Added sample data, updated readme

README.md

@@ -1,15 +1,19 @@
 # Prob-Dists-GB
 
-Summary of the package
+Python package to model probability distributions.<br>
+Currently supports Gaussian and Binomial Distributions
 
 # Files
 
 Explanation of files in the package
 
 # Installation
 
-Steps to install
+```
+pip install Prob-Dists-GB
+```
+You can find the project on PyPi [here](https://pypi.org/project/Prob-Dists-GB/)
 
 # Licence
 
-MIT Licence
+[MIT Licence](LICENCE.txt)

numbers.txt

@@ -0,0 +1,11 @@
+1
+3
+99
+100
+120
+32
+330
+23
+76
+44
+31

numbers_binomial.txt

@@ -0,0 +1,13 @@
+0
+1
+1
+1
+1
+1
+0
+1
+0
+1
+0
+1
+0

test.py

@@ -0,0 +1,87 @@
+import unittest
+
+from distributions import Gaussian
+from distributions 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()