Base (abstract) solver classes.
class sfepy.solvers.solvers.EigenvalueSolver(conf, mtx_a=None, mtx_b=None, n_eigs=None, eigenvectors=None, status=None)[source]
Abstract eigenvalue solver class.
class sfepy.solvers.solvers.LinearSolver(conf, mtx=None, status=None, **kwargs)[source]
Abstract linear solver class.
Return tuple (eps_a, eps_r) of absolute and relative tolerance
settings. Either value can be None, meaning that the solver
does not use that setting.
class sfepy.solvers.solvers.NonlinearSolver(conf, fun=None, fun_grad=None, lin_solver=None, iter_hook=None, status=None, **kwargs)[source]
Abstract nonlinear solver class.
class sfepy.solvers.solvers.OptimizationSolver(conf, obj_fun=None, obj_fun_grad=None, status=None, obj_args=None, **kwargs)[source]
Abstract optimization solver class.
class sfepy.solvers.solvers.Solver(conf=None, **kwargs)[source]
Base class for all solver kinds. Takes care of processing of common
The factory method any_from_conf() can be used to create an instance of any
The subclasses have to reimplement __init__() and __call__(). The
subclasses that implement process_conf() have to call Solver.process_conf().
All solvers use the following configuration parameters:
name : str
The name referred to in problem description options.
kind : str
The solver kind, as given by the name class attribute of the Solver
verbose : bool
If True, the solver can print more information about the solution.
static any_from_conf(conf, **kwargs)
Create an instance of a solver class according to the configuration.
static process_conf(conf, kwargs=None)[source]
Ensures conf contains ‘name’ and ‘kind’.
class sfepy.solvers.solvers.TimeSteppingSolver(conf, **kwargs)[source]
Abstract time stepping solver class.