# encoding=utf-8

from recognize import tag
from segment import cut, hmm_cut, dict_cut, dag_segger
from abstract import get_abstract
from word2vec import Word2Vec

import os

def data_path(filename):
    return os.path.join(os.path.dirname(__file__), "%s" % filename)

def test_seg():
    cases = [
        "给你们传授一点人生的经验",
        "我来到北京清华大学",
        "长春市长春节讲话",
        "我们在野生动物园玩",
        "我只是做了一些微小的工作",
        "国庆节我在研究中文分词",
        "比起生存还是死亡来忠诚与背叛可能更是一个问题"
    ]
    for case in cases:
        result = dict_cut(case)
        print(result)

def test_tag():
    cases = [
        "给你们传授一点人生的经验",
        "我来到北京清华大学",
        "长春市长春节讲话",
        "我们在野生动物园玩",
        "我只是做了一些微小的工作",
        "国庆节我在研究中文分词",
        "比起生存还是死亡来忠诚与背叛可能更是一个问题"
    ]
    for case in cases:
        result = tag(case)
        print(result)

def test_abstract():
    fr = open(data_path('tmp/news.txt'), encoding='utf-8')

    case = ''
    for line in fr:
        line = line.strip()
        if line == '####':
            result = get_abstract(case)
            print(result)
            case = ''
        else:
            case += line

def test_word2vec():
    data = [
        'Merge multiple sorted inputs into a single sorted output',
        'The API below differs from textbook heap algorithms in two aspects'
    ]
    wv = Word2Vec(vec_len=50)
    wv.train(data, model='cbow')
    print(wv['into'])

def test():
    print("test seg:")
    test_seg()
    print("==========")
    #print("test tag:")
    #test_tag()
    #print("==========")
    #print("test abstract:")
    #test_abstract()
    #print("==========")
    #print("test word2vec:")
    #test_word2vec()
    #print("==========")

if __name__ == '__main__':
    test()