def test_create_paragraph_probability_plural_noun(self):
create_test_csvs(['dog', 'cat'], ['water'], ['like'], ['Abbey Normal'])
self.config_state['probability_pronoun'] = 0.0
self.config_state['probability_plural_noun'] = 1.0
pg = ParagraphsGenerator(self.config_state)
answer = pg.create_paragraph()
noun_values = [
'Dogs', 'The dogs', 'dogs', 'the dogs', 'Cats', 'The cats', 'cats',
'the cats', 'Water', 'The water', 'water', 'the water',
'Abbey Normal'
]
for sentence in answer:
self.assertIn(sentence[0].value, noun_values)
self.assertIn(sentence[2].value, noun_values)
pg.update_options({'probability_plural_noun': 0.0})
answer = pg.create_paragraph()
noun_values = [
'A dog', 'The dog', 'a dog', 'the dog', 'A cat', 'The cat',
'a cat', 'the cat', 'Water', 'The water', 'water', 'the water',
'Abbey Normal'
]
for sentence in answer:
self.assertIn(sentence[0].value, noun_values)
self.assertIn(sentence[2].value, noun_values)
def test_create_paragraph_paragraph_size(self):
self.config_state['paragraph_size'] = 5
pg = ParagraphsGenerator(self.config_state)
for _ in range(3):
self.assertEqual(len(pg.create_paragraph()), 5)
pg.update_options({'paragraph_size': 2})
for _ in range(3):
self.assertEqual(len(pg.create_paragraph()), 2)
def test_create_paragraph_probability_negative_verb(self):
create_test_csvs(['dog', 'cat'], ['water'], ['like'], ['Mom'])
self.config_state['probability_pronoun'] = 0.0
self.config_state['probability_plural_noun'] = 0.0
self.config_state['probability_negative_verb'] = 1.0
pg = ParagraphsGenerator(self.config_state)
answer = pg.create_paragraph()
verb_value = "doesn't like"
for sentence in answer:
self.assertEqual(verb_value, sentence[1].value)
pg.update_options({'probability_negative_verb': 0.0})
answer = pg.create_paragraph()
verb_value = "likes"
for sentence in answer:
self.assertEqual(verb_value, sentence[1].value)
def test_create_paragraph_probability_pronoun(self):
create_test_csvs(['dog'], ['water'], ['like'], [])
self.config_state['probability_pronoun'] = 0.0
pg = ParagraphsGenerator(self.config_state)
for _ in range(10):
paragraph = pg.create_paragraph()
for sentence in paragraph:
self.assertIsInstance(sentence[0], Noun)
self.assertIsInstance(sentence[2], Noun)
pg.update_options({'probability_pronoun': 1.0})
for _ in range(10):
paragraph = pg.create_paragraph()
for sentence in paragraph:
self.assertIsInstance(sentence[0], CapitalPronoun)
self.assertIsInstance(sentence[2], Pronoun)
def test_create_paragraph_tense(self):
create_test_csvs(['dog', 'cat'], ['water'], ['like'], ['Dad'])
self.config_state['probability_pronoun'] = 0.0
self.config_state['probability_negative_verb'] = 0.0
self.config_state['tense'] = 'simple_past'
pg = ParagraphsGenerator(self.config_state)
answer = pg.create_paragraph()
verb_value = "liked"
for sentence in answer:
self.assertEqual(verb_value, sentence[1].value)
def test_create_paragraph_pool_paragraph(self):
seed(8908)
create_test_csvs(['dog', 'cat'], ['water'], ['like'],
['My Great-Aunt Fanny'])
self.config_state['probability_pronoun'] = 0.0
self.config_state['paragraph_type'] = 'pool'
self.config_state['subject_pool'] = 1
pg = ParagraphsGenerator(self.config_state)
answer = pg.create_paragraph()
for sentence in answer:
self.assertIn('cat', sentence[0].value)
self.assertIsInstance(sentence[2], Noun)
self.assertNotIn('cat', sentence[2].value)
pg.update_options({'subject_pool': 2})
answer = pg.create_paragraph()
values = ['Water', 'The water', 'My Great-Aunt Fanny']
for sentence in answer:
self.assertIn(sentence[0].value, values)
self.assertIsInstance(sentence[2], Noun)
def test_create_paragraph_word_lists(self):
seed(1234)
create_test_csvs(['dog'], ['water'], ['like'], ['Frank'])
self.config_state['probability_pronoun'] = 0.0
self.config_state['paragraph_size'] = 2
pg = ParagraphsGenerator(self.config_state)
raw_answer = pg.create_paragraph()
answer = [[word.value for word in sentence] for sentence in raw_answer]
self.assertEqual(answer, [['Water', "doesn't like", 'Frank', '.'],
['Frank', 'likes', 'the water', '.']])
raw_answer = pg.create_paragraph()
answer = [[word.value for word in sentence] for sentence in raw_answer]
self.assertEqual(answer, [['Frank', "doesn't like", 'a dog', '.'],
['The dog', 'likes', 'Frank', '.']])
raw_answer = pg.create_paragraph()
answer = [[word.value for word in sentence] for sentence in raw_answer]
self.assertEqual(answer, [['Water', 'likes', 'Frank', '!'],
['Frank', 'likes', 'a dog', '.']])
def test_create_paragraph_chain_paragraph(self):
seed(4569)
create_test_csvs(['dog'], ['water'], ['like'], [])
self.config_state['probability_pronoun'] = 0.0
self.config_state['paragraph_type'] = 'chain'
pg = ParagraphsGenerator(self.config_state)
answer = pg.create_paragraph()
for index, sentence in enumerate(answer):
if index == 0:
self.assertEqual(sentence[0].value, 'Water')
self.assertEqual(sentence[2].value, 'a dog')
elif index % 2 == 0:
self.assertEqual(sentence[0].value, 'The water')
self.assertEqual(sentence[2].value, 'the dog')
else:
self.assertEqual(sentence[0].value, 'The dog')
self.assertEqual(sentence[2].value, 'the water')