scipy_iter_solver.py

Define the scipy iterative solver class.

class openmdao.solvers.linear.scipy_iter_solver.ScipyKrylov(**kwargs)

Bases: LinearSolver

The Krylov iterative solvers in scipy.sparse.linalg.

Parameters:

**kwargs{}

Dictionary of options set by the instantiating class/script.

Attributes:

preconSolver

Preconditioner for linear solve. Default is None for no preconditioner.

_lin_rhs_checkerLinearRHSChecker or None

Object for checking the right-hand side of the linear solve.

Methods

add_recorder(recorder)	Add a recorder to the solver's RecordingManager.
can_solve_cycle()	Return True if this solver can solve groups with cycles.
check_config(logger)	Perform optional error checks.
cleanup()	Clean up resources prior to exit.
does_recursive_applies()	Return False.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this solver are to be placed.
get_reports_dir()	Get the path to the directory where the report files should go.
preferred_sparse_format()	Return the preferred sparse format for the dr/do matrix of a split jacobian.
record_iteration(**kwargs)	Record an iteration of the current Solver.
report_failure(msg)	Report a failure that has occurred.
solve(mode[, rel_systems])	Run the solver.
use_relevance()	Return True if relevance should be active.

SOLVER = 'LN: SCIPY'

__init__(**kwargs)

Declare the solver option.

check_config(logger)

Perform optional error checks.

Parameters:

loggerobject

The object that manages logging output.

preferred_sparse_format()

Return the preferred sparse format for the dr/do matrix of a split jacobian.

Returns:

str

The preferred sparse format for the dr/do matrix of a split jacobian.

solve(mode, rel_systems=None)

Run the solver.

Parameters:

modestr

‘fwd’ or ‘rev’.

rel_systemsset of str

Names of systems relevant to the current solve. Deprecated.

use_relevance()

Return True if relevance should be active.

Returns:

bool

True if relevance should be active.