72 lines
1.9 KiB
Python
72 lines
1.9 KiB
Python
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"""
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Linear Solvers
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==============
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The default solver is SuperLU (included in the scipy distribution),
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which can solve real or complex linear systems in both single and
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double precisions. It is automatically replaced by UMFPACK, if
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available. Note that UMFPACK works in double precision only, so
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switch it off by::
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>>> use_solver(useUmfpack=False)
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to solve in the single precision. See also use_solver documentation.
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Example session::
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>>> from scipy.sparse import csc_matrix, spdiags
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>>> from numpy import array
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>>> from scipy.sparse.linalg import spsolve, use_solver
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>>>
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>>> print("Inverting a sparse linear system:")
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>>> print("The sparse matrix (constructed from diagonals):")
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>>> a = spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]], [0, 1], 5, 5)
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>>> b = array([1, 2, 3, 4, 5])
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>>> print("Solve: single precision complex:")
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>>> use_solver( useUmfpack = False )
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>>> a = a.astype('F')
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>>> x = spsolve(a, b)
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>>> print(x)
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>>> print("Error: ", a@x-b)
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>>>
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>>> print("Solve: double precision complex:")
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>>> use_solver( useUmfpack = True )
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>>> a = a.astype('D')
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>>> x = spsolve(a, b)
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>>> print(x)
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>>> print("Error: ", a@x-b)
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>>>
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>>> print("Solve: double precision:")
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>>> a = a.astype('d')
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>>> x = spsolve(a, b)
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>>> print(x)
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>>> print("Error: ", a@x-b)
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>>>
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>>> print("Solve: single precision:")
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>>> use_solver( useUmfpack = False )
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>>> a = a.astype('f')
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>>> x = spsolve(a, b.astype('f'))
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>>> print(x)
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>>> print("Error: ", a@x-b)
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"""
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#import umfpack
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#__doc__ = '\n\n'.join( (__doc__, umfpack.__doc__) )
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#del umfpack
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from .linsolve import *
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from ._superlu import SuperLU
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from . import _add_newdocs
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from . import linsolve
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__all__ = [
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'MatrixRankWarning', 'SuperLU', 'factorized',
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'spilu', 'splu', 'spsolve',
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'spsolve_triangular', 'use_solver'
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]
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from scipy._lib._testutils import PytestTester
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test = PytestTester(__name__)
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del PytestTester
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