idmtools_calibra.resamplers.random_perturbation_resampler module#

class idmtools_calibra.resamplers.random_perturbation_resampler.RandomPerturbationResampler(calib_manager=None, **kwargs)[source]#

Bases: BaseResampler

resample(calibrated_points, selection_values, initial_calibration_points)[source]#

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)[source]#
Parameters:

  • resampled_points –

  • analyzer_results –

  • from_resample –

Returns:

generate_perturbed_points(center_point) → DataFrame[source]#

given center and generate perturbed points

Parameters:

center_point – center point

Returns: