SciPy Optimizers
Bases: Optimizer
SciPy optimization backend for ropt.
This class provides an interface to several optimization algorithms from
SciPy's
scipy.optimize
module, enabling their use within ropt.
To select an optimizer, set the method field within the
optimizer section of the
EnOptConfig configuration object to the desired
algorithm's name. Most methods support the general options defined in the
EnOptConfig object. For algorithm-specific
options, use the options dictionary within the
optimizer section.
The table below lists the included methods together with the method-specific
options that are supported. Click on the method name to consult the
corresponding
scipy.optimize
documentation:
| Method | Method Options |
|---|---|
| Nelder-Mead | disp, maxiter, maxfev, xatol, fatol, adaptive |
| Powell | disp, maxiter, maxfev, xtol, ftol |
| CG | disp, maxiter, gtol, norm, eps, finite_diff_rel_step, c1, c2 |
| BFGS | disp, maxiter, gtol, norm, eps, finite_diff_rel_step, xrtol, c1, c2 |
| Newton-CG | disp, maxiter, xtol, eps, c1, c2 |
| L-BFGS-B | disp, maxiter, maxcor, ftol, gtol, eps, maxfun, iprint, maxls, finite_diff_rel_step |
| TNC | disp, maxfun, eps, scale, offset, maxCGit, eta, stepmx, accuracy, minfev, ftol, xtol, gtol, rescale, finite_diff_rel_step |
| COBYLA | disp, maxiter, rhobeg, tol, catol |
| SLSQP | disp, maxiter, ftol, eps, finite_diff_rel_step |
| differential_evolution | disp, maxiter, strategy, popsize, tol, mutation, recombination, rng, polish, init, atol, updating |