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
14 namespace rtc {
15
16 namespace {
17
18 const double kLearningRate = 0.5;
19
20 } // namespace
21
TEST(RollingAccumulatorTest,ZeroSamples)22 TEST(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
TEST(RollingAccumulatorTest,SomeSamples)32 TEST(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
TEST(RollingAccumulatorTest,RollingSamples)47 TEST(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
TEST(RollingAccumulatorTest,ResetSamples)62 TEST(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
TEST(RollingAccumulatorTest,RollingSamplesDouble)87 TEST(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
TEST(RollingAccumulatorTest,ComputeWeightedMeanCornerCases)102 TEST(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