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"""
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
=============== ==========================================================
"""
# To get sub-modules
from info import __doc__
from linalg import *
from numpy.testing import Tester
test = Tester().test
bench = Tester().test
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