Exemple #1
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def test_markov_with_higher_level(size=100, file_name="sample1.txt"):
    markov = Markov()
    mark = markov.train_model_higher(
        normalize(os.getcwd() + "\\samples\\" + file_name))
    text = markov.generate_sentence(size, mark)
    save_text(text)
    save_long_file(text, file_name)
    print(text)
Exemple #2
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def main(argv):
    update_data = False
    generate_sentences = False
    interactive_mode = False
    if len(argv) < 2:
        print("No params specified. Using default values.")
        argv.extend(("-u", "-g"))
    args_dict = { i : True for i in argv }
    if "-u" in args_dict:
        update_data = True
    if "-g" in args_dict:
        generate_sentences = True
    if "-h" in args_dict:
        print(get_help_info()) 
        return
    if "-a" in args_dict:
        print(get_about_info())
        return
    if "-i" in args_dict:
        interactive_mode = True
    if update_data:
        dirname = "rawdata"
        shutil.rmtree(dirname, ignore_errors=True)
        filename = "news.zip"
        yesterday = datetime.date.today() - datetime.timedelta(days=1)
        network.download_file(network.URL.format(yesterday), filename)
        with zipfile.ZipFile(filename, 'r') as zip_ref:
            zip_ref.extractall(dirname)
        parse_files(dirname + "/day")
    
    if generate_sentences:
        markov = Markov(OUTFILE)
        markov.get_sentences()
    
    if interactive_mode:
        markov = Markov(OUTFILE)
        outfile = open(GOODFILE, 'a', encoding="utf-8") # TODO: post these news
        while True:
            sentence = markov.generate_sentence()
            print(sentence)
            user_input = getch()
            if user_input == "\x1b":
                break
            elif user_input == "+":
                outfile.write(sentence + "\n")
                pass
        outfile.close()
class TestMarkovMethods(unittest.TestCase):
    """Test the Markov-Chain."""

    def setUp(self):
        """Set up a Markov Chain instance for testing."""
        self.m = Markov()

    def test_new_word_entry(self):
        """Make sure that a new word and its next word are properly entered."""
        self.m.add_next_word('hello', 'world')
        self.assertEqual(self.m.chain, {'hello': ['world']})

    def test_additional_next_word_entry(self):
        """Test insertion of a new next word for an existing current word."""
        self.m.add_next_word('hello', 'world')
        self.m.add_next_word('hello', 'you')
        self.assertEqual(self.m.chain, {'hello': ['world', 'you']})

    def test_paragraph_entry(self):
        """
        Test insertion of a paragraph into the chains.

        Verify the logic concerning the period.
        """
        self.m.add_text(['hello', 'world', '.', 'goodnight', 'moon', '.'])
        self.assertEqual(self.m.chain, {
            '.': ['hello', 'goodnight'],
            'hello': ['world'],
            'world': ['.'],
            'goodnight': ['moon'],
            'moon': ['.']})

    def test_sentence_generation(self):
        """Test traversing through Markov-Chain dict to create sentence."""
        self.m.add_text(['hello', 'world', '.'])
        self.m.add_text(['hello', 'you', '.'])
        self.assertIn(
            self.m.generate_sentence(4), ['hello world.', 'hello you.'])
Exemple #4
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def gen_markov_higher(lst, size=100, file_name="sample1.txt"):
    markov = Markov()
    mark = markov.train_model_higher(normalize(os.getcwd() + "\\samples\\" + file_name))
    for i in range(30):
        lst.append(markov.generate_sentence(size, mark))
    return lst