def __init__(self,
experiment_df,
output_directory,
plotter,
experiment_name=None):
if experiment_name:
self.name = experiment_name
else:
# Take name from first row.
self.name = experiment_df.experiment.iloc[0]
# FuzzBench repo commit hash.
self.git_hash = None
if 'git_hash' in experiment_df.columns:
# Not possible to represent hashes for multiple experiments.
if len(experiment_df.experiment.unique()) == 1:
self.git_hash = experiment_df.git_hash.iloc[0]
# Earliest trial start time.
self.started = experiment_df.time_started.dropna().min()
# Latest trial end time.
self.ended = experiment_df.time_ended.dropna().max()
# Keep data frame without non-interesting columns.
self._experiment_df = data_utils.drop_uninteresting_columns(
experiment_df)
# Directory where the rendered plots are written to.
self._output_directory = output_directory
self._plotter = plotter
def __init__(self,
experiment_df,
output_directory,
plotter,
experiment_name=None):
if experiment_name:
self.name = experiment_name
else:
# Take name from first row.
self.name = experiment_df.experiment[0]
# Earliest trial start time.
self.started = experiment_df.time_started.min()
# Latest trial end time.
self.ended = experiment_df.time_ended.max()
# Keep data frame without non-interesting columns.
self._experiment_df = data_utils.drop_uninteresting_columns(
experiment_df)
# Directory where the rendered plots are written to.
self._output_directory = output_directory
self._plotter = plotter
self.git_hash = data_utils.get_git_hash(experiment_df)
def __init__( # pylint: disable=too-many-arguments
self,
experiment_df,
coverage_dict,
output_directory,
plotter,
experiment_name=None):
if experiment_name:
self.name = experiment_name
else:
# Take name from first row.
self.name = experiment_df.experiment.iloc[0]
# FuzzBench repo commit hash.
self.git_hash = None
if 'git_hash' in experiment_df.columns:
# Not possible to represent hashes for multiple experiments.
if len(experiment_df.experiment.unique()) == 1:
self.git_hash = experiment_df.git_hash.iloc[0]
# Earliest trial start time.
self.started = experiment_df.time_started.dropna().min()
# Latest trial end time.
self.ended = experiment_df.time_ended.dropna().max()
# Keep a full version of the dataframe (to count unique bugs)
self._full_experiment_df = experiment_df
# Keep data frame without non-interesting columns.
experiment_df = data_utils.drop_uninteresting_columns(experiment_df)
# Add relative columns (% of experiment max, % of fuzzer max)
self._experiment_df = data_utils.add_relative_columns(experiment_df)
# Directory where the rendered plots are written to.
self._output_directory = output_directory
self._plotter = plotter
# Dictionary to store the full coverage data.
self._coverage_dict = coverage_dict
def test_drop_uniteresting_columns():
experiment_df = create_experiment_data()
cleaned_df = data_utils.drop_uninteresting_columns(experiment_df)
assert 'time_started' not in cleaned_df.columns
