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 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 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 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 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 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 } 101 102 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
