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:
41
api/numerics/BUILD.gn
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41
api/numerics/BUILD.gn
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# Copyright (c) 2020 The WebRTC project authors. All Rights Reserved.
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#
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# Use of this source code is governed by a BSD-style license
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# that can be found in the LICENSE file in the root of the source
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# tree. An additional intellectual property rights grant can be found
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# in the file PATENTS. All contributing project authors may
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# be found in the AUTHORS file in the root of the source tree.
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import("../../webrtc.gni")
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rtc_library("numerics") {
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visibility = [ "*" ]
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sources = [
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"samples_stats_counter.cc",
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"samples_stats_counter.h",
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]
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deps = [
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"..:array_view",
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"../../rtc_base:checks",
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"../../rtc_base:rtc_numerics",
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"../../rtc_base:timeutils",
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"../units:timestamp",
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]
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absl_deps = [ "//third_party/abseil-cpp/absl/algorithm:container" ]
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}
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if (rtc_include_tests) {
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rtc_library("numerics_unittests") {
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visibility = [ "*" ]
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testonly = true
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sources = [ "samples_stats_counter_unittest.cc" ]
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deps = [
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":numerics",
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"../../test:test_support",
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]
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absl_deps = [ "//third_party/abseil-cpp/absl/algorithm:container" ]
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}
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}
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6
api/numerics/DEPS
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6
api/numerics/DEPS
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@ -0,0 +1,6 @@
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specific_include_rules = {
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# Some internal headers are allowed even in API headers:
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"samples_stats_counter\.h": [
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"+rtc_base/numerics/running_statistics.h",
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]
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}
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97
api/numerics/samples_stats_counter.cc
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97
api/numerics/samples_stats_counter.cc
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@ -0,0 +1,97 @@
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/*
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* Copyright (c) 2018 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include "api/numerics/samples_stats_counter.h"
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#include <algorithm>
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#include <cmath>
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#include "absl/algorithm/container.h"
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#include "rtc_base/time_utils.h"
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namespace webrtc {
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SamplesStatsCounter::SamplesStatsCounter() = default;
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SamplesStatsCounter::~SamplesStatsCounter() = default;
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SamplesStatsCounter::SamplesStatsCounter(const SamplesStatsCounter&) = default;
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SamplesStatsCounter& SamplesStatsCounter::operator=(
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const SamplesStatsCounter&) = default;
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SamplesStatsCounter::SamplesStatsCounter(SamplesStatsCounter&&) = default;
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SamplesStatsCounter& SamplesStatsCounter::operator=(SamplesStatsCounter&&) =
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default;
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void SamplesStatsCounter::AddSample(double value) {
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AddSample(StatsSample{value, Timestamp::Micros(rtc::TimeMicros())});
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}
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void SamplesStatsCounter::AddSample(StatsSample sample) {
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stats_.AddSample(sample.value);
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samples_.push_back(sample);
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sorted_ = false;
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}
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void SamplesStatsCounter::AddSamples(const SamplesStatsCounter& other) {
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stats_.MergeStatistics(other.stats_);
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samples_.insert(samples_.end(), other.samples_.begin(), other.samples_.end());
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sorted_ = false;
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}
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double SamplesStatsCounter::GetPercentile(double percentile) {
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RTC_DCHECK(!IsEmpty());
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RTC_CHECK_GE(percentile, 0);
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RTC_CHECK_LE(percentile, 1);
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if (!sorted_) {
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absl::c_sort(samples_, [](const StatsSample& a, const StatsSample& b) {
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return a.value < b.value;
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});
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sorted_ = true;
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}
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const double raw_rank = percentile * (samples_.size() - 1);
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double int_part;
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double fract_part = std::modf(raw_rank, &int_part);
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size_t rank = static_cast<size_t>(int_part);
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if (fract_part >= 1.0) {
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// It can happen due to floating point calculation error.
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rank++;
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fract_part -= 1.0;
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}
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RTC_DCHECK_GE(rank, 0);
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RTC_DCHECK_LT(rank, samples_.size());
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RTC_DCHECK_GE(fract_part, 0);
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RTC_DCHECK_LT(fract_part, 1);
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RTC_DCHECK(rank + fract_part == raw_rank);
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const double low = samples_[rank].value;
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const double high = samples_[std::min(rank + 1, samples_.size() - 1)].value;
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return low + fract_part * (high - low);
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}
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SamplesStatsCounter operator*(const SamplesStatsCounter& counter,
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double value) {
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SamplesStatsCounter out;
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for (const auto& sample : counter.GetTimedSamples()) {
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out.AddSample(
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SamplesStatsCounter::StatsSample{sample.value * value, sample.time});
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}
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return out;
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}
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SamplesStatsCounter operator/(const SamplesStatsCounter& counter,
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double value) {
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SamplesStatsCounter out;
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for (const auto& sample : counter.GetTimedSamples()) {
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out.AddSample(
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SamplesStatsCounter::StatsSample{sample.value / value, sample.time});
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}
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return out;
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}
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} // namespace webrtc
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119
api/numerics/samples_stats_counter.h
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119
api/numerics/samples_stats_counter.h
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@ -0,0 +1,119 @@
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/*
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* Copyright (c) 2018 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#ifndef API_NUMERICS_SAMPLES_STATS_COUNTER_H_
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#define API_NUMERICS_SAMPLES_STATS_COUNTER_H_
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#include <vector>
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#include "api/array_view.h"
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#include "api/units/timestamp.h"
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#include "rtc_base/checks.h"
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#include "rtc_base/numerics/running_statistics.h"
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namespace webrtc {
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// This class extends RunningStatistics by providing GetPercentile() method,
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// while slightly adapting the interface.
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class SamplesStatsCounter {
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public:
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struct StatsSample {
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double value;
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Timestamp time;
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};
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SamplesStatsCounter();
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~SamplesStatsCounter();
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SamplesStatsCounter(const SamplesStatsCounter&);
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SamplesStatsCounter& operator=(const SamplesStatsCounter&);
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SamplesStatsCounter(SamplesStatsCounter&&);
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SamplesStatsCounter& operator=(SamplesStatsCounter&&);
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// Adds sample to the stats in amortized O(1) time.
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void AddSample(double value);
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void AddSample(StatsSample sample);
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// Adds samples from another counter.
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void AddSamples(const SamplesStatsCounter& other);
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// Returns if there are any values in O(1) time.
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bool IsEmpty() const { return samples_.empty(); }
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// Returns min in O(1) time. This function may not be called if there are no
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// samples.
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double GetMin() const {
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RTC_DCHECK(!IsEmpty());
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return *stats_.GetMin();
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}
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// Returns max in O(1) time. This function may not be called if there are no
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// samples.
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double GetMax() const {
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RTC_DCHECK(!IsEmpty());
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return *stats_.GetMax();
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}
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// Returns average in O(1) time. This function may not be called if there are
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// no samples.
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double GetAverage() const {
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RTC_DCHECK(!IsEmpty());
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return *stats_.GetMean();
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}
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// Returns variance in O(1) time. This function may not be called if there are
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// no samples.
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double GetVariance() const {
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RTC_DCHECK(!IsEmpty());
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return *stats_.GetVariance();
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}
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// Returns standard deviation in O(1) time. This function may not be called if
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// there are no samples.
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double GetStandardDeviation() const {
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RTC_DCHECK(!IsEmpty());
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return *stats_.GetStandardDeviation();
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}
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// Returns percentile in O(nlogn) on first call and in O(1) after, if no
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// additions were done. This function may not be called if there are no
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// samples.
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//
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// |percentile| has to be in [0; 1]. 0 percentile is the min in the array and
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// 1 percentile is the max in the array.
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double GetPercentile(double percentile);
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// Returns array view with all samples added into counter. There are no
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// guarantees of order, so samples can be in different order comparing to in
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// which they were added into counter. Also return value will be invalidate
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// after call to any non const method.
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rtc::ArrayView<const StatsSample> GetTimedSamples() const { return samples_; }
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std::vector<double> GetSamples() const {
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std::vector<double> out;
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out.reserve(samples_.size());
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for (const auto& sample : samples_) {
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out.push_back(sample.value);
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}
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return out;
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}
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private:
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webrtc_impl::RunningStatistics<double> stats_;
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std::vector<StatsSample> samples_;
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bool sorted_ = false;
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};
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// Multiply all sample values on |value| and return new SamplesStatsCounter
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// with resulted samples. Doesn't change origin SamplesStatsCounter.
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SamplesStatsCounter operator*(const SamplesStatsCounter& counter, double value);
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inline SamplesStatsCounter operator*(double value,
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const SamplesStatsCounter& counter) {
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return counter * value;
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}
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// Divide all sample values on |value| and return new SamplesStatsCounter with
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// resulted samples. Doesn't change origin SamplesStatsCounter.
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SamplesStatsCounter operator/(const SamplesStatsCounter& counter, double value);
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} // namespace webrtc
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#endif // API_NUMERICS_SAMPLES_STATS_COUNTER_H_
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221
api/numerics/samples_stats_counter_unittest.cc
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221
api/numerics/samples_stats_counter_unittest.cc
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/*
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* Copyright (c) 2016 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include "api/numerics/samples_stats_counter.h"
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#include <math.h>
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#include <random>
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#include <vector>
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#include "absl/algorithm/container.h"
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#include "test/gtest.h"
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namespace webrtc {
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namespace {
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SamplesStatsCounter CreateStatsFilledWithIntsFrom1ToN(int n) {
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std::vector<double> data;
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for (int i = 1; i <= n; i++) {
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data.push_back(i);
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}
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absl::c_shuffle(data, std::mt19937(std::random_device()()));
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SamplesStatsCounter stats;
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for (double v : data) {
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stats.AddSample(v);
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}
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return stats;
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}
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// Add n samples drawn from uniform distribution in [a;b].
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SamplesStatsCounter CreateStatsFromUniformDistribution(int n,
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double a,
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double b) {
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std::mt19937 gen{std::random_device()()};
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std::uniform_real_distribution<> dis(a, b);
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SamplesStatsCounter stats;
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for (int i = 1; i <= n; i++) {
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stats.AddSample(dis(gen));
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}
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return stats;
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}
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class SamplesStatsCounterTest : public ::testing::TestWithParam<int> {};
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constexpr int SIZE_FOR_MERGE = 10;
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} // namespace
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TEST(SamplesStatsCounterTest, FullSimpleTest) {
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SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(100);
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EXPECT_TRUE(!stats.IsEmpty());
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EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
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EXPECT_DOUBLE_EQ(stats.GetMax(), 100.0);
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EXPECT_NEAR(stats.GetAverage(), 50.5, 1e-6);
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for (int i = 1; i <= 100; i++) {
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double p = i / 100.0;
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EXPECT_GE(stats.GetPercentile(p), i);
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EXPECT_LT(stats.GetPercentile(p), i + 1);
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}
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}
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TEST(SamplesStatsCounterTest, VarianceAndDeviation) {
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SamplesStatsCounter stats;
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stats.AddSample(2);
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stats.AddSample(2);
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stats.AddSample(-1);
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stats.AddSample(5);
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EXPECT_DOUBLE_EQ(stats.GetAverage(), 2.0);
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EXPECT_DOUBLE_EQ(stats.GetVariance(), 4.5);
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EXPECT_DOUBLE_EQ(stats.GetStandardDeviation(), sqrt(4.5));
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}
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TEST(SamplesStatsCounterTest, FractionPercentile) {
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SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(5);
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EXPECT_DOUBLE_EQ(stats.GetPercentile(0.5), 3);
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}
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TEST(SamplesStatsCounterTest, TestBorderValues) {
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SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(5);
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EXPECT_GE(stats.GetPercentile(0.01), 1);
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EXPECT_LT(stats.GetPercentile(0.01), 2);
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EXPECT_DOUBLE_EQ(stats.GetPercentile(1.0), 5);
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}
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TEST(SamplesStatsCounterTest, VarianceFromUniformDistribution) {
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// Check variance converge to 1/12 for [0;1) uniform distribution.
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// Acts as a sanity check for NumericStabilityForVariance test.
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SamplesStatsCounter stats = CreateStatsFromUniformDistribution(1e6, 0, 1);
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EXPECT_NEAR(stats.GetVariance(), 1. / 12, 1e-3);
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}
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TEST(SamplesStatsCounterTest, NumericStabilityForVariance) {
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// Same test as VarianceFromUniformDistribution,
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// except the range is shifted to [1e9;1e9+1).
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// Variance should also converge to 1/12.
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// NB: Although we lose precision for the samples themselves, the fractional
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// part still enjoys 22 bits of mantissa and errors should even out,
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// so that couldn't explain a mismatch.
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SamplesStatsCounter stats =
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CreateStatsFromUniformDistribution(1e6, 1e9, 1e9 + 1);
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EXPECT_NEAR(stats.GetVariance(), 1. / 12, 1e-3);
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}
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TEST_P(SamplesStatsCounterTest, AddSamples) {
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int data[SIZE_FOR_MERGE] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
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// Split the data in different partitions.
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// We have 11 distinct tests:
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// * Empty merged with full sequence.
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// * 1 sample merged with 9 last.
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// * 2 samples merged with 8 last.
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// [...]
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// * Full merged with empty sequence.
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// All must lead to the same result.
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SamplesStatsCounter stats0, stats1;
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for (int i = 0; i < GetParam(); ++i) {
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stats0.AddSample(data[i]);
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}
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for (int i = GetParam(); i < SIZE_FOR_MERGE; ++i) {
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stats1.AddSample(data[i]);
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}
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stats0.AddSamples(stats1);
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EXPECT_EQ(stats0.GetMin(), 0);
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EXPECT_EQ(stats0.GetMax(), 9);
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EXPECT_DOUBLE_EQ(stats0.GetAverage(), 4.5);
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EXPECT_DOUBLE_EQ(stats0.GetVariance(), 8.25);
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EXPECT_DOUBLE_EQ(stats0.GetStandardDeviation(), sqrt(8.25));
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EXPECT_DOUBLE_EQ(stats0.GetPercentile(0.1), 0.9);
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EXPECT_DOUBLE_EQ(stats0.GetPercentile(0.5), 4.5);
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EXPECT_DOUBLE_EQ(stats0.GetPercentile(0.9), 8.1);
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}
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TEST(SamplesStatsCounterTest, MultiplyRight) {
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SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(10);
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EXPECT_TRUE(!stats.IsEmpty());
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EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
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EXPECT_DOUBLE_EQ(stats.GetMax(), 10.0);
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EXPECT_DOUBLE_EQ(stats.GetAverage(), 5.5);
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SamplesStatsCounter multiplied_stats = stats * 10;
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EXPECT_TRUE(!multiplied_stats.IsEmpty());
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EXPECT_DOUBLE_EQ(multiplied_stats.GetMin(), 10.0);
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EXPECT_DOUBLE_EQ(multiplied_stats.GetMax(), 100.0);
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EXPECT_DOUBLE_EQ(multiplied_stats.GetAverage(), 55.0);
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EXPECT_EQ(multiplied_stats.GetSamples().size(), stats.GetSamples().size());
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// Check that origin stats were not modified.
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EXPECT_TRUE(!stats.IsEmpty());
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EXPECT_DOUBLE_EQ(stats.GetMin(), 1.0);
|
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EXPECT_DOUBLE_EQ(stats.GetMax(), 10.0);
|
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EXPECT_DOUBLE_EQ(stats.GetAverage(), 5.5);
|
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}
|
||||
|
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TEST(SamplesStatsCounterTest, MultiplyLeft) {
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SamplesStatsCounter stats = CreateStatsFilledWithIntsFrom1ToN(10);
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||||
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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;
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||||
EXPECT_TRUE(!multiplied_stats.IsEmpty());
|
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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
|
Reference in New Issue
Block a user