1/*
2 *  Copyright 2011 The WebRTC Project Authors. All rights reserved.
3 *
4 *  Use of this source code is governed by a BSD-style license
5 *  that can be found in the LICENSE file in the root of the source
6 *  tree. An additional intellectual property rights grant can be found
7 *  in the file PATENTS.  All contributing project authors may
8 *  be found in the AUTHORS file in the root of the source tree.
9 */
10
11#include "webrtc/base/gunit.h"
12#include "webrtc/base/rollingaccumulator.h"
13
14namespace rtc {
15
16namespace {
17
18const double kLearningRate = 0.5;
19
20}  // namespace
21
22TEST(RollingAccumulatorTest, ZeroSamples) {
23  RollingAccumulator<int> accum(10);
24
25  EXPECT_EQ(0U, accum.count());
26  EXPECT_DOUBLE_EQ(0.0, accum.ComputeMean());
27  EXPECT_DOUBLE_EQ(0.0, accum.ComputeVariance());
28  EXPECT_EQ(0, accum.ComputeMin());
29  EXPECT_EQ(0, accum.ComputeMax());
30}
31
32TEST(RollingAccumulatorTest, SomeSamples) {
33  RollingAccumulator<int> accum(10);
34  for (int i = 0; i < 4; ++i) {
35    accum.AddSample(i);
36  }
37
38  EXPECT_EQ(4U, accum.count());
39  EXPECT_EQ(6, accum.ComputeSum());
40  EXPECT_DOUBLE_EQ(1.5, accum.ComputeMean());
41  EXPECT_NEAR(2.26666, accum.ComputeWeightedMean(kLearningRate), 0.01);
42  EXPECT_DOUBLE_EQ(1.25, accum.ComputeVariance());
43  EXPECT_EQ(0, accum.ComputeMin());
44  EXPECT_EQ(3, accum.ComputeMax());
45}
46
47TEST(RollingAccumulatorTest, RollingSamples) {
48  RollingAccumulator<int> accum(10);
49  for (int i = 0; i < 12; ++i) {
50    accum.AddSample(i);
51  }
52
53  EXPECT_EQ(10U, accum.count());
54  EXPECT_EQ(65, accum.ComputeSum());
55  EXPECT_DOUBLE_EQ(6.5, accum.ComputeMean());
56  EXPECT_NEAR(10.0, accum.ComputeWeightedMean(kLearningRate), 0.01);
57  EXPECT_NEAR(9.0, accum.ComputeVariance(), 1.0);
58  EXPECT_EQ(2, accum.ComputeMin());
59  EXPECT_EQ(11, accum.ComputeMax());
60}
61
62TEST(RollingAccumulatorTest, ResetSamples) {
63  RollingAccumulator<int> accum(10);
64
65  for (int i = 0; i < 10; ++i) {
66    accum.AddSample(100);
67  }
68  EXPECT_EQ(10U, accum.count());
69  EXPECT_DOUBLE_EQ(100.0, accum.ComputeMean());
70  EXPECT_EQ(100, accum.ComputeMin());
71  EXPECT_EQ(100, accum.ComputeMax());
72
73  accum.Reset();
74  EXPECT_EQ(0U, accum.count());
75
76  for (int i = 0; i < 5; ++i) {
77    accum.AddSample(i);
78  }
79
80  EXPECT_EQ(5U, accum.count());
81  EXPECT_EQ(10, accum.ComputeSum());
82  EXPECT_DOUBLE_EQ(2.0, accum.ComputeMean());
83  EXPECT_EQ(0, accum.ComputeMin());
84  EXPECT_EQ(4, accum.ComputeMax());
85}
86
87TEST(RollingAccumulatorTest, RollingSamplesDouble) {
88  RollingAccumulator<double> accum(10);
89  for (int i = 0; i < 23; ++i) {
90    accum.AddSample(5 * i);
91  }
92
93  EXPECT_EQ(10u, accum.count());
94  EXPECT_DOUBLE_EQ(875.0, accum.ComputeSum());
95  EXPECT_DOUBLE_EQ(87.5, accum.ComputeMean());
96  EXPECT_NEAR(105.049, accum.ComputeWeightedMean(kLearningRate), 0.1);
97  EXPECT_NEAR(229.166667, accum.ComputeVariance(), 25);
98  EXPECT_DOUBLE_EQ(65.0, accum.ComputeMin());
99  EXPECT_DOUBLE_EQ(110.0, accum.ComputeMax());
100}
101
102TEST(RollingAccumulatorTest, ComputeWeightedMeanCornerCases) {
103  RollingAccumulator<int> accum(10);
104  EXPECT_DOUBLE_EQ(0.0, accum.ComputeWeightedMean(kLearningRate));
105  EXPECT_DOUBLE_EQ(0.0, accum.ComputeWeightedMean(0.0));
106  EXPECT_DOUBLE_EQ(0.0, accum.ComputeWeightedMean(1.1));
107
108  for (int i = 0; i < 8; ++i) {
109    accum.AddSample(i);
110  }
111
112  EXPECT_DOUBLE_EQ(3.5, accum.ComputeMean());
113  EXPECT_DOUBLE_EQ(3.5, accum.ComputeWeightedMean(0));
114  EXPECT_DOUBLE_EQ(3.5, accum.ComputeWeightedMean(1.1));
115  EXPECT_NEAR(6.0, accum.ComputeWeightedMean(kLearningRate), 0.1);
116}
117
118}  // namespace rtc
119