def test_build_markov_model_repetition(self):
model = markovmodeller.build_markov_model_from_string(
self.basic_text_repetition)
self.assertIsInstance(model, MarkovModel)
self.assertEqual(len(model), 5)
self.assertEqual(len(model.find_node_by_name("robot").connections), 1)
self.assertEqual(len(model.find_node_by_name("roBOT").connections), 1)
def test_build_markov_model_cyborg(self):
model = markovmodeller.build_markov_model_from_string(
self.basic_text_cyborg)
walk_string = markovmodeller.get_walk(model)
self.assertTrue("hello i am a robot ." == walk_string
or "hello i am a human ." == walk_string)
def test_build_markov_model_punctuation(self):
model = markovmodeller.build_markov_model_from_string(
self.text_punctuation)
self.assertEqual(len(model), 13)
start_node = model.get_start_node()
self.assertEqual(len(start_node.connections), 3)
self.assertEqual(len(model.find_node_by_name("i").connections), 1)
self.assertEqual(len(model.find_node_by_name("am").connections), 1)
def test_build_markov_model(self):
model = markovmodeller.build_markov_model_from_string(self.basic_text)
self.assertIsInstance(model, MarkovModel)
self.assertEqual(len(model), 6)
start_node = model.get_start_node()
self.assertEqual(len(start_node.connections), 1)
self.assertEqual(len(model.find_node_by_name("i").connections), 1)
self.assertEqual(len(model.find_node_by_name("am").connections), 1)
def test_build_markov_model_3_ways(self):
model = markovmodeller.build_markov_model_from_string(
self.basic_text_3_ways)
walk_string = markovmodeller.get_walk(model)
self.assertTrue("mr anderson ." == walk_string
or "madame bovary ." == walk_string
or "lord buckethead ." == walk_string)
def test_build_markov_model_multiple_2(self):
model = markovmodeller.build_markov_model_from_string(
self.basic_text_multiple_2)
self.assertIsInstance(model, MarkovModel)
self.assertEqual(len(model), 4)
start_node = model.get_start_node()
self.assertEqual(len(start_node.connections), 1)
self.assertEqual(len(model.find_node_by_name("you").connections), 3)
self.assertEqual(len(model.find_node_by_name("eat").connections), 1)
self.assertIsNone(model.find_node_by_name("definitelyNotAWord"))
def test_build_markov_model_cyborg_max_walk(self):
model = markovmodeller.build_markov_model_from_string(
self.basic_text_cyborg)
self.assertEqual(len(model), 7)
start_node = model.get_start_node()
self.assertEqual(len(start_node.connections), 1)
self.assertEqual(len(start_node.connections), 1)
self.assertEqual(start_node.connections[0].weight, 3)
self.assertEqual(len(model.find_node_by_name("i").connections), 1)
self.assertEqual(len(model.find_node_by_name("am").connections), 1)
self.assertEqual(len(model.find_node_by_name("a").connections), 2)
walk_string_max = markovmodeller.get_max_walk(model)
self.assertTrue("hello i am a robot ." == walk_string_max)
from nltk.corpus import gutenberg
from nltk.text import Text
from chatbot.markovgenerator import markovmodeller
if __name__ == "__main__":
my_essay = True
if my_essay:
txt = ""
with open('res/ans.txt') as text:
for line in text:
txt += line
model = markovmodeller.build_markov_model_from_string(txt)
else:
list_sentences = Text(gutenberg.sents('austen-sense.txt'))
model = markovmodeller.build_markov_model_from_list_of_sentences(
list_sentences)
while (True):
walk_string = markovmodeller.get_walk(model)
print(walk_string)
x = input("--- type X to stop")
if x == "X":
break
def test_basic_random_walk_2(self):
model = markovmodeller.build_markov_model_from_string(
self.basic_text_full_stop)
self.assertEqual(len(model), 6)
walk_string = markovmodeller.get_max_walk(model)
self.assertEqual("hello i am a robot .", walk_string)
def test_build_markov_model_repetition_normalise(self):
model = markovmodeller.build_markov_model_from_string(
self.basic_text_repetition_normalise)
self.assertIsInstance(model, MarkovModel)
self.assertEqual(len(model), 5)
