def test_compare_classifiers_predictions_distribution_vis_api( experiment_to_use): """Ensure pdf and png figures can be saved via visualization API call. :param experiment_to_use: Object containing trained model and results to test visualization :return: None """ experiment = experiment_to_use predictions = experiment.predictions_num viz_outputs = ('pdf', 'png') with TemporaryDirectory() as tmpvizdir: for viz_output in viz_outputs: vis_output_pattern_pdf = tmpvizdir + '/*.{}'.format( viz_output ) visualize.compare_classifiers_predictions_distribution( [predictions, predictions], experiment.ground_truth, experiment.ground_truth_metadata, experiment.output_feature_name, labels_limit=0, model_names=['Model1', 'Model2'], output_directory=tmpvizdir, file_format=viz_output ) figure_cnt = glob.glob(vis_output_pattern_pdf) assert 1 == len(figure_cnt)
def test_compare_classifiers_predictions_distribution_vis_api(csv_filename): """Ensure pdf and png figures can be saved via visualization API call. :param csv_filename: csv fixture from tests.fixtures.filenames.csv_filename :return: None """ experiment = Experiment(csv_filename) prediction = experiment.prediction viz_outputs = ('pdf', 'png') for viz_output in viz_outputs: vis_output_pattern_pdf = experiment.model.exp_dir_name + '/*.{}'.format( viz_output) visualize.compare_classifiers_predictions_distribution( [prediction, prediction], experiment.ground_truth, labels_limit=0, model_names=['Model1', 'Model2'], output_directory=experiment.model.exp_dir_name, file_format=viz_output) figure_cnt = glob.glob(vis_output_pattern_pdf) assert 1 == len(figure_cnt) shutil.rmtree(experiment.model.exp_dir_name, ignore_errors=True)