brent.py

Define the Brent class.

Based on implementation of the Brent algorithm in OpenMDAO 2.0 using brentq from scipy.

class openmdao.solvers.nonlinear.brent.BrentSolver(**kwargs)

Bases: NonlinearSolver

Brent solver.

Root finding using Brent’s method. This is a specialized solver that can only converge a single scalar residual. You must specify the name of the implicit state-variable via the state_target option. You must specify lower_bound and upper_bound for the upper and lower.

Parameters:

**kwargsdict

Options dictionary.

Attributes:

state_targetstr

Relative openmdao varpath to the state.

upper_targetstr or None

Relative openmdao varpath to the upper bound. Only used if the lower bound is computed somewhere in the model.

lower_targetstr or None

Relative openmdao varpath to the lower bound. Only used if the lower bound is computed somewhere in the model.

normfloat

The current norm.

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.
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.
record_iteration(**kwargs)	Record an iteration of the current Solver.
report_failure(msg)	Report a failure that has occurred.
solve()	Run the solver.
use_relevance()	Return True if relevance should be active.

SOLVER = 'NL: BRENT'

__init__(**kwargs)

Initialize all attributes.