from causal_world.metrics.metric_base import BaseMetric
import numpy as np
[docs]class MeanFullIntegratedFractionalSuccess(BaseMetric):
[docs] def __init__(self):
"""
The MeanFullIntegratedFractionalSuccess to be used to calculate the mean
of sum of fractional success over all episodes processed.
"""
super(MeanFullIntegratedFractionalSuccess,
self).__init__(name='full_integrated_fractional_success')
self.per_episode_scores = []
self.total_number_of_episodes = 0
return
[docs] def process_episode(self, episode_obj):
"""
Processes the episode to calculate the scores out of it.
:param episode_obj: (causal_world.loggers.Episode) episode to process
and calculate its metric.
:return:
"""
self.total_number_of_episodes += 1
in_episode_accumulated_success = 0.0
for info in episode_obj.infos:
in_episode_accumulated_success += info['fractional_success']
self.per_episode_scores.append(in_episode_accumulated_success / len(
episode_obj.infos))
[docs] def get_metric_score(self):
"""
:return: (tuple) the mean of the metric score,
the std of the metric score.
"""
return (np.mean(self.per_episode_scores), np.std(self.per_episode_scores))
[docs] def reset(self):
"""
resets the metric calculation of episodes.
:return:
"""
self.per_episode_scores = []
self.total_number_of_episodes = 0