diff options
| -rwxr-xr-x | lib/dfatool.py | 23 |
1 files changed, 3 insertions, 20 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py index f7be534..535fb30 100755 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -627,13 +627,6 @@ def _try_fits(by_param, state_or_tran, model_attribute, param_index, safe_functi 'results' : results } -def _compute_param_statistics_parallel(args): - return { - 'state_or_trans' : args['state_or_trans'], - 'key' : args['key'], - 'result' : _compute_param_statistics(*args['args']) - } - def _all_params_are_numeric(data, param_idx): param_values = list(map(lambda x: x[param_idx], data['param'])) if len(list(filter(is_numeric, param_values))) == len(param_values): @@ -877,24 +870,14 @@ class EnergyModel: def _compute_all_param_statistics(self): - #queue = [] + # Note: This is deliberately single-threaded. The overhead incurred + # by multiprocessing is higher than the speed gained by parallel + # computation of statistics measures. for state_or_trans in self.by_name.keys(): self.stats[state_or_trans] = {} for key in self.by_name[state_or_trans]['attributes']: if key in self.by_name[state_or_trans]: self.stats[state_or_trans][key] = _compute_param_statistics(self.by_name, self.by_param, self._parameter_names, self._num_args, state_or_trans, key) - #queue.append({ - # 'state_or_trans' : state_or_trans, - # 'key' : key, - # 'args' : [self.by_name, self.by_param, self._parameter_names, self._num_args, state_or_trans, key] - #}) - - # IPC overhead for by_name/by_param (un)pickling is higher than - # multiprocessing speedup... so let's not do this. - #with Pool() as pool: - # results = pool.map(_compute_param_statistics_parallel, queue) - #for ret in results: - # self.stats[ret['state_or_trans']][ret['key']] = ret['result'] @classmethod def from_model(self, model_data, parameter_names): |