src/third_party/webrtc/base/rollingaccumulator_unittest.cc

   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