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1"""
2Sparse linear algebra (:mod:`scipy.sparse.linalg`)
3==================================================
5.. currentmodule:: scipy.sparse.linalg
7Abstract linear operators
8-------------------------
10.. autosummary::
11 :toctree: generated/
13 LinearOperator -- abstract representation of a linear operator
14 aslinearoperator -- convert an object to an abstract linear operator
16Matrix Operations
17-----------------
19.. autosummary::
20 :toctree: generated/
22 inv -- compute the sparse matrix inverse
23 expm -- compute the sparse matrix exponential
24 expm_multiply -- compute the product of a matrix exponential and a matrix
26Matrix norms
27------------
29.. autosummary::
30 :toctree: generated/
32 norm -- Norm of a sparse matrix
33 onenormest -- Estimate the 1-norm of a sparse matrix
35Solving linear problems
36-----------------------
38Direct methods for linear equation systems:
40.. autosummary::
41 :toctree: generated/
43 spsolve -- Solve the sparse linear system Ax=b
44 spsolve_triangular -- Solve the sparse linear system Ax=b for a triangular matrix
45 factorized -- Pre-factorize matrix to a function solving a linear system
46 MatrixRankWarning -- Warning on exactly singular matrices
47 use_solver -- Select direct solver to use
49Iterative methods for linear equation systems:
51.. autosummary::
52 :toctree: generated/
54 bicg -- Use BIConjugate Gradient iteration to solve A x = b
55 bicgstab -- Use BIConjugate Gradient STABilized iteration to solve A x = b
56 cg -- Use Conjugate Gradient iteration to solve A x = b
57 cgs -- Use Conjugate Gradient Squared iteration to solve A x = b
58 gmres -- Use Generalized Minimal RESidual iteration to solve A x = b
59 lgmres -- Solve a matrix equation using the LGMRES algorithm
60 minres -- Use MINimum RESidual iteration to solve Ax = b
61 qmr -- Use Quasi-Minimal Residual iteration to solve A x = b
62 gcrotmk -- Solve a matrix equation using the GCROT(m,k) algorithm
64Iterative methods for least-squares problems:
66.. autosummary::
67 :toctree: generated/
69 lsqr -- Find the least-squares solution to a sparse linear equation system
70 lsmr -- Find the least-squares solution to a sparse linear equation system
72Matrix factorizations
73---------------------
75Eigenvalue problems:
77.. autosummary::
78 :toctree: generated/
80 eigs -- Find k eigenvalues and eigenvectors of the square matrix A
81 eigsh -- Find k eigenvalues and eigenvectors of a symmetric matrix
82 lobpcg -- Solve symmetric partial eigenproblems with optional preconditioning
84Singular values problems:
86.. autosummary::
87 :toctree: generated/
89 svds -- Compute k singular values/vectors for a sparse matrix
91Complete or incomplete LU factorizations
93.. autosummary::
94 :toctree: generated/
96 splu -- Compute a LU decomposition for a sparse matrix
97 spilu -- Compute an incomplete LU decomposition for a sparse matrix
98 SuperLU -- Object representing an LU factorization
100Exceptions
101----------
103.. autosummary::
104 :toctree: generated/
106 ArpackNoConvergence
107 ArpackError
109"""
111from .isolve import *
112from .dsolve import *
113from .interface import *
114from .eigen import *
115from .matfuncs import *
116from ._onenormest import *
117from ._norm import *
118from ._expm_multiply import *
120__all__ = [s for s in dir() if not s.startswith('_')]
122from scipy._lib._testutils import PytestTester
123test = PytestTester(__name__)
124del PytestTester