symjax.tensor.linalg.inv

symjax.tensor.linalg.inv(a, overwrite_a=False, check_finite=True)[source]

Compute the inverse of a matrix.

LAX-backend implementation of inv(). Original docstring below.

Parameters:
  • a (array_like) – Square matrix to be inverted.
  • overwrite_a (bool, optional) – Discard data in a (may improve performance). Default is False.
  • check_finite (bool, optional) – Whether to check that the input matrix contains 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:

ainv – Inverse of the matrix a.
Return type:

ndarray
Raises:
  • LinAlgError – If a is singular.
  • ValueError – If a is not square, or not 2D.

Examples

>>> from scipy import linalg
>>> a = np.array([[1., 2.], [3., 4.]])
>>> linalg.inv(a)
array([[-2. ,  1. ],
       [ 1.5, -0.5]])
>>> np.dot(a, linalg.inv(a))
array([[ 1.,  0.],
       [ 0.,  1.]])