ai-content-maker/.venv/Lib/site-packages/scipy/sparse/linalg/__init__.py

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"""
Sparse linear algebra (:mod:`scipy.sparse.linalg`)
==================================================
.. currentmodule:: scipy.sparse.linalg
Abstract linear operators
-------------------------
.. autosummary::
:toctree: generated/
LinearOperator -- abstract representation of a linear operator
aslinearoperator -- convert an object to an abstract linear operator
Matrix Operations
-----------------
.. autosummary::
:toctree: generated/
inv -- compute the sparse matrix inverse
expm -- compute the sparse matrix exponential
expm_multiply -- compute the product of a matrix exponential and a matrix
matrix_power -- compute the matrix power by raising a matrix to an exponent
Matrix norms
------------
.. autosummary::
:toctree: generated/
norm -- Norm of a sparse matrix
onenormest -- Estimate the 1-norm of a sparse matrix
Solving linear problems
-----------------------
Direct methods for linear equation systems:
.. autosummary::
:toctree: generated/
spsolve -- Solve the sparse linear system Ax=b
spsolve_triangular -- Solve sparse linear system Ax=b for a triangular A.
factorized -- Pre-factorize matrix to a function solving a linear system
MatrixRankWarning -- Warning on exactly singular matrices
use_solver -- Select direct solver to use
Iterative methods for linear equation systems:
.. autosummary::
:toctree: generated/
bicg -- Use BIConjugate Gradient iteration to solve Ax = b
bicgstab -- Use BIConjugate Gradient STABilized iteration to solve Ax = b
cg -- Use Conjugate Gradient iteration to solve Ax = b
cgs -- Use Conjugate Gradient Squared iteration to solve Ax = b
gmres -- Use Generalized Minimal RESidual iteration to solve Ax = b
lgmres -- Solve a matrix equation using the LGMRES algorithm
minres -- Use MINimum RESidual iteration to solve Ax = b
qmr -- Use Quasi-Minimal Residual iteration to solve Ax = b
gcrotmk -- Solve a matrix equation using the GCROT(m,k) algorithm
tfqmr -- Use Transpose-Free Quasi-Minimal Residual iteration to solve Ax = b
Iterative methods for least-squares problems:
.. autosummary::
:toctree: generated/
lsqr -- Find the least-squares solution to a sparse linear equation system
lsmr -- Find the least-squares solution to a sparse linear equation system
Matrix factorizations
---------------------
Eigenvalue problems:
.. autosummary::
:toctree: generated/
eigs -- Find k eigenvalues and eigenvectors of the square matrix A
eigsh -- Find k eigenvalues and eigenvectors of a symmetric matrix
lobpcg -- Solve symmetric partial eigenproblems with optional preconditioning
Singular values problems:
.. autosummary::
:toctree: generated/
svds -- Compute k singular values/vectors for a sparse matrix
The `svds` function supports the following solvers:
.. toctree::
sparse.linalg.svds-arpack
sparse.linalg.svds-lobpcg
sparse.linalg.svds-propack
Complete or incomplete LU factorizations
.. autosummary::
:toctree: generated/
splu -- Compute a LU decomposition for a sparse matrix
spilu -- Compute an incomplete LU decomposition for a sparse matrix
SuperLU -- Object representing an LU factorization
Sparse arrays with structure
----------------------------
.. autosummary::
:toctree: generated/
LaplacianNd -- Laplacian on a uniform rectangular grid in ``N`` dimensions
Exceptions
----------
.. autosummary::
:toctree: generated/
ArpackNoConvergence
ArpackError
"""
from ._isolve import *
from ._dsolve import *
from ._interface import *
from ._eigen import *
from ._matfuncs import *
from ._onenormest import *
from ._norm import *
from ._expm_multiply import *
from ._special_sparse_arrays import *
# Deprecated namespaces, to be removed in v2.0.0
from . import isolve, dsolve, interface, eigen, matfuncs
__all__ = [s for s in dir() if not s.startswith('_')]
from scipy._lib._testutils import PytestTester
test = PytestTester(__name__)
del PytestTester