def update_with_sentences(self, parsed_user):
# Check user input for names, focus appropriately
for word in parsed_user.split(' '):
base, pos = parse_utils.split_parsed(word)
if (pos == 'NNP'):
self.focus_on(base)
self.step()
def update_with_sentences(self, parsed_combined):
char_count = 0;
last_state_update = 0
for word in parsed_combined.split(' '):
char_count += len(word)
base, pos = parse_utils.split_parsed(word)
if (pos == 'JJ'):
base = base.lower()
if base in adjective_to_vector_map:
last_state_update = char_count
new_topic_vector = adjective_to_vector_map[base]
# Combine vectors in EWMA like way
self.topic = [self.topic_old_weight * old * 0.5 ** ((char_count - last_state_update) / self.topic_half_life) \
+ new * (1 - self.topic_old_weight) for old, new in zip(self.topic, new_topic_vector)]
# Decay for all remaining characters
self.topic = [x * 0.5 ** ((char_count - last_state_update) / self.topic_half_life) for x in self.topic]
