本文整理汇总了Python中unittest.mock.Mock.char_bag方法的典型用法代码示例。如果您正苦于以下问题：Python Mock.char_bag方法的具体用法？Python Mock.char_bag怎么用？Python Mock.char_bag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unittest.mock.Mock的用法示例。
在下文中一共展示了Mock.char_bag方法的7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_train_pwd_long
# 需要导入模块: from unittest.mock import Mock [as 别名]
# 或者: from unittest.mock.Mock import char_bag [as 别名]
def test_train_pwd_long(self):
config = Mock()
config.char_bag = string.ascii_lowercase + pg.PASSWORD_END
m = mm.MarkovModel(config, smoothing='none', order=4)
m.train([('pa', 1)])
self.assertEqual(m.freq_dict, {
'p' : 1, 'pa' : 1, 'pa' + pg.PASSWORD_END : 1
})示例2: test_predict
# 需要导入模块: from unittest.mock import Mock [as 别名]
# 或者: from unittest.mock.Mock import char_bag [as 别名]
def test_predict(self):
config = Mock()
config.char_bag = pg.PASSWORD_END + 'aehnpst'
m = mm.MarkovModel(config, smoothing='none', order=2)
m.train([('pass', 1), ('past', 1), ('ashen', 1)])
answer = np.zeros((len(config.char_bag), ), dtype=np.float64)
m.predict('pa', answer)
np.testing.assert_array_equal(answer, np.array([
0, 0, 0, 0, 0, 0, 1, 0
]))示例3: test_train_one
# 需要导入模块: from unittest.mock import Mock [as 别名]
# 或者: from unittest.mock.Mock import char_bag [as 别名]
def test_train_one(self):
config = Mock()
config.char_bag = (
string.ascii_lowercase + pg.PASSWORD_END)
m = mm.BackoffMarkovModel(config, order=2)
m.train([('pass', 1)])
self.assertEqual(set(m.freq_dict.items()), set([
(mm.PASSWORD_START, 1), ('p', 1), ('a', 1), ('s', 2),
(pg.PASSWORD_END, 1), (mm.PASSWORD_START + 'p', 1),
('pa', 1), ('as', 1), ('ss', 1), ('s' + pg.PASSWORD_END, 1)
]))示例4: test_save_load_model
# 需要导入模块: from unittest.mock import Mock [as 别名]
# 或者: from unittest.mock.Mock import char_bag [as 别名]
def test_save_load_model(self):
config = Mock()
config.char_bag = string.ascii_lowercase + pg.PASSWORD_END
m = mm.MarkovModel(config, smoothing='none', order=2)
m.train([('pass', 1), ('past', 1), ('ashen', 1)])
self.assertAlmostEqual(m.probability_next_char('', 'p'), 2./3.)
with tempfile.NamedTemporaryFile('w') as tempf:
m.saveModel(tempf.name)
new_model = mm.MarkovModel.fromModelFile(
tempf.name, config, smoothing='none', order=2)
self.assertAlmostEqual(new_model.probability_next_char('', 'p'), 2./3.)示例5: test_train_one_pwd_no_smoothing
# 需要导入模块: from unittest.mock import Mock [as 别名]
# 或者: from unittest.mock.Mock import char_bag [as 别名]
def test_train_one_pwd_no_smoothing(self):
config = Mock()
config.char_bag = string.ascii_lowercase + pg.PASSWORD_END
m = mm.MarkovModel(config, smoothing='none', order=2)
m.train([('pass', 1)])
self.assertAlmostEqual(m.probability_next_char('p', 'a'), 1)
self.assertAlmostEqual(m.probability_next_char('pa', 's'), 1)
self.assertAlmostEqual(
m.probability_next_char('pass', pg.PASSWORD_END), .5)
self.assertAlmostEqual(m.probability_next_char('pas', 's'), .5)
self.assertAlmostEqual(m.probability_next_char('', 'p'), 1)
self.assertAlmostEqual(m.probability_next_char('pas', 'k'), 0)
self.assertAlmostEqual(m.probability_next_char('', 'j'), 0)示例6: test_predict_longer_context
# 需要导入模块: from unittest.mock import Mock [as 别名]
# 或者: from unittest.mock.Mock import char_bag [as 别名]
def test_predict_longer_context(self):
config = Mock()
config.char_bag = ('abc' + pg.PASSWORD_END)
config.backoff_smoothing_threshold = 0
config.additive_smoothing_amount = 0
m = mm.BackoffMarkovModel(config, order=3)
m.train([('abc', 1), ('aaa', 1)])
answer = np.zeros((len(config.char_bag), ), dtype=np.float64)
m.predict('ab', answer)
np.testing.assert_array_almost_equal(
answer, np.array([0., 0., 0., 1.], dtype=np.float64))
answer.fill(0)
m.predict('ba', answer)
np.testing.assert_array_almost_equal(
answer, np.array([.25, .5, .25, 0.], dtype=np.float64))示例7: test_train_high_order_no_smoothing
# 需要导入模块: from unittest.mock import Mock [as 别名]
# 或者: from unittest.mock.Mock import char_bag [as 别名]
def test_train_high_order_no_smoothing(self):
config = Mock()
config.char_bag = string.ascii_lowercase + pg.PASSWORD_END
m = mm.MarkovModel(config, smoothing='none', order=3)
m.train([('pass', 1), ('past', 1), ('ashen', 1)])
self.assertAlmostEqual(m.probability_next_char('', 'p'), 2./3.)
self.assertAlmostEqual(m.probability_next_char('p', 'a'), 1)
self.assertAlmostEqual(m.probability_next_char('pa', 's'), 1)
self.assertAlmostEqual(
m.probability_next_char('pass', pg.PASSWORD_END), 1)
self.assertAlmostEqual(m.probability_next_char('pas', 's'), 1./3.)
self.assertAlmostEqual(m.probability_next_char('pas', 't'), 1./3.)
self.assertAlmostEqual(m.probability_next_char('as', 'h'), 1./3.)
self.assertAlmostEqual(m.probability_next_char('as', 't'), 1./3.)
self.assertAlmostEqual(m.probability_next_char('pas', 'k'), 0)
self.assertAlmostEqual(m.probability_next_char('', 'j'), 0)