This is documentation for an old release of SciPy (version 1.6.2). Read this page in the documentation of the latest stable release (version 1.15.1).
Sparse linear algebra (scipy.sparse.linalg
)¶
Abstract linear operators¶
|
Common interface for performing matrix vector products |
Return A as a LinearOperator. |
Matrix Operations¶
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Compute the inverse of a sparse matrix |
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Compute the matrix exponential using Pade approximation. |
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Compute the action of the matrix exponential of A on B. |
Matrix norms¶
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Norm of a sparse matrix |
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Compute a lower bound of the 1-norm of a sparse matrix. |
Solving linear problems¶
Direct methods for linear equation systems:
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Solve the sparse linear system Ax=b, where b may be a vector or a matrix. |
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Solve the equation |
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Return a function for solving a sparse linear system, with A pre-factorized. |
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Select default sparse direct solver to be used. |
Iterative methods for linear equation systems:
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Use BIConjugate Gradient iteration to solve |
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Use BIConjugate Gradient STABilized iteration to solve |
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Use Conjugate Gradient iteration to solve |
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Use Conjugate Gradient Squared iteration to solve |
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Use Generalized Minimal RESidual iteration to solve |
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Solve a matrix equation using the LGMRES algorithm. |
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Use MINimum RESidual iteration to solve Ax=b |
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Use Quasi-Minimal Residual iteration to solve |
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Solve a matrix equation using flexible GCROT(m,k) algorithm. |
Iterative methods for least-squares problems:
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Find the least-squares solution to a large, sparse, linear system of equations. |
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Iterative solver for least-squares problems. |
Matrix factorizations¶
Eigenvalue problems:
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Find k eigenvalues and eigenvectors of the square matrix A. |
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Find k eigenvalues and eigenvectors of the real symmetric square matrix or complex Hermitian matrix A. |
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Locally Optimal Block Preconditioned Conjugate Gradient Method (LOBPCG) |
Singular values problems:
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Compute the largest or smallest k singular values/vectors for a sparse matrix. |
Complete or incomplete LU factorizations
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Compute the LU decomposition of a sparse, square matrix. |
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Compute an incomplete LU decomposition for a sparse, square matrix. |
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LU factorization of a sparse matrix. |
Exceptions¶
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ARPACK iteration did not converge |
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ARPACK error |