aesara.tensor.nlinalg.qr#
- aesara.tensor.nlinalg.qr(a, mode='reduced')[source]#
Computes the QR decomposition of a matrix. Factor the matrix a as qr, where q is orthonormal and r is upper-triangular.
- Parameters:
a (array_like, shape (M, N)) – Matrix to be factored.
mode ({'reduced', 'complete', 'r', 'raw'}, optional) –
If K = min(M, N), then
- ’reduced’
returns q, r with dimensions (M, K), (K, N)
- ’complete’
returns q, r with dimensions (M, M), (M, N)
- ’r’
returns r only with dimensions (K, N)
- ’raw’
returns h, tau with dimensions (N, M), (K,)
Note that array h returned in ‘raw’ mode is transposed for calling Fortran.
Default mode is ‘reduced’
- Returns:
q (matrix of float or complex, optional) – A matrix with orthonormal columns. When mode = ‘complete’ the result is an orthogonal/unitary matrix depending on whether or not a is real/complex. The determinant may be either +/- 1 in that case.
r (matrix of float or complex, optional) – The upper-triangular matrix.