コード例 #1
0
def get_users_data(user_name1, user_name2):
    user1 = engine.get_user_info(user_name1)
    user2 = engine.get_user_info(user_name2)

    db.save_user(user1.serialise())
    db.save_user(user2.serialise())

    timeline1 = tools.flush(user1.timeline, by_what=lambda x: tp.get_words(x['text'], is_normalise=True))[:10]
    timeline2 = tools.flush(user2.timeline, by_what=lambda x: tp.get_words(x['text'], is_normalise=True))[:10]
    print len(timeline1)
    print len(timeline2)
    mc1 = markov_chain_machine.create_model(timeline1, user_name1, boost)
    mc2 = markov_chain_machine.create_model(timeline2, user_name2, boost)

    return mc1, mc2
コード例 #2
0
    timeline1 = tools.flush(user1.timeline, by_what=lambda x: tp.get_words(x['text'], is_normalise=True))[:10]
    timeline2 = tools.flush(user2.timeline, by_what=lambda x: tp.get_words(x['text'], is_normalise=True))[:10]
    print len(timeline1)
    print len(timeline2)
    mc1 = markov_chain_machine.create_model(timeline1, user_name1, boost)
    mc2 = markov_chain_machine.create_model(timeline2, user_name2, boost)

    return mc1, mc2


def form_timeline(user_timeline):
    true_timeline = tools.flush(user_timeline, by_what=lambda x: tp.get_words(x['text'], is_normalise=True))
    return true_timeline

if __name__ == '__main__':
#    models = get_users_data('navalny', 'MedvedevRussia')
#    print diff_markov_chains(models[0], models[1])
#    engine.get_relations_of_user('navalny')

#    user = engine.get_user_info('GoogleRussia')
#    db.save_user(user.serialise())
#    user = db.get_user({'name_':'@GoogleRussia'})
#
#    print len(user.timeline)
#    print user.timeline_count

    user = db.get_user({'name_': '@GoogleRussia'})
    time_line = form_timeline(user.timeline)
    mc = markov_chain_machine.create_model(time_line,user.name_,boost)
    mc.print_me()
    diff_markov_chains(mc,mc)
コード例 #3
0
def prep_models(timeline):
    return [markov_chain_machine.create_model([message], hash(str(message)), booster) for message in timeline]