idmtools_calibra.resamplers.random_perturbation_resampler module

class idmtools_calibra.resamplers.random_perturbation_resampler.RandomPerturbationResampler(calib_manager=None, **kwargs)

Bases: idmtools_calibra.resamplers.base_resampler.BaseResampler

resample(calibrated_points, selection_values, initial_calibration_points)

Takes in a list of 1+ Point objects and returns method-specific resampled points as a list of Point objects The resultant Point objects should be copies of the input Points BUT with Value overridden on each, e.g.:

new_point = Point.copy(one_of_the_input_calibrated_points)
for param in new_point.list_params():
  new_point.set_param_value(param, value=SOME_NEW_VALUE)
Parameters
  • calibrated_points – input points for this resampling method

  • selection_values

  • initial_calibration_points

Returns

A list of resampled Point objects

post_analysis(resampled_points, analyzer_results, from_resample=None)
Parameters
  • resampled_points

  • analyzer_results

  • from_resample

Returns:

generate_perturbed_points(center_point) → pandas.core.frame.DataFrame

given center and generate perturbed points

Parameters

center_point – center point

Returns: