def main(): # Init. logging.basicConfig( level=logging.DEBUG) # TODO(alessio): INFO once debugged. parser = collect_data.InstanceArgumentsParser() parser.add_argument('-f', '--filename_suffix', help=('suffix of the exported file')) parser.description = ('Exports pre-computed APM module quality assessment ' 'results into HTML tables') args = parser.parse_args() # Get the scores. src_path = collect_data.ConstructSrcPath(args) logging.debug(src_path) scores_data_frame = collect_data.FindScores(src_path, args) # Export. output_filepath = os.path.join(args.output_dir, _BuildOutputFilename(args.filename_suffix)) exporter = export.HtmlExport(output_filepath) exporter.Export(scores_data_frame) logging.info('output file successfully written in %s', output_filepath) sys.exit(0)
def main(): # Init. # TODO(alessiob): INFO once debugged. logging.basicConfig(level=logging.DEBUG) parser = InstanceArgumentsParser() args = parser.parse_args() # Get the scores. src_path = collect_data.ConstructSrcPath(args) logging.debug(src_path) scores_data_frame = collect_data.FindScores(src_path, args) # Filter the data by `args.params_to_plot` scores_filtered = FilterScoresByParams(scores_data_frame, args.params_to_plot, args.eval_score, args.config_dir) data_list = sorted(scores_filtered.items()) data_values = [_FlattenToScoresList(x) for (_, x) in data_list] data_labels = [x for (x, _) in data_list] _, axes = plt.subplots(nrows=1, ncols=1, figsize=(6, 6)) axes.boxplot(data_values, labels=data_labels) axes.set_ylabel(args.eval_score) axes.set_xlabel('/'.join(args.params_to_plot)) plt.show()
def main(): # Init. # TODO(alessiob): INFO once debugged. logging.basicConfig(level=logging.DEBUG) parser = _InstanceArgumentsParser() args = parser.parse_args() # Get the scores. src_path = collect_data.ConstructSrcPath(args) logging.debug('Src path <%s>', src_path) scores_data_frame = collect_data.FindScores(src_path, args) all_scores = _ConfigurationAndScores(scores_data_frame, args.params, args.params_not_to_optimize, args.config_dir) opt_param = _FindOptimalParameter(all_scores, _ExampleWeighting) logging.info('Optimal parameter combination: <%s>', opt_param) logging.info('It\'s score values: <%s>', all_scores[opt_param])