Adds cross-chi2 comparison script

copycat/statistics.py

@@ -29,29 +29,38 @@ def chi_squared(actual, expected):
             print('Warning! Expected 0 counts of {}, but got {}'.format(k, O))
         else:
             chiSquared += (O - E) ** 2 / E
-    return chiSquared
+    return degreesFreedom, chiSquared
+
+def chi_squared_test(actual, expected):
+    df, chiSquared = chi_squared(actual, expected)
+
+    if chiSquared >= _chiSquared_table[df]:
+        print('Significant difference between expected and actual answer distributions: \n' +
+            'Chi2 value: {} with {} degrees of freedom'.format(chiSquared, df))
+        return False
+    return True
 
 def cross_formula_chi_squared(actualDict, expectedDict):
     for ka, actual in actualDict.items():
         for ke, expected in expectedDict.items():
             print('Comparing {} with {}'.format(ka, ke))
-            chiSquared = chi_squared(actual, expected)
-
-            if chiSquared >= _chiSquared_table[degreesFreedom]:
-                print('Significant difference between expected and actual answer distributions: \n' +
-                    'Chi2 value: {} with {} degrees of freedom'.format(chiSquared, degreesFreedom))
+            chi_squared_test(actual, expected)
 
 def cross_chi_squared(problemSets):
     for i, problemSetA in enumerate(problemSets):
         for problemSetB in problemSets[i + 1:]:
             for problemA in problemSetA:
                 for problemB in problemSetB:
-                    answersA = problemA.distributions
-                    answersB = problemB.distributions
-                    cross_formula_chi_squared(answersA, answersB)
+                    if (problemA.initial  == problemB.initial and 
+                        problemA.modified == problemB.modified and
+                        problemA.target   == problemB.target):
+                        answersA = problemA.distributions
+                        answersB = problemB.distributions
+                        cross_formula_chi_squared(answersA, answersB)
 
 def iso_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]
+        chi_squared_test(actual, expected)

cross_compare.py

@@ -0,0 +1,23 @@
+#!/usr/bin/env python3
+import sys
+import pickle
+
+from copycat import Problem
+from copycat.statistics import cross_chi_squared
+
+def compare_sets():
+    pass
+
+def main(args):
+    branchProblemSets = dict()
+    problemSets = []
+    for filename in args:
+        with open(filename, 'rb') as infile:
+            pSet = pickle.load(infile)
+            branchProblemSets[filename] = pSet
+            problemSets.append(pSet)
+    cross_chi_squared(problemSets)
+    return 0
+
+if __name__ == '__main__':
+    sys.exit(main(sys.argv[1:]))