def test_aggregate(self):
'''
Should return non-empty self.braidagg
'''
mc = MarkovChain(BraidWord([1, 2, 3]))
mc.model(num_braidreps=1, msteps=10)
# Check if non-empty
self.assertTrue(mc.aggregate())
def test_braidreps_1(self):
'''
Should return non-empty self.braidagg.braidreps
in word form
'''
mc = MarkovChain(BraidWord([1, 2, 3]))
mc.model(num_braidreps=1, msteps=10)
isos = mc.braidreps(as_word=True)
# Check if non-empty
self.assertTrue(isos)
# Check types
self.assertIsInstance(isos[0], list)
def test_topandas_1(self):
'''
Should return non-empty pandas df
of only BraidWords in word form
only_braidreps=True
'''
mc = MarkovChain(BraidWord([1, 2, 3]))
mc.model(num_braidreps=1, msteps=10)
df = mc.topandas(only_braidreps=True)
# Check df columns
self.assertTrue(df.shape[1] == 1)
self.assertTrue(list(df.columns) == ['braidreps'])
# Check if non-empty
self.assertFalse(df['braidreps'].empty)
# Check types of braidreps
self.assertIsInstance(df['braidreps'][0], list)
def test_init_pathfail_5(self):
"""
Should throw error if keyword argument
maxlen is negative
(kwargs)
"""
with self.assertRaises(ValueError) as ve:
MarkovChain(braidword=BraidWord([1, 2, 3]), maxgen=1, maxlen=-1)
def test_init_pathfail_3(self):
"""
Should throw error if argument maxLen
is negative
(args)
"""
with self.assertRaises(ValueError) as ve:
MarkovChain(BraidWord([1, 2, 3]), 1, -1)
def test_init_pathfail_1(self):
'''
Should throw error if number of arguments
is greater than three
(args)
'''
with self.assertRaises(Exception) as ex:
MarkovChain(BraidWord([1, 2, 3]), 0, 0, 0)
def test_init_pathsuccess_4(self):
"""
Should create MarkovChain with only list argument given
(kwargs)
"""
bw = MarkovChain(braidword=[1, 2, 3])
# Check types
self.assertEqual(type(bw.braid), BraidWord)
# Check words
self.assertEqual(bw.braid.word, BraidWord([1, 2, 3]).word)
def test_init_pathsuccess_1(self):
"""
Should create MarkovChain if all keyword arguments are valid
(kwargs)
"""
bw = MarkovChain(braidword=BraidWord([1, 2, 3]), maxgen=1, maxlen=1)
# Check types
self.assertEqual(type(bw.braid), BraidWord)
# Check words
self.assertEqual(bw.braid.word, BraidWord([1, 2, 3]).word)
self.assertEqual(bw.maxgen, 1)
self.assertEqual(bw.maxlen, 1)
def test_clear_model(self):
'''
Should clear the model leaving
self.braid_agg's components empty
'''
mc = MarkovChain(BraidWord([1, 2, 3]))
mc.model(num_braidreps=1, msteps=10)
mc.clear_model()
# Check if empty
self.assertFalse(mc.braidagg['braidreps'])
self.assertFalse(mc.braidagg['logs'])
def test_init_pathfail_0(self):
"""Should throw error if BraidWord not given"""
with self.assertRaises(Exception) as te:
MarkovChain()
