U Gv f…ã@sŠdZddlTddlTddlTddlTddlTddlTddlTddlTddl m Z m Z m Z m Z mZdd„eƒDƒZddlmZeeƒZ[dS) a· 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 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 the sparse linear system Ax=b for a triangular matrix 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 A x = b bicgstab -- Use BIConjugate Gradient STABilized iteration to solve A x = b cg -- Use Conjugate Gradient iteration to solve A x = b cgs -- Use Conjugate Gradient Squared iteration to solve A x = b gmres -- Use Generalized Minimal RESidual iteration to solve A x = 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 A x = b gcrotmk -- Solve a matrix equation using the GCROT(m,k) algorithm tfqmr -- Use Transpose-Free Quasi-Minimal Residual iteration to solve A x = 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 Exceptions ---------- .. autosummary:: :toctree: generated/ ArpackNoConvergence ArpackError é)Ú*)ÚisolveÚdsolveÚ interfaceÚeigenÚmatfuncscCsg|]}| d¡s|‘qS)Ú_)Ú startswith)Ú.0Ús©r ú@/tmp/pip-unpacked-wheel-96ln3f52/scipy/sparse/linalg/__init__.pyÚ „s ré)Ú PytestTesterN)Ú__doc__Z_isolveZ_dsolveZ _interfaceZ_eigenZ _matfuncsZ _onenormestZ_normZ_expm_multiplyÚrrrrrÚdirÚ__all__Zscipy._lib._testutilsrÚ__name__Útestr r r r Úsw