本文整理汇总了Python中markov.Markov.make_ngram_freqs_dict方法的典型用法代码示例。如果您正苦于以下问题：Python Markov.make_ngram_freqs_dict方法的具体用法？Python Markov.make_ngram_freqs_dict怎么用？Python Markov.make_ngram_freqs_dict使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类markov.Markov的用法示例。
在下文中一共展示了Markov.make_ngram_freqs_dict方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: Test_Markov
# 需要导入模块: from markov import Markov [as 别名]
# 或者: from markov.Markov import make_ngram_freqs_dict [as 别名]
class Test_Markov(unittest.TestCase):
def setUp(self):
self.test_text = "I have bought this bonnet.\r\nI am Mr. Darcy.\r\nI am.\r\n"
with open("in.txt",'w') as f:
f.write(self.test_text)
self.test_outfile = "out.txt"
ospl.process_data("in.txt", self.test_outfile, True)
self.test_markov = Markov(self.test_outfile)
def test_unigrams(self):
self.assertEqual(type(self.test_markov.unigrams), defaultdict)
self.assertEqual(round(sum(self.test_markov.unigrams.values()), 5), 1.0)
self.assertEqual(self.test_markov.unigrams["**Beginning**"], 0.15)
def test_bigrams(self):
self.assertEqual(type(self.test_markov.bigrams), defaultdict)
self.assertEqual(round(sum(self.test_markov.bigrams["I"].values()), 5), 1.0)
self.assertEqual(self.test_markov.bigrams["**Beginning**"]["I"], 1.0)
self.assertEqual(self.test_markov.bigrams["I"]["have"], 1/3.)
def test_bigrams_counter(self):
bigram_freqs = self.test_markov.make_ngram_freqs_dict(2)
self.assertEqual(type(bigram_freqs), defaultdict)
self.assertEqual(bigram_freqs["I"]["am"], 2)
self.assertEqual(bigram_freqs["."]["**End**"], 3)
def test_trigrams(self):
self.assertEqual(type(self.test_markov.trigrams), defaultdict)
self.assertEqual(round(sum(self.test_markov.trigrams[("I","am")].values()), 5), 1.0)
self.assertEqual(self.test_markov.trigrams[("**Beginning**","I")]["am"], 2/3.)
self.assertEqual(self.test_markov.trigrams[("I","have")]["rocketships"], 1e-5)
def test_trigrams_counter(self):
trigram_freqs = self.test_markov.make_ngram_freqs_dict(3)
self.assertEqual(type(trigram_freqs), defaultdict)
self.assertEqual(trigram_freqs[("Darcy",".")]["**End**"], 1)
self.assertEqual(trigram_freqs[("**Beginning**","I")]["am"], 2)
def test_make_sentence(self):
self.test_markov.make_ngram_sentence(n=2)
self.test_markov.make_ngram_sentence(n=3)
self.assertRaises(AssertionError, self.test_markov.make_ngram_sentence, n=5)
def test_score_sentence(self):
""" make up nonsense sentence, make sure it scores worse than Markov sentence. possibly also make up word with same words as corpus but in a completly bogus order, that should also score lower"""
nonsense = "Vestiges of cetaceous gentility."
nonsense_score = self.test_markov.score_sentence(nonsense)
real_trigram_sent = self.test_markov.make_ngram_sentence()
real_trigram_score = self.test_markov.score_sentence(real_trigram_sent)
weird_order = "Darcy . I bonnet am bought have am"
weird_order_score = self.test_markov.score_sentence(weird_order)
self.assertGreater(nonsense_score, real_trigram_score)
self.assertGreater(weird_order_score, real_trigram_score)
def tearDown(self):
os.remove("in.txt")
os.remove("out.txt")