def loadContext(user_id):
words_arr = loadWordsArr(user_id)
words_arr = removeStopList(words_arr)
length = len(words_arr)
context = Counter(words_arr).most_common()
context = map(lambda x: (x[0], x[1] / float(length)), context)
return context
def vectorize(self, text):
# better filter maybe
texts = text.split('\n')
#texts = filter(lambda t: not re.search('year', t), texts)
#texts = filter(lambda t: not re.search('old', t), texts)
texts = filter(lambda t: not re.search(r'\d{2} years old', t), texts)
text = '\n'.join(texts)
# Replace Twitter specific patterns.
#text = re.sub(r'https?:\S+', ' ', text)
#text = re.sub(r'\b\d{2} years old', ' ', text)
#text = re.sub(r'old', ' ', text)
#text = re.sub(r'years', ' ', text)
#text = re.sub(r'\d+', ' ', text)
#text = re.sub(r'#\w+', ' ', text)
#text = re.sub(r'@\w+', ' ', text)
# tokenize and remove stoplist
words_arr = re.findall(r'\w+', text)
words_arr = removeStopList(words_arr)
# normalize
length = len(words_arr)
context = Counter(words_arr).most_common()
context = map(lambda x: (x[0], x[1] / float(length)), context)
return context
def contextFromText(text):
text = replaceTWPattern(text)
words_arr = re.findall(r'\w+', text)
words_arr = removeStopList(words_arr)
length = len(words_arr)
context = Counter(words_arr).most_common()
context = map(lambda x: (x[0], x[1] / float(length)), context)
return context
def vectorize(self, text):
# better filter maybe
texts = text.split("\n")
texts = filter(lambda t: not re.search(r"\b(I am|I'm|Im) a (man|woman)\b", t, re.I), texts)
text = "\n".join(texts)
# tokenize and remove stoplist
words_arr = re.findall(r"\w+", text)
words_arr = removeStopList(words_arr)
# normalize
length = len(words_arr)
context = Counter(words_arr).most_common()
context = map(lambda x: (x[0], x[1] / float(length)), context)
return context