shgo

despasito.parameter_fitting.global_methods.shgo

shgo(parameters_guess, bounds, fit_bead, fit_parameter_names, exp_dict, global_opts={}, minimizer_opts={}, constraints=None)[source]

Fit defined parameters for equation of state object using scipy.optimize.shgo with given experimental data.

Parameters:

  • parameters_guess (numpy.ndarray) – An array of initial guesses for parameters.

  • bounds (list[tuple]) – List of length equal to fit_parameter_names with lists of pairs for minimum and maximum bounds of parameter being fit. Defaults from Eos object are broad, so we recommend specification.

  • fit_bead (str) – Name of bead whose parameters are being fit.

  • fit_parameter_names (list[str]) – This list contains the name of the parameter being fit (e.g. epsilon). See EOS documentation for supported parameter names. Cross interaction parameter names should be composed of parameter name and the other bead type, separated by an underscore (e.g. epsilon_CO2).

  • exp_dict (dict) – Dictionary of experimental data objects.

  • global_opts (dict, Optional, default={}) –

    • init (str) - Optional, default=”random”, type of initiation for population

    • etc. Other keywords for scipy.optimize.shgo use the function defaults

  • minimizer_opts (dict, Optional, default={}) – Dictionary used to define minimization type and the associated options.

    • method (str) - Optional, default=nelder-mead, Method available to

    scipy.optimize.minimize - options (dict) - Optional, default={‘maxiter’: 50}, This dictionary contains the kwargs available to the chosen method

  • constraints (dict, Optional, default=None) – This dictionary of constraint types and their arguments will be converted into a tuple of dictionaries that is compatible

Returns:

Objective – scipy OptimizedResult object

Return type:

obj