-
Notifications
You must be signed in to change notification settings - Fork 0
/
test.py
93 lines (70 loc) · 3.41 KB
/
test.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
# Any changes to the distributions library should be reinstalled with
# pip install --upgrade .
# For running unit tests, use
# /usr/bin/python -m unittest test
import unittest
from Gaussiandistribution import Gaussian
from Binomialdistribution import Binomial
class TestGaussianClass(unittest.TestCase):
def setUp(self):
self.gaussian = Gaussian(25, 2)
self.gaussian.read_data_file('numbers.txt')
def test_initialization(self):
self.assertEqual(self.gaussian.mean, 25, 'incorrect mean')
self.assertEqual(self.gaussian.stdev, 2, 'incorrect standard deviation')
def test_readdata(self):
self.assertEqual(self.gaussian.data,\
[1, 3, 99, 100, 120, 32, 330, 23, 76, 44, 31], 'data not read in correctly')
def test_meancalculation(self):
self.assertEqual(self.gaussian.calculate_mean(),\
sum(self.gaussian.data) / float(len(self.gaussian.data)), 'calculated mean not as expected')
def test_stdevcalculation(self):
self.assertEqual(round(self.gaussian.calculate_stdev(), 2), 92.87, 'sample standard deviation incorrect')
self.assertEqual(round(self.gaussian.calculate_stdev(0), 2), 88.55, 'population standard deviation incorrect')
def test_pdf(self):
self.assertEqual(round(self.gaussian.pdf(25), 5), 0.19947,\
'pdf function does not give expected result')
self.gaussian.calculate_mean()
self.gaussian.calculate_stdev()
self.assertEqual(round(self.gaussian.pdf(75), 5), 0.00429,\
'pdf function after calculating mean and stdev does not give expected result')
def test_add(self):
gaussian_one = Gaussian(25, 3)
gaussian_two = Gaussian(30, 4)
gaussian_sum = gaussian_one + gaussian_two
self.assertEqual(gaussian_sum.mean, 55)
self.assertEqual(gaussian_sum.stdev, 5)
class TestBinomialClass(unittest.TestCase):
def setUp(self):
self.binomial = Binomial(0.4, 20)
self.binomial.read_data_file('numbers_binomial.txt')
def test_initialization(self):
self.assertEqual(self.binomial.p, 0.4, 'p value incorrect')
self.assertEqual(self.binomial.n, 20, 'n value incorrect')
def test_readdata(self):
self.assertEqual(self.binomial.data,\
[0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0], 'data not read in correctly')
def test_calculatemean(self):
mean = self.binomial.calculate_mean()
self.assertEqual(mean, 8)
def test_calculatestdev(self):
stdev = self.binomial.calculate_stdev()
self.assertEqual(round(stdev,2), 2.19)
def test_replace_stats_with_data(self):
p, n = self.binomial.replace_stats_with_data()
self.assertEqual(round(p,3), .615)
self.assertEqual(n, 13)
def test_pdf(self):
self.assertEqual(round(self.binomial.pdf(5), 5), 0.07465)
self.assertEqual(round(self.binomial.pdf(3), 5), 0.01235)
self.binomial.replace_stats_with_data()
self.assertEqual(round(self.binomial.pdf(5), 5), 0.05439)
self.assertEqual(round(self.binomial.pdf(3), 5), 0.00472)
def test_add(self):
binomial_one = Binomial(.4, 20)
binomial_two = Binomial(.4, 60)
binomial_sum = binomial_one + binomial_two
self.assertEqual(binomial_sum.p, .4)
self.assertEqual(binomial_sum.n, 80)
if __name__ == '__main__':
unittest.main()