Move SampleStatsCounter to public API

Bug: None
Change-Id: I8956f6febbb1caf71e951d212d57746fe1ec5eb2
Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/184506
Commit-Queue: Artem Titov <titovartem@webrtc.org>
Reviewed-by: Karl Wiberg <kwiberg@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#32142}
This commit is contained in:
Artem Titov
2020-09-18 18:23:08 +02:00
committed by Commit Bot
parent 979c13f565
commit 9d77762023
25 changed files with 126 additions and 56 deletions

41
api/numerics/BUILD.gn Normal file
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# Copyright (c) 2020 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.
import("../../webrtc.gni")
rtc_library("numerics") {
visibility = [ "*" ]
sources = [
"samples_stats_counter.cc",
"samples_stats_counter.h",
]
deps = [
"..:array_view",
"../../rtc_base:checks",
"../../rtc_base:rtc_numerics",
"../../rtc_base:timeutils",
"../units:timestamp",
]
absl_deps = [ "//third_party/abseil-cpp/absl/algorithm:container" ]
}
if (rtc_include_tests) {
rtc_library("numerics_unittests") {
visibility = [ "*" ]
testonly = true
sources = [ "samples_stats_counter_unittest.cc" ]
deps = [
":numerics",
"../../test:test_support",
]
absl_deps = [ "//third_party/abseil-cpp/absl/algorithm:container" ]
}
}

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api/numerics/DEPS Normal file
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specific_include_rules = {
# Some internal headers are allowed even in API headers:
"samples_stats_counter\.h": [
"+rtc_base/numerics/running_statistics.h",
]
}

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/*
* Copyright (c) 2018 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 <algorithm>
#include <cmath>
#include "absl/algorithm/container.h"
#include "rtc_base/time_utils.h"
namespace webrtc {
SamplesStatsCounter::SamplesStatsCounter() = default;
SamplesStatsCounter::~SamplesStatsCounter() = default;
SamplesStatsCounter::SamplesStatsCounter(const SamplesStatsCounter&) = default;
SamplesStatsCounter& SamplesStatsCounter::operator=(
const SamplesStatsCounter&) = default;
SamplesStatsCounter::SamplesStatsCounter(SamplesStatsCounter&&) = default;
SamplesStatsCounter& SamplesStatsCounter::operator=(SamplesStatsCounter&&) =
default;
void SamplesStatsCounter::AddSample(double value) {
AddSample(StatsSample{value, Timestamp::Micros(rtc::TimeMicros())});
}
void SamplesStatsCounter::AddSample(StatsSample sample) {
stats_.AddSample(sample.value);
samples_.push_back(sample);
sorted_ = false;
}
void SamplesStatsCounter::AddSamples(const SamplesStatsCounter& other) {
stats_.MergeStatistics(other.stats_);
samples_.insert(samples_.end(), other.samples_.begin(), other.samples_.end());
sorted_ = false;
}
double SamplesStatsCounter::GetPercentile(double percentile) {
RTC_DCHECK(!IsEmpty());
RTC_CHECK_GE(percentile, 0);
RTC_CHECK_LE(percentile, 1);
if (!sorted_) {
absl::c_sort(samples_, [](const StatsSample& a, const StatsSample& b) {
return a.value < b.value;
});
sorted_ = true;
}
const double raw_rank = percentile * (samples_.size() - 1);
double int_part;
double fract_part = std::modf(raw_rank, &int_part);
size_t rank = static_cast<size_t>(int_part);
if (fract_part >= 1.0) {
// It can happen due to floating point calculation error.
rank++;
fract_part -= 1.0;
}
RTC_DCHECK_GE(rank, 0);
RTC_DCHECK_LT(rank, samples_.size());
RTC_DCHECK_GE(fract_part, 0);
RTC_DCHECK_LT(fract_part, 1);
RTC_DCHECK(rank + fract_part == raw_rank);
const double low = samples_[rank].value;
const double high = samples_[std::min(rank + 1, samples_.size() - 1)].value;
return low + fract_part * (high - low);
}
SamplesStatsCounter operator*(const SamplesStatsCounter& counter,
double value) {
SamplesStatsCounter out;
for (const auto& sample : counter.GetTimedSamples()) {
out.AddSample(
SamplesStatsCounter::StatsSample{sample.value * value, sample.time});
}
return out;
}
SamplesStatsCounter operator/(const SamplesStatsCounter& counter,
double value) {
SamplesStatsCounter out;
for (const auto& sample : counter.GetTimedSamples()) {
out.AddSample(
SamplesStatsCounter::StatsSample{sample.value / value, sample.time});
}
return out;
}
} // namespace webrtc

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/*
* Copyright (c) 2018 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.
*/
#ifndef API_NUMERICS_SAMPLES_STATS_COUNTER_H_
#define API_NUMERICS_SAMPLES_STATS_COUNTER_H_
#include <vector>
#include "api/array_view.h"
#include "api/units/timestamp.h"
#include "rtc_base/checks.h"
#include "rtc_base/numerics/running_statistics.h"
namespace webrtc {
// This class extends RunningStatistics by providing GetPercentile() method,
// while slightly adapting the interface.
class SamplesStatsCounter {
public:
struct StatsSample {
double value;
Timestamp time;
};
SamplesStatsCounter();
~SamplesStatsCounter();
SamplesStatsCounter(const SamplesStatsCounter&);
SamplesStatsCounter& operator=(const SamplesStatsCounter&);
SamplesStatsCounter(SamplesStatsCounter&&);
SamplesStatsCounter& operator=(SamplesStatsCounter&&);
// Adds sample to the stats in amortized O(1) time.
void AddSample(double value);
void AddSample(StatsSample sample);
// Adds samples from another counter.
void AddSamples(const SamplesStatsCounter& other);
// Returns if there are any values in O(1) time.
bool IsEmpty() const { return samples_.empty(); }
// Returns min in O(1) time. This function may not be called if there are no
// samples.
double GetMin() const {
RTC_DCHECK(!IsEmpty());
return *stats_.GetMin();
}
// Returns max in O(1) time. This function may not be called if there are no
// samples.
double GetMax() const {
RTC_DCHECK(!IsEmpty());
return *stats_.GetMax();
}
// Returns average in O(1) time. This function may not be called if there are
// no samples.
double GetAverage() const {
RTC_DCHECK(!IsEmpty());
return *stats_.GetMean();
}
// Returns variance in O(1) time. This function may not be called if there are
// no samples.
double GetVariance() const {
RTC_DCHECK(!IsEmpty());
return *stats_.GetVariance();
}
// Returns standard deviation in O(1) time. This function may not be called if
// there are no samples.
double GetStandardDeviation() const {
RTC_DCHECK(!IsEmpty());
return *stats_.GetStandardDeviation();
}
// Returns percentile in O(nlogn) on first call and in O(1) after, if no
// additions were done. This function may not be called if there are no
// samples.
//
// |percentile| has to be in [0; 1]. 0 percentile is the min in the array and
// 1 percentile is the max in the array.
double GetPercentile(double percentile);
// Returns array view with all samples added into counter. There are no
// guarantees of order, so samples can be in different order comparing to in
// which they were added into counter. Also return value will be invalidate
// after call to any non const method.
rtc::ArrayView<const StatsSample> GetTimedSamples() const { return samples_; }
std::vector<double> GetSamples() const {
std::vector<double> out;
out.reserve(samples_.size());
for (const auto& sample : samples_) {
out.push_back(sample.value);
}
return out;
}
private:
webrtc_impl::RunningStatistics<double> stats_;
std::vector<StatsSample> samples_;
bool sorted_ = false;
};
// Multiply all sample values on |value| and return new SamplesStatsCounter
// with resulted samples. Doesn't change origin SamplesStatsCounter.
SamplesStatsCounter operator*(const SamplesStatsCounter& counter, double value);
inline SamplesStatsCounter operator*(double value,
const SamplesStatsCounter& counter) {
return counter * value;
}
// Divide all sample values on |value| and return new SamplesStatsCounter with
// resulted samples. Doesn't change origin SamplesStatsCounter.
SamplesStatsCounter operator/(const SamplesStatsCounter& counter, double value);
} // namespace webrtc
#endif // API_NUMERICS_SAMPLES_STATS_COUNTER_H_

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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