def test__example_1_2(self):
has_kj = Discrete.from_probs(data={
'yes': 1e-5,
'no': 1 - 1e-5
},
variables='has_kj')
self.assertEqual(1e-5, has_kj.p(has_kj='yes'))
self.assertEqual(1 - 1e-5, has_kj.p(has_kj='no'))
eats_hbs__given__has_kj = Conditional.from_probs(
data={
('yes', 'yes'): 0.9,
('no', 'yes'): 0.1
},
joint_variables='eats_hbs',
conditional_variables='has_kj')
eats_hbs = Discrete.from_probs(data={
'yes': 0.5,
'no': 0.5
},
variables='eats_hbs')
# 1
has_kj__given__eats_hbs = eats_hbs__given__has_kj * has_kj / eats_hbs
self.assertEqual(
1.8e-5, has_kj__given__eats_hbs.p(has_kj='yes', eats_hbs='yes'))
# 2
eats_hbs = Discrete.from_probs(data={
'yes': 0.001,
'no': 0.999
},
variables='eats_hbs')
has_kj__given__eats_hbs = eats_hbs__given__has_kj * has_kj / eats_hbs
self.assertEqual(
9 / 1000, has_kj__given__eats_hbs.p(has_kj='yes', eats_hbs='yes'))
def test__example_1_3(self):
butler = Discrete.from_probs(data={
'yes': 0.6,
'no': 0.4
},
variables='butler')
maid = Discrete.from_probs(data={
'yes': 0.2,
'no': 0.8
},
variables='maid')
butler__and__maid = butler * maid
knife__given__butler__and__maid = Conditional.from_probs(
data={
('yes', 'no', 'no'): 0.3,
('yes', 'no', 'yes'): 0.2,
('yes', 'yes', 'no'): 0.6,
('yes', 'yes', 'yes'): 0.1,
('no', 'no', 'no'): 0.7,
('no', 'no', 'yes'): 0.8,
('no', 'yes', 'no'): 0.4,
('no', 'yes', 'yes'): 0.9,
},
joint_variables='knife_used',
conditional_variables=['butler', 'maid'])
butler__and__maid__and__knife = (knife__given__butler__and__maid *
butler__and__maid)
butler__given__knife = butler__and__maid__and__knife.given(
knife_used='yes').p(butler='yes')
self.assertAlmostEqual(0.728, butler__given__knife, 3)
def test__example_1_4(self):
occupied__given__alice__and__bob = Conditional.from_probs(
{
(True, False, False): 1,
(True, False, True): 1,
(True, True, False): 1,
(True, True, True): 0,
},
joint_variables='occupied',
conditional_variables=['alice', 'bob'])
alice__and__bob = Discrete.from_probs(
{
(False, False): 0.25,
(False, True): 0.25,
(True, False): 0.25,
(True, True): 0.25,
},
variables=['alice', 'bob'])
alice__and__bob__and__occupied = (occupied__given__alice__and__bob *
alice__and__bob)
self.assertEqual(
1,
alice__and__bob__and__occupied.given(alice=True,
occupied=True).p(bob=False))
def setUp(self) -> None:
self.education = Discrete.from_counts(
data={
('Male', 'Never finished high school'): 112,
('Male', 'High school'): 231,
('Male', 'College'): 595,
('Male', 'Graduate school'): 242,
('Female', 'Never finished high school'): 136,
('Female', 'High school'): 189,
('Female', 'College'): 763,
('Female', 'Graduate school'): 172,
},
variables=['gender', 'highest_education'])
self.education__total = 112 + 231 + 595 + 242 + 136 + 189 + 763 + 172
self.total__high_school = 231 + 189
self.coin_dist = Discrete.from_probs(
data={
('H', 'H', 1, 1): 0.25,
('H', 'T', 1, 0): 0.25,
('T', 'H', 1, 0): 0.25,
('T', 'T', 0, 1): 0.25
},
variables=['coin_1', 'coin_2', 'x', 'y'])
def test_max_numeric(self):
discrete = Discrete.from_probs(data={
0: 0.7,
1000: 0.2,
2000: 0.1
},
variables='a')
self.assertAlmostEqual(2000, discrete.max())
discrete_2 = Discrete.from_probs(data={
0: 0.7,
1000: 0.3,
2000: 0
},
variables='a')
self.assertAlmostEqual(1000, discrete_2.max())
def test_max_categorical(self):
discrete = Discrete.from_probs(data={
'a': 0.7,
'b': 0.2,
'c': 0.1
},
variables='x')
self.assertRaises(TypeError, discrete.max)
def test_mode_1d_numeric(self):
discrete = Discrete.from_probs(data={
0: 0.7,
1000: 0.2,
2000: 0.1
},
variables='a')
self.assertEqual(0, discrete.mode())
def setUp(self) -> None:
# cookies
self.bowl_1_and_chocolate = 0.125
self.bowl_1_and_vanilla = 0.375
self.bowl_2_and_chocolate = 0.25
self.bowl_2_and_vanilla = 0.25
cookie_data = TestChapter01.make_cookies_observations()
self.cookies = Discrete.from_observations(cookie_data)
self.vanilla = self.cookies.p(flavor='vanilla')
self.vanilla__bowl_1 = self.cookies.given(bowl='bowl 1').p(
flavor='vanilla')
self.vanilla__bowl_2 = self.cookies.given(bowl='bowl 2').p(
flavor='vanilla')
self.bowl = Discrete.from_probs({
'bowl 1': 0.5,
'bowl 2': 0.5
},
variables=['bowl'])
self.bowl_1 = self.bowl.p(bowl='bowl 1')
self.bowl_2 = self.bowl.p(bowl='bowl 2')
# m & m's
self.mix_1994 = Discrete.from_probs(
{
'brown': 0.3,
'yellow': 0.2,
'red': 0.2,
'green': 0.1,
'orange': 0.1,
'tan': 0.1
},
variables='color')
self.mix_1996 = Discrete.from_probs(
{
'blue': 0.24,
'green': 0.2,
'orange': 0.16,
'yellow': 0.14,
'red': 0.13,
'brown': 0.13
},
variables='color')
self.bag = Discrete.from_probs({1994: 0.5, 1996: 0.5}, variables='bag')
def test_mean_numeric(self):
discrete = Discrete.from_probs(data={
0: 0.7,
1000: 0.2,
2000: 0.1
},
variables='a')
self.assertAlmostEqual(0 * 0.7 + 1000 * 0.2 + 2000 * 0.1,
discrete.mean())
def test_from_probs__with_dict(self):
bowl = Discrete.from_probs({
'bowl 1': 0.5,
'bowl 2': 0.5
},
variables=['bowl'])
self.assertIsInstance(bowl, Discrete)
mix_1994 = Discrete.from_probs(
{
'brown': 0.3,
'yellow': 0.2,
'red': 0.2,
'green': 0.1,
'orange': 0.1,
'tan': 0.1
},
variables='color')
self.assertIsInstance(mix_1994, Discrete)
def test__1_3_1(self):
t = Discrete.from_observations(data=DataFrame({
't': [s_a + s_b for s_a, s_b in product(range(1, 7), range(1, 7))]
}))
s_a__s_b = Discrete.from_probs(data={
(a, b): 1 / 36
for a, b in product(range(1, 7), range(1, 7))
},
variables=['s_a', 's_b'])
t_9__given__s_a__s_b = Conditional.from_probs(
data={(9, a, b): int(a + b == 9)
for a, b in product(range(1, 7), range(1, 7))},
joint_variables=['t'],
conditional_variables=['s_a', 's_b'])
t_9__s_a__s_b = t_9__given__s_a__s_b * s_a__s_b
t_9 = t_9__s_a__s_b / t.p(t=9)
for s_a, s_b in product(range(1, 6), range(1, 6)):
self.assertEqual(t_9.p(s_a=s_a, s_b=s_b),
0.25 if s_a + s_b == 9 else 0)