Adds distribution saving and cl args

tests.py

@@ -1,6 +1,10 @@
 import unittest
-from pprint import pprint
+import os.path
+import pickle
+import argparse
+import sys
 
+from pprint  import pprint
 from copycat import Copycat
 
 # TODO: update test cases to use entropy
@@ -19,38 +23,94 @@ _chiSquared_table = {
         10:18.307
         }
 
+class ChiSquaredException(Exception):
+    pass
+
+def chi_squared(actual, expected):
+    answerKeys = set(list(actual.keys()) + list(expected.keys()))
+    degreesFreedom = len(answerKeys)
+    chiSquared = 0
+
+    get_count = lambda k, d : d[k]['count'] if k in d else 0
+
+    for k in answerKeys:
+        E = get_count(k, expected)
+        O = get_count(k, actual)
+        if E == 0:
+            print('Warning! Expected 0 counts of {}, but got {}'.format(k, O))
+        else:
+            chiSquared += (O - E) ** 2 / E
+
+    if chiSquared >= _chiSquared_table[degreesFreedom]:
+        raise ChiSquaredException('Significant difference between expected and actual answer distributions: \n' +
+            'Chi2 value: {} with {} degrees of freedom'.format(chiSquared, degreesFreedom))
+
+class AnswerDistribution:
+    def __init__(self, initial, modified, target, iterations, distribution):
+        self.initial  = initial
+        self.modified = modified
+        self.target   = target
+        self.iterations   = iterations
+        self.distribution = distribution
+
+    def test(self):
+        print('expected:')
+        pprint(self.distribution)
+        actual = Copycat().run(self.initial,
+                self.modified,
+                self.target,
+                self.iterations)
+        print('actual:')
+        pprint(actual)
+        chi_squared(actual, self.distribution)
+
+    def generate(self):
+        self.distribution = Copycat().run(self.initial,
+                self.modified,
+                self.target,
+                self.iterations)
+
+        
 class TestCopycat(unittest.TestCase):
 
+    Filename = '.distributions'
+
     def setUp(self):
         self.longMessage = True  # new in Python 2.7
 
-    def assertProbabilitiesLookRoughlyLike(self, actual, expected, iterations):
-        answerKeys = set(list(actual.keys()) + list(expected.keys()))
-        degreesFreedom = len(answerKeys)
-        chiSquared = 0
+    def generate(self):
+        print('Generating distributions for new file')
+        iterations = 30
+        distributions = [
+                AnswerDistribution('abc', 'abd', 'efg',    iterations, None),
+                AnswerDistribution('abc', 'abd', 'ijk',    iterations, None),
+                AnswerDistribution('abc', 'abd', 'xyz',    iterations, None),
+                AnswerDistribution('abc', 'abd', 'ijkk',   iterations, None),
+                AnswerDistribution('abc', 'abd', 'mrrjjj', iterations, None)]
 
-        get_count = lambda k, d : d[k]['count'] if k in d else 0
+        for distribution in distributions:
+            distribution.generate()
 
-        for k in answerKeys:
-            E = get_count(k, expected)
-            O = get_count(k, actual)
-            if E == 0:
-                print('Warning! Expected 0 counts of {}, but got {}'.format(k, O))
-            else:
-                chiSquared += (O - E) ** 2 / E
+        with open(TestCopycat.Filename, 'wb') as outfile:
+            pickle.dump(distributions, outfile)
+        return distributions
 
-        if chiSquared >= _chiSquared_table[degreesFreedom]:
-            self.fail('Significant difference between expected and actual answer distributions: \n' +
-                'Chi2 value: {} with {} degrees of freedom'.format(chiSquared, degreesFreedom))
+    def test(self):
+        try:
+            with open(TestCopycat.Filename, 'rb') as infile:
+                distributions = pickle.load(infile)
+        except Exception as e:
+            print(e)
+            print('Generating due to error..')
+            distributions = self.generate()
 
+        for distribution in distributions:
+            distribution.test()
+
+    '''
     def run_testcase(self, initial, modified, target, iterations, expected):
-        print('expected:')
-        pprint(expected)
-        actual = Copycat().run(initial, modified, target, iterations)
-        print('actual:')
-        pprint(actual)
-        self.assertEqual(sum(a['count'] for a in list(actual.values())), iterations)
-        self.assertProbabilitiesLookRoughlyLike(actual, expected, iterations)
+        adist = AnswerDistribution(initial, modified, target, iterations, expected)
+        adist.test()
 
     def test_simple_cases(self):
         self.run_testcase('abc', 'abd', 'efg', 30, 
@@ -102,8 +162,7 @@ class TestCopycat(unittest.TestCase):
 			'count': 11},
 	     'mrrkkk': {'avgtemp': 43.709349775080746, 'avgtime': 1376.2, 'count': 10}})
 
-    '''
-    Below are examples of improvements that could be made to copycat.
+    # Below are examples of improvements that could be made to copycat.
 
     def test_elongation(self):
         # This isn't remotely what a human would say.
@@ -137,6 +196,15 @@ class TestCopycat(unittest.TestCase):
         })
     '''
 
-
 if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--generate', action='store_true')
+    parser.add_argument('filename', default='.distributions', nargs='?')
+    parser.add_argument('unittest_args', default=[], nargs='?')
+
+    args = parser.parse_args()
+    # TODO: Go do something with args.input and args.filename
+
+    # Now set the sys.argv to the unittest_args (leaving sys.argv[0] alone)
+    sys.argv[1:] = args.unittest_args
     unittest.main()