in c is overwritten (may improve performance). If this is used, c must be big enough to keep the result, i.e. c.shape = a.shape if mode is ‘left’. CQ : float or complex ndarray the product of Q and c, as defined in mode R : float or complex ndarray Of shape (K, N), K = min(M, N). P : ndarray of ints Of shape (N,) for pivoting=True. Not returned if pivoting=False. LinAlgError Raised if decomposition fails

Notes

This is an interface to the LAPACK routines dgeqrf, zgeqrf, dormqr, zunmqr, dgeqp3, and zgeqp3.

scipy.linalg.qr

scipy.linalg.qz