# cupyx.scipy.linalg.solve_triangular#

cupyx.scipy.linalg.solve_triangular(a, b, trans=0, lower=False, unit_diagonal=False, overwrite_b=False, check_finite=False)[source]#

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

Parameters
• a (cupy.ndarray) – The matrix with dimension (M, M).

• b (cupy.ndarray) – The matrix with dimension (M,) or (M, N).

• lower (bool) – Use only data contained in the lower triangle of a. Default is to use upper triangle.

• trans (0, 1, 2, 'N', 'T' or 'C') –

Type of system to solve:

• ’0’ or ‘N’$$a x = b$$

• ’1’ or ‘T’$$a^T x = b$$

• ’2’ or ‘C’$$a^H x = b$$

• unit_diagonal (bool) – If True, diagonal elements of a are assumed to be 1 and will not be referenced.

• overwrite_b (bool) – Allow overwriting data in b (may enhance performance)

• check_finite (bool) – Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.

Returns

The matrix with dimension (M,) or (M, N).

Return type

cupy.ndarray