rsopt.libe_tools.generator_functions package

Submodules

rsopt.libe_tools.generator_functions.local_opt_generator module

rsopt.libe_tools.generator_functions.particle_swarm module

rsopt.libe_tools.generator_functions.persistent_dlib module

rsopt.libe_tools.generator_functions.persistent_mobo module

rsopt.libe_tools.generator_functions.persistent_pysot module

rsopt.libe_tools.generator_functions.rsopt_localopt_support module

This module contains methods to interface with various local optimization routines.

class rsopt.libe_tools.generator_functions.rsopt_localopt_support.LocalOptInterfacer(user_specs, x0, f0, grad0=None)[source]

Bases: object

This class defines the localopt interface to various local optimization routines.

Currently supported routines are

  • NLopt routines [‘LN_SBPLX’, ‘LN_BOBYQA’, ‘LN_COBYLA’, ‘LN_NEWUOA’, ‘LN_NELDERMEAD’, ‘LD_MMA’]

  • SciPy routines [‘scipy_Nelder-Mead’, ‘scipy_COBYLA’, ‘scipy_BFGS’]

  • DFOLS [‘dfols’]

  • External local optimizer [‘external_localopt’] (which use files to pass/receive x/f values)

close()[source]

Join process and close queue

destroy()[source]

Recursively kill any optimizer processes still running

iterate(data)[source]

Returns an instance of either numpy.ndarray corresponding to the next iterative guess or ConvergedMsg when the solver has completed its run.

Parameters:

  • x_on_cube – A numpy array of the point being evaluated (for a handshake)

  • f – A numpy array of the function evaluation.

  • grad – A numpy array of the function’s gradient.

  • fvec – A numpy array of the function’s component values.

rsopt.libe_tools.generator_functions.rsopt_localopt_support.run_external_localopt(user_specs, comm_queue, x0, f0, child_can_read, parent_can_read)[source]

Runs an external local optimization run starting at x0, governed by the parameters in user_specs.

rsopt.libe_tools.generator_functions.rsopt_localopt_support.run_local_dfols(user_specs, comm_queue, x0, f0, child_can_read, parent_can_read)[source]

Runs a DFOLS local optimization run starting at x0, governed by the parameters in user_specs.

rsopt.libe_tools.generator_functions.rsopt_localopt_support.run_local_nlopt(user_specs, comm_queue, x0, f0, child_can_read, parent_can_read)[source]

Runs an NLopt local optimization run starting at x0, governed by the parameters in user_specs.

rsopt.libe_tools.generator_functions.rsopt_localopt_support.run_local_scipy_opt(user_specs, comm_queue, x0, f0, child_can_read, parent_can_read)[source]

Runs a SciPy local optimization run starting at x0, governed by the parameters in user_specs.

rsopt.libe_tools.generator_functions.sobal module

rsopt.libe_tools.generator_functions.sobal.uniform_random_sample(H, persis_info, gen_specs, _)[source]

Generates gen_specs['user']['gen_batch_size'] points uniformly over the domain defined by gen_specs['user']['ub'] and gen_specs['user']['lb'].

See also

test_uniform_sampling.py # noqa

rsopt.libe_tools.generator_functions.utility_generators module

rsopt.libe_tools.generator_functions.utility_generators.generate_mesh(H, persis_info, gen_specs, libE_info)[source]

Module contents