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#!/usr/bin/env python3
import sys
from dfatool import EnergyModel, RawData
if __name__ == '__main__':
filenames = sys.argv[1:]
raw_data = RawData(filenames)
preprocessed_data = raw_data.get_preprocessed_data()
model = EnergyModel(preprocessed_data)
#print('--- simple static model ---')
#static_model = model.get_static()
#for state in model.states():
# print('{:10s}: {:.0f} µW ({:.2f})'.format(
# state,
# static_model(state, 'power'),
# model.generic_param_dependence_ratio(state, 'power')))
# for param in model.parameters():
# print('{:10s} dependence on {:15s}: {:.2f}'.format(
# '',
# param,
# model.param_dependence_ratio(state, 'power', param)))
#for trans in model.transitions():
# print('{:10s}: {:.0f} / {:.0f} / {:.0f} pJ ({:.2f} / {:.2f} / {:.2f})'.format(
# trans, static_model(trans, 'energy'),
# static_model(trans, 'rel_energy_prev'),
# static_model(trans, 'rel_energy_next'),
# model.generic_param_dependence_ratio(trans, 'energy'),
# model.generic_param_dependence_ratio(trans, 'rel_energy_prev'),
# model.generic_param_dependence_ratio(trans, 'rel_energy_next')))
# print('{:10s}: {:.0f} µs'.format(trans, static_model(trans, 'duration')))
#model.assess(static_model)
#print('--- LUT ---')
#lut_model = model.get_param_lut()
#model.assess(lut_model)
print('--- param model ---')
param_model, param_info = model.get_fitted()
for state in model.states():
for attribute in ['power']:
if param_info(state, attribute):
print('{:10s}: {}'.format(state, param_info(state, attribute)['function']._model_str))
for trans in model.transitions():
for attribute in ['energy', 'rel_energy_prev', 'rel_energy_next', 'duration', 'timeout']:
if param_info(trans, attribute):
print('{:10s}: {:10s}: {}'.format(trans, attribute, param_info(trans, attribute)['function']._model_str))
sys.exit(0)
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