mindspore.scipy.linalg.cho_solve

mindspore.scipy.linalg.cho_solve(c_and_lower, b, overwrite_b=False, check_finite=True)[source]

Given the cholesky factorization of a, solve the linear equation

\[a x = b\]

Note

  • cho_solve is not supported on Windows platform yet.

  • Only float32, float64, int32, int64 are supported Tensor dtypes. If Tensor with dtype int32 or int64 is passed, it will be cast to mstype.float64.

Parameters

  • c_and_lower ((Tensor, bool)) – cholesky factorization of a, as given by cho_factor.

  • b (Tensor) – Right-hand side.

  • overwrite_b (bool, optional) – Whether to overwrite data in b (may improve performance). Default: False.

  • check_finite (bool, optional) – 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. Default: True.

Returns

Tensor, the solution to the system a x = b

Supported Platforms:

CPU GPU

Examples

>>> import numpy as onp
>>> from mindspore.common import Tensor
>>> from mindspore.scipy.linalg import cho_factor, cho_solve
>>> a = Tensor(onp.array([[9, 3, 1, 5], [3, 7, 5, 1], [1, 5, 9, 2], [5, 1, 2, 6]]).astype(onp.float32))
>>> b = Tensor(onp.array([1, 1, 1, 1]).astype(onp.float32))
>>> c, low = cho_factor(a)
>>> x = cho_solve((c, low), b)
>>> print(x)
[-0.01749266  0.11953348  0.01166185  0.15743434]