WIP: Add cross-chi-2 tests

tests.py

@@ -6,69 +6,25 @@ import sys
 
 from pprint  import pprint
 from copycat import Problem
+from copycat.statistics import iso_chi_squared
 
 # TODO: update test cases to use entropy
 
-# CHI2 values for n degrees freedom
-_chiSquared_table = {
-        1:3.841,
-        2:5.991,
-        3:7.815,
-        4:9.488,
-        5:11.071,
-        6:12.592,
-        7:14.067,
-        8:15.507,
-        9:16.919,
-        10:18.307
-        }
-
-class ChiSquaredException(Exception):
-    pass
-
-def chi_squared(actualDict, expectedDict):
-    for key in expectedDict.keys():
-        assert key in actualDict, 'The key {} was not tested'.format(key)
-        actual   = actualDict[key]
-        expected = expectedDict[key]
-
-        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))
-
 def generate():
     print('Generating distributions for new file')
     iterations = 30
-    distributions = [
-            Problem('abc', 'abd', 'efg',    iterations, None),
-            Problem('abc', 'abd', 'ijk',    iterations, None),
-            Problem('abc', 'abd', 'xyz',    iterations, None),
-            Problem('abc', 'abd', 'ijkk',   iterations, None),
-            Problem('abc', 'abd', 'mrrjjj', iterations, None)]
-
-    for distribution in distributions:
-        distribution.generate()
+    problems = [
+            Problem('abc', 'abd', 'efg',    iterations),
+            Problem('abc', 'abd', 'ijk',    iterations),
+            Problem('abc', 'abd', 'xyz',    iterations),
+            Problem('abc', 'abd', 'ijkk',   iterations),
+            Problem('abc', 'abd', 'mrrjjj', iterations)]
 
     with open(TestCopycat.Filename, 'wb') as outfile:
-        pickle.dump(distributions, outfile)
-    return distributions
-        
-class TestCopycat(unittest.TestCase):
+        pickle.dump(problems, outfile)
+    return problems
 
+class TestCopycat(unittest.TestCase):
     Filename = None
 
     def setUp(self):
@@ -78,14 +34,14 @@ class TestCopycat(unittest.TestCase):
         print('Testing copycat with input file: {}'.format(TestCopycat.Filename))
         try:
             with open(TestCopycat.Filename, 'rb') as infile:
-                distributions = pickle.load(infile)
+                problems = pickle.load(infile)
         except Exception as e:
             print('Generating due to error:')
             print(e)
-            distributions = generate()
+            problems = generate()
 
-        for distribution in distributions:
-            distribution.test(chi_squared)
+        for problem in problems:
+            problem.test(iso_chi_squared)
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()