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]