scipy.linalg.inv#

scipy.linalg.inv(a, overwrite_a=False, check_finite=True)[source]#

Compute the inverse of a matrix.

Parameters

aarray_like: Square matrix to be inverted.
overwrite_abool, optional: Discard data in a (may improve performance). Default is False.
check_finitebool, 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

ainvndarray: Inverse of the matrix a.

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.]])

Linear algebra (scipy.linalg)

scipy.linalg.solve