comparison search_model_validation.py @ 27:8e49f26b14d3 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"

26:9bb505eafac9

    warnings.simplefilter('ignore')

    with open(inputs, 'r') as param_handler:
        params = json.load(param_handler)

    params_builder = params['search_schemes']['search_params_builder']

    with open(infile_estimator, 'rb') as estimator_handler:
        estimator = load_model(estimator_handler)
    estimator_params = estimator.get_params()

            del main_est.fit_params
            del main_est.model_class_
            del main_est.validation_data
            if getattr(main_est, 'data_generator_', None):
                del main_est.data_generator_
                del main_est.data_batch_generator

        with open(outfile_object, 'wb') as output_handler:
            pickle.dump(best_estimator_, output_handler,
                        pickle.HIGHEST_PROTOCOL)

27:8e49f26b14d3

    warnings.simplefilter('ignore')

    with open(inputs, 'r') as param_handler:
        params = json.load(param_handler)

    # conflict param checker
    if params['outer_split']['split_mode'] == 'nested_cv' \
            and params['save'] != 'nope':
        raise ValueError("Save best estimator is not possible for nested CV!")

    if not (params['search_schemes']['options']['refit']) \
            and params['save'] != 'nope':
        raise ValueError("Save best estimator is not possible when refit "
                         "is False!")

    params_builder = params['search_schemes']['search_params_builder']

    with open(infile_estimator, 'rb') as estimator_handler:
        estimator = load_model(estimator_handler)
    estimator_params = estimator.get_params()

            del main_est.fit_params
            del main_est.model_class_
            del main_est.validation_data
            if getattr(main_est, 'data_generator_', None):
                del main_est.data_generator_

        with open(outfile_object, 'wb') as output_handler:
            pickle.dump(best_estimator_, output_handler,
                        pickle.HIGHEST_PROTOCOL)