inv(a, overwrite_a=False, check_finite=True)
Square matrix to be inverted.
Discard data in a (may improve performance). Default is False.
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.
Compute the inverse of a matrix.
>>> 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.]])See :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.sparse.linalg._matfuncs.inv
scipy.linalg._basic.inv
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