brent.py¶
-
class
openmdao.solvers.brent.
Brent
[source]¶ Bases:
openmdao.solvers.solver_base.NonLinearSolver
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 state-variable/residual via the state_var option. You must also give either lower_bound and upper_bound or var_lower_bound and var_upper_bound.
Options: options[‘iprint’] : int(0)
Set to 0 to disable printing, set to 1 to print the residual to stdout each iteration, set to 2 to print subiteration residuals as well.
options[‘max_iter’] : int(100)
if convergence is not achieved in maxiter iterations, and error is raised. Must be >= 0.
options[‘rtol’] : float64(4.4408920985e-16)
The routine converges when a root is known to lie within rtol times the value returned of the value returned. Should be >= 0. Defaults to np.finfo(float).eps * 2.
options[‘state_var’] : str(‘’)
name of the state-variable/residual the solver should with
options[‘upper_bound’] : float(100.0)
upper bound for the root search
options[‘lower_bound’] : float(0.0)
lower bound for the root search
options[‘var_lower_bound’] : str(‘’)
if given, name of the variable to pull the lower bound value from.This variable must be a parameter on of of the child components of the containing system
options[‘var_upper_bound’] : str(‘’)
if given, name of the variable to pull the upper bound value from.This variable must be a parameter on of of the child components of the containing system
options[‘xtol’] : int(0)
The routine converges when a root is known to lie within xtol of the value return. Should be >= 0. The routine modifies this to take into account the relative precision of doubles.