def __init__(self, target_filename=None, output_columns=None, header=0):
if target_filename is None:
msg = (
f"target_filename must be set for SimpleCSV. This should be"
f"the name of the output file this decoder acts on."
)
logging.error(msg)
raise RuntimeError(msg)
if output_columns is None:
msg = (
f"output_columns must be specified for SimpleCSV. This should"
f"be the names of the output columns this decoder extracts"
f"from the target csv file."
)
logging.error(msg)
raise RuntimeError(msg)
if len(output_columns) == 0:
msg = "output_columns cannot be empty."
logger.error(msg)
raise RuntimeError(msg)
self.target_filename = target_filename
self.output_columns = output_columns
self.header = header
self.output_type = OutputType('sample')
def __init__(self, target_filename=None, output_columns=None):
if target_filename is None:
msg = (
f"target_filename must be set for JSONDecoder. This should be"
f"the name of the output file this decoder acts on.")
logging.error(msg)
raise RuntimeError(msg)
if output_columns is None:
msg = (
f"output_columns must be specified for JSONDecoder. This should"
f"be the names of the output fields this decoder extracts"
f"from the target json file. For nested values use arrays"
f"e.g. ['root', 'node', 'field'] where field is the leaf"
f"that contains the value you need.")
logging.error(msg)
raise RuntimeError(msg)
if len(output_columns) == 0:
msg = "output_columns cannot be empty."
logger.error(msg)
raise RuntimeError(msg)
self.target_filename = target_filename
self.output_columns = output_columns
self.output_type = OutputType('sample')
def __init__(self, target_filename, cpo_name, output_columns):
if target_filename is None:
msg = (f"target_filename must be set for CPODecoder. This should be"
f"the name of the output file this decoder acts on.")
logging.error(msg)
raise Exception(msg)
if output_columns is None:
msg = (f"output_columns must be specified for CPODecoder.")
logging.error(msg)
raise Exception(msg)
if cpo_name is None:
msg = (f"cpo_name must be specified for CPODecoder.")
logging.error(msg)
raise Exception(msg)
if len(output_columns) == 0:
msg = "output_columns cannot be empty."
logger.error(msg)
raise Exception(msg)
self.target_filename = target_filename
self.cpo_name = cpo_name
self.output_columns = output_columns
self.output_type = OutputType('sample')
def __init__(self, target_filename, output_columns):
if len(output_columns) == 0:
msg = "output_columns cannot be empty."
logger.error(msg)
raise RuntimeError(msg)
self.target_filename = target_filename
self.output_columns = output_columns
self.output_type = OutputType('sample')
def __init__(self, target_filename=None):
if target_filename is None:
msg = (f"target_filename must be set for SimpleCSV. This should be"
f"the name of the output file this decoder acts on.")
logging.error(msg)
raise Exception(msg)
self.output_type = OutputType('sample')
self.target_filename = target_filename
def aggregate_samples(campaign, average=False, *args, **kwargs):
"""
Aggregate the results of all completed simulations described by the
Campaign.
Parameters
----------
campaign: `easyvvuq.Campaign`
Campaign from which to get simulation output to aggregate.
average:
Should the values read in be averaged (mean).
Returns
-------
`pd.DataFrame`:
Aggregated data from all completed runs referenced in the input Campaign.
"""
decoder = campaign.decoder
if decoder.output_type != OutputType.SAMPLE:
raise RuntimeError('Can only aggregate sample type data')
runs = campaign.runs
full_data = pd.DataFrame()
for run_id, run_info in runs.items():
if decoder.sim_complete(run_info=run_info, *args, **kwargs):
runs[run_id]['completed'] = True
run_data = decoder.parse_sim_output(run_info=run_info,
*args,
**kwargs)
if average:
run_data = pd.DataFrame(run_data.mean()).transpose()
column_list = list(run_info.keys()) + run_data.columns.tolist()
for param, value in run_info.items():
run_data[param] = value
# Reorder columns
run_data = run_data[column_list]
run_data['run_id'] = run_id
full_data = full_data.append(run_data, ignore_index=True)
data_dir = os.path.join(campaign.campaign_dir, 'data')
out_dir = tempfile.mkdtemp(dir=data_dir)
out_file = os.path.join(out_dir, 'aggregate_sample.tsv')
full_data.to_csv(out_file, sep='\t', index=False)
state_file = os.path.join(out_dir, 'state_snapshot.json')
campaign.save_state(state_file)
campaign.data = {
'files': [out_file],
'type': OutputType('summary').value,
'output_columns': decoder.output_columns,
'state': state_file
}
return full_data
def __init__(self, *args, **kwargs):
# Handles creation of `self.app_info` attribute (dicts)
super().__init__(*args, **kwargs)
self.output_type = OutputType('sample')
def __init__(self, *args, **kwargs):
self.output_type = OutputType('sample')
self.output_columns = []