def extract(self, sample):
result = FeatureResult(self._short_name)
num_syllables = []
words = self._get_words(sample)
# Create a list of the number of syllables of each word
for word in words :
num_syllables.append(syllables_en.count(word))
result.value = float(sum(num_syllables)) / float(len(words))
return [result]
def __analyze_text(self, sample):
""" Calculates a few properties that are needed for analysis"""
words = self._get_words(sample)
self.word_count = len(words)
self.char_count = len(sample.plain_text)
for word in words:
self.syllable_count += syllables_en.count(word)
self.sentence_count = len(nltk.sent_tokenize(sample.plain_text))
self.avg_words_per_sentence = float(self.word_count) / \
float(self.sentence_count)
def count_syllables(lines):
"""Syllables in a line for each line"""
return np.array(list(syllables.count(l) for l in lines))
def nsyl(self, word):
return SE.count(word)