# `ulab.scipy.linalg`¶

`ulab.scipy.linalg.``solve_triangular`(A: ulab.numpy.ndarray, b: ulab.numpy.ndarray, lower: bool)ulab.numpy.ndarray
Parameters
• A (ndarray) – a matrix

• b (ndarray) – a vector

• lower (~bool) – if true, use only data contained in lower triangle of A, else use upper triangle of A

Returns

solution to the system A x = b. Shape of return matches b

Raises
• TypeError – if A and b are not of type ndarray and are not dense

• ValueError – if A is a singular matrix

Solve the equation A x = b for x, assuming A is a triangular matrix

`ulab.scipy.linalg.``cho_solve`(L: ulab.numpy.ndarray, b: ulab.numpy.ndarray)ulab.numpy.ndarray
Parameters
• L (ndarray) – the lower triangular, Cholesky factorization of A

• b (ndarray) – right-hand-side vector b

Returns

solution to the system A x = b. Shape of return matches b

Raises

TypeError – if L and b are not of type ndarray and are not dense

Solve the linear equations A x = b, given the Cholesky factorization of A as input