Add test for different means of rejects over 1437.

reject-mean-test.py

@@ -0,0 +1,77 @@
+import numpy
+import sqlite3
+from scipy import stats
+
+# Build 1437 release
+# https://emu.freenetproject.org/pipermail/devl/2013-March/036860.html
+epoch = "strftime('%s', '2013-03-22')"
+
+query = """SELECT
+             "bulk_request_chk",
+             "bulk_request_ssk",
+             "bulk_insert_chk",
+             "bulk_insert_ssk"
+           FROM
+             "reject_stats"
+           WHERE
+             "time" """
+
+def apply_numpy(result, func):
+    means = []
+    if len(result) > 0:
+        for i in xrange(len(result[0])):
+            values = numpy.fromiter((entry[i] for entry in result), float, count=-1)
+            means.append(getattr(numpy, func)(values, dtype=numpy.float64))
+    return means
+
+reject_types = [ "Bulk Request CHK:",
+                 "Bulk Request SSK:",
+                 "Bulk Insert CHK:",
+                 "Bulk Insert SSK:" ]
+
+db = sqlite3.connect("database.sql")
+
+before = db.execute(query + " < " + epoch).fetchall()
+
+before_samples = len(before)
+
+print("Samples before epoch: {0:n}".format(before_samples))
+
+print("---Mean Before---")
+for element in zip(reject_types, apply_numpy(before, 'mean')):
+    print(element[0] + " {0:n}".format(element[1]))
+
+print("---Standard Deviation Before---")
+for element in zip(reject_types, apply_numpy(before, 'std')):
+    print(element[0] + " {0:n}".format(element[1]))
+
+after  = db.execute(query + " > " + epoch).fetchall()
+
+after_samples = len(after)
+
+print("Samples after epoch: {0:n}".format(after_samples))
+
+print("---Mean After---")
+for element in zip(reject_types, apply_numpy(after, 'mean')):
+    print(element[0] + " {0:n}".format(element[1]))
+
+print("---Standard Deviation After---")
+for element in zip(reject_types, apply_numpy(before, 'std')):
+    print(element[0] + " {0:n}".format(element[1]))
+
+print("---Pooled Two-Sample t-Test---")
+
+for element in zip(reject_types, range(len(reject_types))):
+    i = element[1]
+    # Assumption of equal variance checked by the rule of thumb that
+    # the ratio between the standard deviations of the sample not exceed
+    # about 2.
+    test_result = stats.ttest_ind(
+        numpy.fromiter((entry[i] for entry in before), int, count=-1),
+        numpy.fromiter((entry[i] for entry in after), int, count=-1))
+    # SciPy gives two-sided p-value. /2 for one-sided.
+    # t-statistic will be positive if the before mean is greater than
+    # the after mean:
+    # http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ttest_ind.html
+    # uses a - b.
+    print(element[0] + "t-statistic: {0:n} p-value: {1:n}".format(test_result[0], test_result[1]/2))