Adds a modified copy of talk/base to webrtc/base. It is the first step in
migrating talk/base to webrtc/base.
BUG=N/A
R=niklas.enbom@webrtc.org
Review URL: https://webrtc-codereview.appspot.com/17479005
git-svn-id: http://webrtc.googlecode.com/svn/trunk@6129 4adac7df-926f-26a2-2b94-8c16560cd09d
diff --git a/webrtc/base/rollingaccumulator_unittest.cc b/webrtc/base/rollingaccumulator_unittest.cc
new file mode 100644
index 0000000..7e3d8cd
--- /dev/null
+++ b/webrtc/base/rollingaccumulator_unittest.cc
@@ -0,0 +1,118 @@
+/*
+ * Copyright 2011 The WebRTC Project Authors. All rights reserved.
+ *
+ * Use of this source code is governed by a BSD-style license
+ * that can be found in the LICENSE file in the root of the source
+ * tree. An additional intellectual property rights grant can be found
+ * in the file PATENTS. All contributing project authors may
+ * be found in the AUTHORS file in the root of the source tree.
+ */
+
+#include "webrtc/base/gunit.h"
+#include "webrtc/base/rollingaccumulator.h"
+
+namespace rtc {
+
+namespace {
+
+const double kLearningRate = 0.5;
+
+} // namespace
+
+TEST(RollingAccumulatorTest, ZeroSamples) {
+ RollingAccumulator<int> accum(10);
+
+ EXPECT_EQ(0U, accum.count());
+ EXPECT_DOUBLE_EQ(0.0, accum.ComputeMean());
+ EXPECT_DOUBLE_EQ(0.0, accum.ComputeVariance());
+ EXPECT_EQ(0, accum.ComputeMin());
+ EXPECT_EQ(0, accum.ComputeMax());
+}
+
+TEST(RollingAccumulatorTest, SomeSamples) {
+ RollingAccumulator<int> accum(10);
+ for (int i = 0; i < 4; ++i) {
+ accum.AddSample(i);
+ }
+
+ EXPECT_EQ(4U, accum.count());
+ EXPECT_EQ(6, accum.ComputeSum());
+ EXPECT_DOUBLE_EQ(1.5, accum.ComputeMean());
+ EXPECT_NEAR(2.26666, accum.ComputeWeightedMean(kLearningRate), 0.01);
+ EXPECT_DOUBLE_EQ(1.25, accum.ComputeVariance());
+ EXPECT_EQ(0, accum.ComputeMin());
+ EXPECT_EQ(3, accum.ComputeMax());
+}
+
+TEST(RollingAccumulatorTest, RollingSamples) {
+ RollingAccumulator<int> accum(10);
+ for (int i = 0; i < 12; ++i) {
+ accum.AddSample(i);
+ }
+
+ EXPECT_EQ(10U, accum.count());
+ EXPECT_EQ(65, accum.ComputeSum());
+ EXPECT_DOUBLE_EQ(6.5, accum.ComputeMean());
+ EXPECT_NEAR(10.0, accum.ComputeWeightedMean(kLearningRate), 0.01);
+ EXPECT_NEAR(9.0, accum.ComputeVariance(), 1.0);
+ EXPECT_EQ(2, accum.ComputeMin());
+ EXPECT_EQ(11, accum.ComputeMax());
+}
+
+TEST(RollingAccumulatorTest, ResetSamples) {
+ RollingAccumulator<int> accum(10);
+
+ for (int i = 0; i < 10; ++i) {
+ accum.AddSample(100);
+ }
+ EXPECT_EQ(10U, accum.count());
+ EXPECT_DOUBLE_EQ(100.0, accum.ComputeMean());
+ EXPECT_EQ(100, accum.ComputeMin());
+ EXPECT_EQ(100, accum.ComputeMax());
+
+ accum.Reset();
+ EXPECT_EQ(0U, accum.count());
+
+ for (int i = 0; i < 5; ++i) {
+ accum.AddSample(i);
+ }
+
+ EXPECT_EQ(5U, accum.count());
+ EXPECT_EQ(10, accum.ComputeSum());
+ EXPECT_DOUBLE_EQ(2.0, accum.ComputeMean());
+ EXPECT_EQ(0, accum.ComputeMin());
+ EXPECT_EQ(4, accum.ComputeMax());
+}
+
+TEST(RollingAccumulatorTest, RollingSamplesDouble) {
+ RollingAccumulator<double> accum(10);
+ for (int i = 0; i < 23; ++i) {
+ accum.AddSample(5 * i);
+ }
+
+ EXPECT_EQ(10u, accum.count());
+ EXPECT_DOUBLE_EQ(875.0, accum.ComputeSum());
+ EXPECT_DOUBLE_EQ(87.5, accum.ComputeMean());
+ EXPECT_NEAR(105.049, accum.ComputeWeightedMean(kLearningRate), 0.1);
+ EXPECT_NEAR(229.166667, accum.ComputeVariance(), 25);
+ EXPECT_DOUBLE_EQ(65.0, accum.ComputeMin());
+ EXPECT_DOUBLE_EQ(110.0, accum.ComputeMax());
+}
+
+TEST(RollingAccumulatorTest, ComputeWeightedMeanCornerCases) {
+ RollingAccumulator<int> accum(10);
+ EXPECT_DOUBLE_EQ(0.0, accum.ComputeWeightedMean(kLearningRate));
+ EXPECT_DOUBLE_EQ(0.0, accum.ComputeWeightedMean(0.0));
+ EXPECT_DOUBLE_EQ(0.0, accum.ComputeWeightedMean(1.1));
+
+ for (int i = 0; i < 8; ++i) {
+ accum.AddSample(i);
+ }
+
+ EXPECT_DOUBLE_EQ(3.5, accum.ComputeMean());
+ EXPECT_DOUBLE_EQ(3.5, accum.ComputeWeightedMean(0));
+ EXPECT_DOUBLE_EQ(3.5, accum.ComputeWeightedMean(1.1));
+ EXPECT_NEAR(6.0, accum.ComputeWeightedMean(kLearningRate), 0.1);
+}
+
+} // namespace rtc
