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])