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/*
* 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 "api/numerics/samples_stats_counter.h"
#include <math.h>
#include <random>
#include <vector>
#include "absl/algorithm/container.h"
#include "test/gtest.h"
namespace webrtc {
namespace {
SamplesStatsCounter 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()()));
SamplesStatsCounter stats;
for (double v : data) {
stats.AddSample(v);
}
return stats;
}
// Add n samples drawn from uniform distribution in [a;b].
SamplesStatsCounter CreateStatsFromUniformDistribution(int n,
double a,
double b) {
std::mt19937 gen{std::random_device()()};
std::uniform_real_distribution<> dis(a, b);
SamplesStatsCounter stats;
for (int i = 1; i <= n; i++) {
stats.AddSample(dis(gen));
}
return stats;
}
class SamplesStatsCounterTest : public ::testing::TestWithParam<int> {};
constexpr int SIZE_FOR_MERGE = 10;
} // namespace
TEST(SamplesStatsCounterTest, FullSimpleTest) {
SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(100);
EXPECT_TRUE(!stats.IsEmpty());
EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
EXPECT_DOUBLE_EQ(stats.GetMax(), 100.0);
EXPECT_NEAR(stats.GetAverage(), 50.5, 1e-6);
for (int i = 1; i <= 100; i++) {
double p = i / 100.0;
EXPECT_GE(stats.GetPercentile(p), i);
EXPECT_LT(stats.GetPercentile(p), i + 1);
}
}
TEST(SamplesStatsCounterTest, VarianceAndDeviation) {
SamplesStatsCounter stats;
stats.AddSample(2);
stats.AddSample(2);
stats.AddSample(-1);
stats.AddSample(5);
EXPECT_DOUBLE_EQ(stats.GetAverage(), 2.0);
EXPECT_DOUBLE_EQ(stats.GetVariance(), 4.5);
EXPECT_DOUBLE_EQ(stats.GetStandardDeviation(), sqrt(4.5));
}
TEST(SamplesStatsCounterTest, FractionPercentile) {
SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(5);
EXPECT_DOUBLE_EQ(stats.GetPercentile(0.5), 3);
}
TEST(SamplesStatsCounterTest, TestBorderValues) {
SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(5);
EXPECT_GE(stats.GetPercentile(0.01), 1);
EXPECT_LT(stats.GetPercentile(0.01), 2);
EXPECT_DOUBLE_EQ(stats.GetPercentile(1.0), 5);
}
TEST(SamplesStatsCounterTest, VarianceFromUniformDistribution) {
// Check variance converge to 1/12 for [0;1) uniform distribution.
// Acts as a sanity check for NumericStabilityForVariance test.
SamplesStatsCounter stats = CreateStatsFromUniformDistribution(1e6, 0, 1);
EXPECT_NEAR(stats.GetVariance(), 1. / 12, 1e-3);
}
TEST(SamplesStatsCounterTest, 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.
SamplesStatsCounter stats =
CreateStatsFromUniformDistribution(1e6, 1e9, 1e9 + 1);
EXPECT_NEAR(stats.GetVariance(), 1. / 12, 1e-3);
}
TEST_P(SamplesStatsCounterTest, AddSamples) {
int data[SIZE_FOR_MERGE] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
// Split the data in different partitions.
// We have 11 distinct tests:
// * Empty merged with full sequence.
// * 1 sample merged with 9 last.
// * 2 samples merged with 8 last.
// [...]
// * Full merged with empty sequence.
// All must lead to the same result.
SamplesStatsCounter 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.AddSamples(stats1);
EXPECT_EQ(stats0.GetMin(), 0);
EXPECT_EQ(stats0.GetMax(), 9);
EXPECT_DOUBLE_EQ(stats0.GetAverage(), 4.5);
EXPECT_DOUBLE_EQ(stats0.GetVariance(), 8.25);
EXPECT_DOUBLE_EQ(stats0.GetStandardDeviation(), sqrt(8.25));
EXPECT_DOUBLE_EQ(stats0.GetPercentile(0.1), 0.9);
EXPECT_DOUBLE_EQ(stats0.GetPercentile(0.5), 4.5);
EXPECT_DOUBLE_EQ(stats0.GetPercentile(0.9), 8.1);
}
TEST(SamplesStatsCounterTest, MultiplyRight) {
SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(10);
EXPECT_TRUE(!stats.IsEmpty());
EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
EXPECT_DOUBLE_EQ(stats.GetMax(), 10.0);
EXPECT_DOUBLE_EQ(stats.GetAverage(), 5.5);
SamplesStatsCounter multiplied_stats = stats * 10;
EXPECT_TRUE(!multiplied_stats.IsEmpty());
EXPECT_DOUBLE_EQ(multiplied_stats.GetMin(), 10.0);
EXPECT_DOUBLE_EQ(multiplied_stats.GetMax(), 100.0);
EXPECT_DOUBLE_EQ(multiplied_stats.GetAverage(), 55.0);
EXPECT_EQ(multiplied_stats.GetSamples().size(), stats.GetSamples().size());
// Check that origin stats were not modified.
EXPECT_TRUE(!stats.IsEmpty());
EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
EXPECT_DOUBLE_EQ(stats.GetMax(), 10.0);
EXPECT_DOUBLE_EQ(stats.GetAverage(), 5.5);
}
TEST(SamplesStatsCounterTest, MultiplyLeft) {
SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(10);
EXPECT_TRUE(!stats.IsEmpty());
EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
EXPECT_DOUBLE_EQ(stats.GetMax(), 10.0);
EXPECT_DOUBLE_EQ(stats.GetAverage(), 5.5);
SamplesStatsCounter multiplied_stats = 10 * stats;
EXPECT_TRUE(!multiplied_stats.IsEmpty());
EXPECT_DOUBLE_EQ(multiplied_stats.GetMin(), 10.0);
EXPECT_DOUBLE_EQ(multiplied_stats.GetMax(), 100.0);
EXPECT_DOUBLE_EQ(multiplied_stats.GetAverage(), 55.0);
EXPECT_EQ(multiplied_stats.GetSamples().size(), stats.GetSamples().size());
// Check that origin stats were not modified.
EXPECT_TRUE(!stats.IsEmpty());
EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
EXPECT_DOUBLE_EQ(stats.GetMax(), 10.0);
EXPECT_DOUBLE_EQ(stats.GetAverage(), 5.5);
}
TEST(SamplesStatsCounterTest, Divide) {
SamplesStatsCounter stats;
for (int i = 1; i <= 10; i++) {
stats.AddSample(i * 10);
}
EXPECT_TRUE(!stats.IsEmpty());
EXPECT_DOUBLE_EQ(stats.GetMin(), 10.0);
EXPECT_DOUBLE_EQ(stats.GetMax(), 100.0);
EXPECT_DOUBLE_EQ(stats.GetAverage(), 55.0);
SamplesStatsCounter divided_stats = stats / 10;
EXPECT_TRUE(!divided_stats.IsEmpty());
EXPECT_DOUBLE_EQ(divided_stats.GetMin(), 1.0);
EXPECT_DOUBLE_EQ(divided_stats.GetMax(), 10.0);
EXPECT_DOUBLE_EQ(divided_stats.GetAverage(), 5.5);
EXPECT_EQ(divided_stats.GetSamples().size(), stats.GetSamples().size());
// Check that origin stats were not modified.
EXPECT_TRUE(!stats.IsEmpty());
EXPECT_DOUBLE_EQ(stats.GetMin(), 10.0);
EXPECT_DOUBLE_EQ(stats.GetMax(), 100.0);
EXPECT_DOUBLE_EQ(stats.GetAverage(), 55.0);
}
INSTANTIATE_TEST_SUITE_P(SamplesStatsCounterTests,
SamplesStatsCounterTest,
::testing::Range(0, SIZE_FOR_MERGE + 1));
} // namespace webrtc
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