idmtools_calibra.calib_base_app module#


This function is called on every samples and allow the user to edit them before they are passed to the map_sample_to_model_input function. It is useful to round some parameters as demonstrated below. #Can do much more here, e.g. for Clinical Fever Threshold High < MSP1 Merozoite Kill Fraction if ‘Clinical Fever Threshold High’ and “MSP1 Merozoite Kill Fraction” in sample: sample[‘Clinical Fever Threshold High’] = min( sample[‘Clinical Fever Threshold High’], sample[‘MSP1 Merozoite Kill Fraction’] ). You can omit this function by not specifying it in the OptimTool constructor call below. :param sample: The sample coming from the next point algorithm

Returns: The sample with constrained values

idmtools_calibra.calib_base_app.map_sample_to_model_input(simulation, sample)[source]#

This method maps the samples generated by the next point algorithm to the model inputs (via the simulation object). All parameters specified for dynamic calibration (above) that do not have a MapTo value must have associated mapping logic in this method. :param simulation: idmtools simulation :param sample: The sample containing a values for all the params. e.g. {‘Clinical Fever Threshold High’:1, … }

Returns: A dictionary containing the tags that will be attached to the simulation

idmtools_calibra.calib_base_app.init(settings, site, task=None, platform=None)[source]#
idmtools_calibra.calib_base_app.go(calib_manager, **kwargs)[source]#