def retro_analyze_experiment(predir):
'''Retro analyze an experiment'''
logger.info('Running retro_analyze_experiment')
trial_spec_paths = glob(f'{predir}/*_t*_spec.json')
# remove trial and session spec paths
experiment_spec_paths = ps.difference(glob(f'{predir}/*_spec.json'), trial_spec_paths)
experiment_spec_path = experiment_spec_paths[0]
spec = util.read(experiment_spec_path)
info_prepath = spec['meta']['info_prepath']
if not os.path.exists(f'{info_prepath}_trial_data_dict.json'):
return # only run analysis if experiment had been ran
trial_data_dict = util.read(f'{info_prepath}_trial_data_dict.json')
analysis.analyze_experiment(spec, trial_data_dict)
def retro_analyze_experiment(predir):
'''Retro analyze an experiment'''
logger.info('Running retro_analyze_experiment')
if ps.is_empty(glob(f'{predir}/info/*_trial_data_dict.json')):
logger.info(
'Skipping retro_analyze_experiment since no experiment was ran.')
return # only run analysis if experiment had been ran
trial_spec_paths = glob(f'{predir}/*_t*_spec.json')
# remove trial and session spec paths
experiment_spec_paths = ps.difference(glob(f'{predir}/*_spec.json'),
trial_spec_paths)
experiment_spec_path = experiment_spec_paths[0]
spec = util.read(experiment_spec_path)
info_prepath = spec['meta'].get('info_prepath')
trial_data_dict = util.read(f'{info_prepath}_trial_data_dict.json')
analysis.analyze_experiment(spec, trial_data_dict)
def run(self):
for t in range(_.get(self.spec, 'meta.max_trial')):
logger.debug(f'trial {t}')
(self.trial_df_dict[t],
self.trial_fitness_df_dict[t]) = self.init_trial().run()
self.df, self.fitness_df = analysis.analyze_experiment(self)
self.close()
return self.df, self.fitness_df
def retro_analyze_experiment(predir):
'''Retro-analyze all experiment level datas.'''
logger.info('Retro-analyzing experiment from file')
from slm_lab.experiment.control import Experiment
_, _, _, spec_name, _, _ = util.prepath_split(predir)
prepath = f'{predir}/{spec_name}'
spec, info_space = util.prepath_to_spec_info_space(prepath)
if 'search' not in spec:
return
experiment = Experiment(spec, info_space)
experiment.trial_data_dict = trial_data_dict_from_file(predir)
if not ps.is_empty(experiment.trial_data_dict):
return analysis.analyze_experiment(experiment)
def run(self):
self.trial_data_dict = self.search.run()
self.data = analysis.analyze_experiment(self)
self.close()
return self.data
def run(self):
trial_data_dict = search.run_ray_search(self.spec)
experiment_df = analysis.analyze_experiment(self.spec, trial_data_dict)
self.close()
return experiment_df
def run(self):
self.trial_data_dict = self.search.run()
self.data = analysis.analyze_experiment(self)
self.close()
return self.data