sfepy.solvers.eigen module¶
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class
sfepy.solvers.eigen.
LOBPCGEigenvalueSolver
(conf, **kwargs)[source]¶ SciPy-based LOBPCG solver for sparse symmetric problems.
Kind: ‘eig.scipy_lobpcg’
For common configuration parameters, see
Solver
.Specific configuration parameters:
Parameters: i_max : int (default: 20)
The maximum number of iterations.
eps_a : float
The absolute tolerance for the convergence.
largest : bool (default: True)
If True, solve for the largest eigenvalues, otherwise the smallest.
precond : {dense matrix, sparse matrix, LinearOperator}
The preconditioner.
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name
= 'eig.scipy_lobpcg'¶
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class
sfepy.solvers.eigen.
PysparseEigenvalueSolver
(conf, **kwargs)[source]¶ Pysparse-based eigenvalue solver for sparse symmetric problems.
Kind: ‘eig.pysparse’
For common configuration parameters, see
Solver
.Specific configuration parameters:
Parameters: i_max : int (default: 100)
The maximum number of iterations.
eps_a : float (default: 1e-05)
The absolute tolerance for the convergence.
tau : float (default: 0.0)
The target value.
method : {‘cgs’, ‘qmrs’} (default: ‘qmrs’)
The linear iterative solver supported by
pysparse
.verbosity : int (default: 0)
The
pysparse
verbosity level.strategy : {0, 1} (default: 1)
The shifting and sorting strategy of JDSYM: strategy=0 enables the default JDSYM algorithm, strategy=1 enables JDSYM to avoid convergence to eigenvalues smaller than tau.
* : *
Additional parameters supported by the solver.
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name
= 'eig.pysparse'¶
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class
sfepy.solvers.eigen.
ScipyEigenvalueSolver
(conf, **kwargs)[source]¶ SciPy-based solver for both dense and sparse problems (if n_eigs is given).
Kind: ‘eig.scipy’
For common configuration parameters, see
Solver
.Specific configuration parameters:
Parameters: method : {‘eig’, ‘eigh’} (default: ‘eig’)
The method for solving general or symmetric eigenvalue problems: for dense problems
eig()
oreigh()
are used, for sparse problems (if n_eigs is given)eigs()
oreigsh()
are used.* : *
Additional parameters supported by the method.
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name
= 'eig.scipy'¶
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class
sfepy.solvers.eigen.
ScipySGEigenvalueSolver
(conf, **kwargs)[source]¶ SciPy-based solver for dense symmetric problems.
Kind: ‘eig.sgscipy’
For common configuration parameters, see
Solver
.Specific configuration parameters:
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name
= 'eig.sgscipy'¶
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