diff --git a/modules/base/pymod/stutil.py b/modules/base/pymod/stutil.py
index 474861c88e9e6586e947cfae7af348d85fb6ee54..1c485127ec202785126186195892dc96264e97a6 100644
--- a/modules/base/pymod/stutil.py
+++ b/modules/base/pymod/stutil.py
@@ -45,7 +45,7 @@ def Mean(xs):
"""
if len(xs)==0:
raise RuntimeError("Can't calculate mean of empty sequence")
- return sum(xs)/len(xs)
+ return float(sum(xs))/len(xs)
@FloatValueExtract
def Median(xs):
@@ -86,7 +86,7 @@ def Correl(xs, ys):
sum[(xi-<x>)*(yi-<y>)]
r=----------------------
- (n-1)*sx*sy
+ sx*sy
where <x>, <y> are the mean of dataset xs and ys, and, sx and sy are the
standard deviations.
@@ -103,9 +103,9 @@ def Correl(xs, ys):
cross_term+=(x-mean_x)*(y-mean_y)
sigma_x+=(x-mean_x)**2
sigma_y+=(y-mean_y)**2
- sigma_x=math.sqrt(sigma_x/len(xs))
- sigma_y=math.sqrt(sigma_y/len(ys))
- return cross_term/((len(xs)-1)*sigma_x*sigma_y)
+ sigma_x=math.sqrt(sigma_x)
+ sigma_y=math.sqrt(sigma_y)
+ return cross_term/(sigma_x*sigma_y)
def Histogram(xs, bounds, num_bins):
bins=[0 for i in range(num_bins)]
diff --git a/modules/base/tests/CMakeLists.txt b/modules/base/tests/CMakeLists.txt
index be13a37fffbbb6a8a52fd62c535ff856266c5726..d18e16f0765d8c2cd562338655b90f6ed9e97750 100644
--- a/modules/base/tests/CMakeLists.txt
+++ b/modules/base/tests/CMakeLists.txt
@@ -2,6 +2,7 @@ set(OST_BASE_UNIT_TESTS
test_generic_property.cc
test_string_ref.cc
test_pod_vector.cc
+ test_stutil.py
tests.cc
)
diff --git a/modules/base/tests/test_stutil.py b/modules/base/tests/test_stutil.py
new file mode 100644
index 0000000000000000000000000000000000000000..6c64f0e6b4f071f484f6220195b03a8faa446ddd
--- /dev/null
+++ b/modules/base/tests/test_stutil.py
@@ -0,0 +1,82 @@
+import unittest
+from ost import stutil
+
+class TestStUtils(unittest.TestCase):
+
+ def setUp(self):
+ self.data1 = [0,1,2,3,4,5,6,-5,-4,-3,-2,-1,1]
+ self.data2 = [1,2,3,4,5,6,7,8,9,10,11,12,13]
+ self.data3 = [0.1,0.5,0.7,2.4,0.5,4.1,0.9,-1.1,-0.5,0.7,-1.4,-7.5,8.5]
+
+ self.mean = 0.5384615385
+ self.mean2 = 0.6076923077
+ self.median = 1
+ self.median2 = 0.5
+ self.stddev = 3.3192998478
+ self.stddev2 = 3.4192805223
+ self.minimum = -5
+ self.minimum2 = -7.5
+ self.maximum = 6
+ self.maximum2 = 8.5
+ self.correl = -0.39639313
+ self.correl2 = -0.0619291504
+
+
+ def isSimilar(self, value, reference, accuracy):
+ if abs(value - reference) <= accuracy:
+ return True
+ return False
+
+ def testMean(self):
+ assert self.isSimilar(stutil.Mean(self.data1), self.mean, 0.001), \
+ "Mean (%f) does not correspond to precalculated mean (%f)" % \
+ (stutil.Mean(self.data1), self.mean)
+ assert self.isSimilar(stutil.Mean(self.data3), self.mean2, 0.001), \
+ "Mean (%f) does not correspond to precalculated mean (%f)" % \
+ (stutil.Mean(self.data3), self.mean2)
+
+ def testMedian(self):
+ assert self.isSimilar(stutil.Median(self.data1), self.median, 0.001), \
+ "Median (%f) does not correspond to precalculated median (%f)" % \
+ (stutil.Median(self.data1), self.median)
+ assert self.isSimilar(stutil.Median(self.data3), self.median2, 0.001), \
+ "Median (%f) does not correspond to precalculated median (%f)" % \
+ (stutil.Median(self.data3), self.median2)
+
+ def testStddev(self):
+ assert self.isSimilar(stutil.StdDev(self.data1), self.stddev, 0.001), \
+ "StdDev (%f) does not correspond to precalculated StdDev (%f)" % \
+ (stutil.StdDev(self.data1), self.stddev)
+ assert self.isSimilar(stutil.StdDev(self.data3), self.stddev2, 0.001), \
+ "StdDev (%f) does not correspond to precalculated StdDev (%f)" % \
+ (stutil.StdDev(self.data3), self.stddev2)
+
+ def testMinimum(self):
+ assert self.isSimilar(stutil.Min(self.data1), self.minimum, 0.001), \
+ "Minimum (%f) does not correspond to precalculated minimum (%f)" % \
+ (stutil.Min(self.data1), self.minimum)
+ assert self.isSimilar(stutil.Min(self.data3), self.minimum2, 0.001), \
+ "Minimum (%f) does not correspond to precalculated minimum (%f)" % \
+ (stutil.Min(self.data3), self.minimum2)
+
+ def testMaximum(self):
+ assert self.isSimilar(stutil.Max(self.data1), self.maximum, 0.001), \
+ "Maximum (%f) does not correspond to precalculated maximum (%f)" % \
+ (stutil.Max(self.data1), self.maximum)
+ assert self.isSimilar(stutil.Max(self.data3), self.maximum2, 0.001), \
+ "Maximum (%f) does not correspond to precalculated maximum (%f)" % \
+ (stutil.Max(self.data3), self.maximum2)
+
+ def testCorrel(self):
+ assert self.isSimilar(stutil.Correl(self.data1, self.data2), self.correl, 0.001), \
+ "Correl (%f) does not correspond to precalculated correl (%f)" % \
+ (stutil.Correl(self.data1, self.data2), self.correl)
+ assert self.isSimilar(stutil.Correl(self.data3, self.data2), self.correl2, 0.001), \
+ "Correl (%f) does not correspond to precalculated correl (%f)" % \
+ (stutil.Correl(self.data3, self.data2), self.correl2)
+
+if __name__ == "__main__":
+ try:
+ unittest.main()
+ except Exception, e:
+ print e
\ No newline at end of file