tidy3d.plugins.dispersion.web.run(fitter: tidy3d.plugins.dispersion.fit.DispersionFitter, num_poles: pydantic.v1.types.PositiveInt = 1, num_tries: pydantic.v1.types.PositiveInt = 50, tolerance_rms: pydantic.v1.types.NonNegativeFloat = 0.01, advanced_param: tidy3d.plugins.dispersion.web.AdvancedFitterParam = AdvancedFitterParam(bound_amp=None, bound_f=None, bound_f_lower=0.0, bound_eps_inf=10.0, constraint='hard', nlopt_maxeval=5000, random_seed=0, type='AdvancedFitterParam')) Tuple[tidy3d.components.medium.PoleResidue, float]#

Execute the data fit using the stable fitter in the server.

  • fitter (DispersionFitter) – Fitter with the data to fit.

  • num_poles (PositiveInt, optional) – Number of poles in the model.

  • num_tries (PositiveInt, optional) – Number of optimizations to run with random initial guess.

  • tolerance_rms (NonNegativeFloat, optional) – RMS error below which the fit is successful and the result is returned.

  • advanced_param (AdvancedFitterParam, optional) – Advanced parameters passed on to the server.


Best results of multiple fits: (dispersive medium, RMS error).

Return type

Tuple[PoleResidue, float]