backend.data.AnalysisData

class backend.data.AnalysisData

__init__()

Initialize self. See help(type(self)) for accurate signature.

get_params()

Returns dict of this object’s attributes, excluding any attributes in the excluded_params list

get_settings_params()

Returns only the settings-related params; not the data

update_from_params(params)

Update this object’s attributes using the params dict. Any attributes in the excluded_params list will not be updated

slice(start=None, end=None, bools=None)

Just returns a deepcopy since there is no way to slice results yet.

clear_data()

Clear the evaluated test results

static concatenate(*data_objects)

Concatenate the data from the given objects into one. The settings from the first data object are used.

print_test_results(printer, print_data=True)

Prints the current test results to the given printer using the Result class’s print method

calc_results(output_data: backend.data.output_data.OutputData, trials, timestep: float, relax_pos=0, printer=<function empty_func>)

Calculates & returns the dictionary of test results for output_data using self.results

eval_dual_results(output_data: backend.data.output_data.OutputData)

eval_results(output_data, relax_pos=None, timestep=0.033, printer=<function empty_func>, stop_task_event=<backend.utils.DummyClass object>)

Calculate the test results using either the provided data or the current test data and the results specified in self.analysis_data.results

cross_validation(output_data, train_callback, test_callback, timestep=0.033, relax_pos=0, holdout_first=False, holdout_last=False, printer=<function empty_func>, stop_task_event=<backend.utils.DummyClass object>)

Return list of AnalysisData objects for each fold of cross validation

find_first_result(res_type: common.enums.ResultType)