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numpy
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linalg
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__init__.py
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__init__.pyc
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__init__.pyo
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_umath_linalg.so
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info.py
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info.pyc
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info.pyo
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lapack_lite.so
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linalg.py
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linalg.pyc
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linalg.pyo
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setup.py
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setup.pyc
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setup.pyo
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tests
Editing: 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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