def _add_emotions_from_words(
words: Set[Optional[str]], words_emotions: Dict[str, List[Emotion]],
seasons_episodes_subtitles_emotions: Dict[int, Dict[int, List[TimeEmotion]]],
index: Tuple[int, int, int]) -> None:
season, episode, seconds = index
for word in [x for x in words if x]:
for emotion in words_emotions[word]:
seasons_episodes_subtitles_emotions[season][episode].append(
TimeEmotion(seconds=seconds, emotion=emotion))
def _add_emotions_from_sentence(
limbic_model: LexiconLimbicModel,
seasons_episodes_subtitles_emotions: Dict[int, Dict[int, List[TimeEmotion]]],
season_episode_time_sentence: Dict[int, Dict[int, Dict[int, List[str]]]],
index: Tuple[int, int, int]) -> None:
season, episode, seconds = index
for sentence in season_episode_time_sentence[season][episode][seconds]:
for emotion in limbic_model.get_sentence_emotions(sentence):
seasons_episodes_subtitles_emotions[season][episode].append(
TimeEmotion(seconds=seconds, emotion=emotion))
def get_subtitles_emotions(subtitles: List[Subtitle],
limbic_model: LexiconLimbicModel) -> Iterable[TimeEmotion]:
"""
Get emotions per second using TimeEmotion named tuple.
Each term per subtitle line is processed, and all emotions within a term
is listed independently.
Note that a given emotion will be mapped to the start of the subtitle time.
"""
for sub in subtitles:
for emotion in limbic_model.get_sentence_emotions(sub.content):
yield TimeEmotion(seconds=sub.start.seconds, emotion=emotion)
def _season_episode_emotions_from_dict(
season_episode_emotions_dict: Dict[str, Any]) -> Dict[int, Dict[int, List[TimeEmotion]]]:
"""
Utility method used to generate TimeEmotion from a dictionary with TimeEmotion data for a
series with season and episodes.
"""
output: Dict[int, Dict[int, List[TimeEmotion]]] = defaultdict(lambda: defaultdict(list))
for season, season_data in season_episode_emotions_dict.items():
for episode, episode_data in season_data.items():
for emotion in episode_data:
output[int(season)][int(episode)].append(
TimeEmotion(
seconds=emotion.get('seconds'),
emotion=Emotion(
category=emotion.get('category'),
value=emotion.get('value'),
term=emotion.get('term'))))
return output