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)