1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
|
/*
* Copyright (c) 2016 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 "rtc_base/numerics/running_statistics.h"
#include <math.h>
#include <random>
#include <vector>
#include "absl/algorithm/container.h"
#include "test/gtest.h"
// Tests were copied from samples_stats_counter_unittest.cc.
namespace webrtc {
namespace webrtc_impl {
namespace {
RunningStatistics<double> CreateStatsFilledWithIntsFrom1ToN(int n) {
std::vector<double> data;
for (int i = 1; i <= n; i++) {
data.push_back(i);
}
absl::c_shuffle(data, std::mt19937(std::random_device()()));
RunningStatistics<double> stats;
for (double v : data) {
stats.AddSample(v);
}
return stats;
}
// Add n samples drawn from uniform distribution in [a;b].
RunningStatistics<double> CreateStatsFromUniformDistribution(int n,
double a,
double b) {
std::mt19937 gen{std::random_device()()};
std::uniform_real_distribution<> dis(a, b);
RunningStatistics<double> stats;
for (int i = 1; i <= n; i++) {
stats.AddSample(dis(gen));
}
return stats;
}
class RunningStatisticsTest : public ::testing::TestWithParam<int> {};
constexpr int SIZE_FOR_MERGE = 5;
TEST(RunningStatistics, FullSimpleTest) {
auto stats = CreateStatsFilledWithIntsFrom1ToN(100);
EXPECT_DOUBLE_EQ(*stats.GetMin(), 1.0);
EXPECT_DOUBLE_EQ(*stats.GetMax(), 100.0);
EXPECT_DOUBLE_EQ(*stats.GetSum(), 5050.0);
// EXPECT_DOUBLE_EQ is too strict (max 4 ULP) for this one.
ASSERT_NEAR(*stats.GetMean(), 50.5, 1e-10);
}
TEST(RunningStatistics, VarianceAndDeviation) {
RunningStatistics<int> stats;
stats.AddSample(2);
stats.AddSample(2);
stats.AddSample(-1);
stats.AddSample(5);
EXPECT_DOUBLE_EQ(*stats.GetMean(), 2.0);
EXPECT_DOUBLE_EQ(*stats.GetVariance(), 4.5);
EXPECT_DOUBLE_EQ(*stats.GetStandardDeviation(), sqrt(4.5));
}
TEST(RunningStatistics, RemoveSample) {
// We check that adding then removing sample is no-op,
// or so (due to loss of precision).
RunningStatistics<int> stats;
stats.AddSample(2);
stats.AddSample(2);
stats.AddSample(-1);
stats.AddSample(5);
constexpr int iterations = 1e5;
for (int i = 0; i < iterations; ++i) {
stats.AddSample(i);
stats.RemoveSample(i);
EXPECT_NEAR(*stats.GetMean(), 2.0, 1e-8);
EXPECT_NEAR(*stats.GetVariance(), 4.5, 1e-3);
EXPECT_NEAR(*stats.GetStandardDeviation(), sqrt(4.5), 1e-4);
}
}
TEST(RunningStatistics, RemoveSamplesSequence) {
// We check that adding then removing a sequence of samples is no-op,
// or so (due to loss of precision).
RunningStatistics<int> stats;
stats.AddSample(2);
stats.AddSample(2);
stats.AddSample(-1);
stats.AddSample(5);
constexpr int iterations = 1e4;
for (int i = 0; i < iterations; ++i) {
stats.AddSample(i);
}
for (int i = 0; i < iterations; ++i) {
stats.RemoveSample(i);
}
EXPECT_NEAR(*stats.GetMean(), 2.0, 1e-7);
EXPECT_NEAR(*stats.GetVariance(), 4.5, 1e-3);
EXPECT_NEAR(*stats.GetStandardDeviation(), sqrt(4.5), 1e-4);
}
TEST(RunningStatistics, VarianceFromUniformDistribution) {
// Check variance converge to 1/12 for [0;1) uniform distribution.
// Acts as a sanity check for NumericStabilityForVariance test.
auto stats = CreateStatsFromUniformDistribution(1e6, 0, 1);
EXPECT_NEAR(*stats.GetVariance(), 1. / 12, 1e-3);
}
TEST(RunningStatistics, NumericStabilityForVariance) {
// Same test as VarianceFromUniformDistribution,
// except the range is shifted to [1e9;1e9+1).
// Variance should also converge to 1/12.
// NB: Although we lose precision for the samples themselves, the fractional
// part still enjoys 22 bits of mantissa and errors should even out,
// so that couldn't explain a mismatch.
auto stats = CreateStatsFromUniformDistribution(1e6, 1e9, 1e9 + 1);
EXPECT_NEAR(*stats.GetVariance(), 1. / 12, 1e-3);
}
TEST(RunningStatistics, MinRemainsUnchangedAfterRemove) {
// We don't want to recompute min (that's RollingAccumulator's role),
// check we get the overall min.
RunningStatistics<int> stats;
stats.AddSample(1);
stats.AddSample(2);
stats.RemoveSample(1);
EXPECT_EQ(stats.GetMin(), 1);
}
TEST(RunningStatistics, MaxRemainsUnchangedAfterRemove) {
// We don't want to recompute max (that's RollingAccumulator's role),
// check we get the overall max.
RunningStatistics<int> stats;
stats.AddSample(1);
stats.AddSample(2);
stats.RemoveSample(2);
EXPECT_EQ(stats.GetMax(), 2);
}
TEST_P(RunningStatisticsTest, MergeStatistics) {
int data[SIZE_FOR_MERGE] = {2, 2, -1, 5, 10};
// Split the data in different partitions.
// We have 6 distinct tests:
// * Empty merged with full sequence.
// * 1 sample merged with 4 last.
// * 2 samples merged with 3 last.
// [...]
// * Full merged with empty sequence.
// All must lead to the same result.
// I miss QuickCheck so much.
RunningStatistics<int> stats0, stats1;
for (int i = 0; i < GetParam(); ++i) {
stats0.AddSample(data[i]);
}
for (int i = GetParam(); i < SIZE_FOR_MERGE; ++i) {
stats1.AddSample(data[i]);
}
stats0.MergeStatistics(stats1);
EXPECT_EQ(stats0.Size(), SIZE_FOR_MERGE);
EXPECT_DOUBLE_EQ(*stats0.GetMin(), -1);
EXPECT_DOUBLE_EQ(*stats0.GetMax(), 10);
EXPECT_DOUBLE_EQ(*stats0.GetMean(), 3.6);
EXPECT_DOUBLE_EQ(*stats0.GetVariance(), 13.84);
EXPECT_DOUBLE_EQ(*stats0.GetStandardDeviation(), sqrt(13.84));
}
INSTANTIATE_TEST_SUITE_P(RunningStatisticsTests,
RunningStatisticsTest,
::testing::Range(0, SIZE_FOR_MERGE + 1));
} // namespace
} // namespace webrtc_impl
} // namespace webrtc
|
