numpy/linalg/info.py

"""\
Core Linear Algebra Tools
-------------------------
Linear algebra basics:

- norm            Vector or matrix norm
- inv             Inverse of a square matrix
- solve           Solve a linear system of equations
- det             Determinant of a square matrix
- lstsq           Solve linear least-squares problem
- pinv            Pseudo-inverse (Moore-Penrose) calculated using a singular
                  value decomposition
- matrix_power    Integer power of a square matrix

Eigenvalues and decompositions:

- eig             Eigenvalues and vectors of a square matrix
- eigh            Eigenvalues and eigenvectors of a Hermitian matrix
- eigvals         Eigenvalues of a square matrix
- eigvalsh        Eigenvalues of a Hermitian matrix
- qr              QR decomposition of a matrix
- svd             Singular value decomposition of a matrix
- cholesky        Cholesky decomposition of a matrix

Tensor operations:

- tensorsolve     Solve a linear tensor equation
- tensorinv       Calculate an inverse of a tensor

Exceptions:

- LinAlgError     Indicates a failed linear algebra operation

"""
from __future__ import division, absolute_import, print_function

depends = ['core']
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