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#!/usr/bin/env python3
import getopt
import re
import sys
from dfatool import PTAModel, RawData, pta_trace_to_aggregate
opts = {}
def get_file_groups(args):
groups = []
index_low = 0
while ':' in args[index_low:]:
index_high = args[index_low:].index(':') + index_low
groups.append(args[index_low: index_high])
index_low = index_high + 1
groups.append(args[index_low:])
return groups
if __name__ == '__main__':
ignored_trace_indexes = []
discard_outliers = None
safe_functions_enabled = False
function_override = {}
show_models = []
show_quality = []
try:
optspec = (
'plot-unparam= plot-param= show-models= show-quality= '
'ignored-trace-indexes= discard-outliers= function-override= '
'with-safe-functions'
)
raw_opts, args = getopt.getopt(sys.argv[1:], "", optspec.split(' '))
for option, parameter in raw_opts:
optname = re.sub(r'^--', '', option)
opts[optname] = parameter
if 'ignored-trace-indexes' in opts:
ignored_trace_indexes = list(map(int, opts['ignored-trace-indexes'].split(',')))
if 0 in ignored_trace_indexes:
print('[E] arguments to --ignored-trace-indexes start from 1')
if 'discard-outliers' in opts:
discard_outliers = float(opts['discard-outliers'])
if 'function-override' in opts:
for function_desc in opts['function-override'].split(';'):
state_or_tran, attribute, *function_str = function_desc.split(' ')
function_override[(state_or_tran, attribute)] = ' '.join(function_str)
if 'show-models' in opts:
show_models = opts['show-models'].split(',')
if 'show-quality' in opts:
show_quality = opts['show-quality'].split(',')
if 'with-safe-functions' in opts:
safe_functions_enabled = True
except getopt.GetoptError as err:
print(err)
sys.exit(2)
score_absolute = 0
score_relative = 0
for file_group in get_file_groups(args):
print('')
print('{}:'.format(' '.join(file_group)))
raw_data = RawData(file_group)
preprocessed_data = raw_data.get_preprocessed_data(verbose=False)
by_name, parameters, arg_count = pta_trace_to_aggregate(preprocessed_data, ignored_trace_indexes)
model = PTAModel(by_name, parameters, arg_count,
traces=preprocessed_data,
ignore_trace_indexes=ignored_trace_indexes,
discard_outliers=discard_outliers,
function_override=function_override,
verbose=False)
lut_quality = model.assess(model.get_param_lut())
for trans in model.transitions():
absolute_quality = lut_quality['by_name'][trans]['energy']
relative_quality = lut_quality['by_name'][trans]['rel_energy_prev']
if absolute_quality['mae'] < relative_quality['mae']:
best = 'absolute'
score_absolute += 1
else:
best = 'relative'
score_relative += 1
print('{:20s}: {:s} (diff {:.0f} / {:.2f}%, abs {:.0f} / {:.2f}%, rel {:.0f} / {:.2f}%)'.format(
trans, best,
abs(absolute_quality['mae'] - relative_quality['mae']),
abs(absolute_quality['mae'] - relative_quality['mae']) * 100 / max(absolute_quality['mae'], relative_quality['mae']),
absolute_quality['mae'], absolute_quality['smape'],
relative_quality['mae'], relative_quality['smape']))
sys.exit(0)
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