SLSQP

GPyOpt does this and that…

For details please refer to http://sheffieldml.github.io/GPyOpt/

Not sure why it is not showing the docstring and Args here below…?

class olympus.planners.Slsqp(*args, **kwargs)[source]

Sequential Least SQuares Programming (SLSQP) optimizers. SciPy implementation.

Parameters

  • goal (str) – The optimization goal, either ‘minimize’ or ‘maximize’. Default is ‘minimize’.

  • disp (bool) – Set to True to print convergence messages. If False, verbosity is ignored and set to 0.

  • eps (float) – Step size used for numerical approximation of the Jacobian.

  • ftol (float) – Precision goal for the value of f in the stopping criterion.

  • maxiter (int) – Maximum number of iterations.

  • init_guess (array, optional) – initial guess for the optimization

  • init_guess_method (str) – method to construct initial guesses if init_guess is not provided. Choose from: random

  • init_guess_seed (str) – random seed for init_guess_method

Methods

tell([observations])

Provide the planner with all previous observations.

ask([return_as])

suggest new set of parameters

recommend([observations, return_as])

Consecutively executes tell and ask: tell the planner about all previous observations, and ask about the next query point.

optimize(emulator[, num_iter, verbose])

Optimizes a surface for a fixed number of iterations.

set_param_space(param_space)

Defines the parameter space over which the planner will search.