#!/usr/bin/env python

# -*- coding: utf-8 -*-

#===============================================================================

#

# Copyright (c) 2017 <> All Rights Reserved

#

#

# File: /Users/hain/ai/Synonyms/demo.py

# Author: Hai Liang Wang

# Date: 2017-09-28:22:23:34

#

#===============================================================================

"""

"""

from __future__ import print_function

from __future__ import division

__copyright__ = "Copyright (c) 2017 . All Rights Reserved"

__author__ = "Hai Liang Wang"

__date__ = "2017-09-28:22:23:34"

import os

import sys

curdir = os.path.dirname(os.path.abspath(__file__))

sys.path.append(curdir)

if sys.version_info[0] < 3:

reload(sys)

sys.setdefaultencoding("utf-8")

# raise "Must be using Python 3"

import synonyms # https://github.com/huyingxi/Synonyms

import numpy

import unittest

import thulac

# run testcase: python /Users/hain/ai/Synonyms/demo.py Test.testExample

class Test(unittest.TestCase):

'''

'''

def setUp(self):

pass

def tearDown(self):

pass

def testSenSimilarity(self):

'''

Generate sentence similarity

'''

sen1 = "旗帜引领方向"

sen2 = "道路决定命运"

assert synonyms.compare(sen1, sen2) == 0.0, "the similarity should be zero"

sen1 = "发生历史性变革"

sen2 = "取得历史性成就"

assert synonyms.compare(sen1, sen2) > 0, "the similarity should be bigger then zero"

def testNearbyWords(self):

thu1 = thulac.thulac() #默认模式

text = thu1.cut("人脸识别", text=True) #进行一句话分词

words, tags = [], []

data = [x.rsplit('_', 1) for x in text.split()]

for _ in data:

assert len(_) == 2, "seg len should be 2"

words.append(_[0])

tags.append(_[1])

for (k,v) in enumerate(tags):

if v.startswith("n") or v.startswith("v"): # 去停，去标，去副词、形容词、代词 etc.

synonyms.display(words[k]) # synonyms.display calls synonyms.nearby

def test():

unittest.main()

if __name__ == '__main__':

test()