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// Copyright 2018 The Chromium Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "ui/latency/stream_analyzer.h"
namespace ui {
namespace frame_metrics {
StreamAnalyzer::StreamAnalyzer(
const StreamAnalyzerClient* client,
const SharedWindowedAnalyzerClient* shared_client,
std::vector<uint32_t> thresholds,
std::unique_ptr<Histogram> histogram)
: client_(client),
histogram_(std::move(histogram)),
windowed_analyzer_(client, shared_client) {
thresholds_.reserve(thresholds.size());
for (const uint32_t& t : thresholds)
thresholds_.emplace_back(t);
}
StreamAnalyzer::~StreamAnalyzer() = default;
void StreamAnalyzer::Reset() {
StartNewReportPeriod();
windowed_analyzer_.ResetHistory();
}
void StreamAnalyzer::StartNewReportPeriod() {
histogram_->Reset();
windowed_analyzer_.ResetWorstValues();
for (auto& t : thresholds_)
t.ResetAccumulators();
total_weight_ = 0;
accumulator_ = 0;
root_accumulator_ = 0;
square_accumulator_ = Accumulator96b();
}
void StreamAnalyzer::AddSample(const uint32_t value, const uint32_t weight) {
DCHECK_GT(weight, 0u);
uint64_t weighted_value = static_cast<uint64_t>(weight) * value;
uint64_t weighted_root = weight * std::sqrt(static_cast<double>(value) *
kFixedPointRootMultiplier);
Accumulator96b weighted_square(value, weight);
// Verify overflow isn't an issue.
// square_accumulator_ has DCHECKs internally, so we don't worry about
// checking that here.
DCHECK_LT(weighted_value,
std::numeric_limits<decltype(accumulator_)>::max() - accumulator_);
DCHECK_LT(weighted_root,
std::numeric_limits<decltype(root_accumulator_)>::max() -
root_accumulator_);
DCHECK_LT(weight, std::numeric_limits<decltype(total_weight_)>::max() -
total_weight_);
histogram_->AddSample(value, weight);
windowed_analyzer_.AddSample(value, weight, weighted_value, weighted_root,
weighted_square);
for (auto& t : thresholds_) {
if (value >= t.threshold)
t.ge_weight += weight;
else
t.lt_weight += weight;
}
total_weight_ += weight;
accumulator_ += weighted_value;
root_accumulator_ += weighted_root;
square_accumulator_.Add(weighted_square);
}
double StreamAnalyzer::ComputeMean() const {
double result = static_cast<double>(accumulator_) / total_weight_;
return client_->TransformResult(result);
}
double StreamAnalyzer::ComputeRMS() const {
double mean_square = square_accumulator_.ToDouble() / total_weight_;
double result = std::sqrt(mean_square);
return client_->TransformResult(result);
}
double StreamAnalyzer::ComputeSMR() const {
double mean_root = static_cast<double>(root_accumulator_) / total_weight_;
double result = (mean_root * mean_root) / kFixedPointRootMultiplier;
return client_->TransformResult(result);
}
double StreamAnalyzer::VarianceHelper(double accum, double square_accum) const {
double mean = accum / total_weight_;
double mean_squared = mean * mean;
double mean_square = square_accum / total_weight_;
double variance = mean_square - mean_squared;
// This approach to calculating the standard deviation isn't numerically
// stable if the variance is very small relative to the mean, which might
// result in a negative variance. Clamp it to 0.
return std::max(0.0, variance);
}
double StreamAnalyzer::ComputeStdDev() const {
double variance =
VarianceHelper(accumulator_, square_accumulator_.ToDouble());
double std_dev = std::sqrt(variance);
return client_->TransformResult(std_dev);
}
double StreamAnalyzer::ComputeVarianceOfRoots() const {
double normalized_root =
static_cast<double>(root_accumulator_) / kFixedPointRootMultiplierSqrt;
double variance = VarianceHelper(normalized_root, accumulator_);
return client_->TransformResult(variance);
}
void StreamAnalyzer::ThresholdState::ResetAccumulators() {
ge_weight = 0;
lt_weight = 0;
}
std::vector<ThresholdResult> StreamAnalyzer::ComputeThresholds() const {
std::vector<ThresholdResult> results;
results.reserve(thresholds_.size());
for (const auto& t : thresholds_) {
double threshold = client_->TransformResult(t.threshold);
double ge_fraction =
static_cast<double>(t.ge_weight) / (t.ge_weight + t.lt_weight);
results.push_back({threshold, ge_fraction});
}
return results;
}
PercentileResults StreamAnalyzer::ComputePercentiles() const {
PercentileResults result;
result = histogram_->ComputePercentiles();
for (size_t i = 0; i < PercentileResults::kCount; i++) {
result.values[i] = client_->TransformResult(result.values[i]);
}
return result;
}
std::unique_ptr<base::trace_event::ConvertableToTraceFormat>
StreamAnalyzer::AsValue() const {
auto state = std::make_unique<base::trace_event::TracedValue>();
AsValueInto(state.get());
return std::move(state);
}
void StreamAnalyzer::AsValueInto(base::trace_event::TracedValue* state) const {
state->SetDouble("mean", ComputeMean());
state->SetDouble("rms", ComputeRMS());
state->SetDouble("smr", ComputeSMR());
state->SetDouble("std_dev", ComputeStdDev());
state->SetDouble("variance_of_roots", ComputeVarianceOfRoots());
state->BeginArray("percentiles");
PercentileResults result = ComputePercentiles();
for (size_t i = 0; i < PercentileResults::kCount; i++) {
state->BeginArray();
state->AppendDouble(PercentileResults::kPercentiles[i]);
state->AppendDouble(result.values[i]);
state->EndArray();
}
state->EndArray();
state->BeginArray("thresholds");
std::vector<ThresholdResult> thresholds(ComputeThresholds());
for (const auto& t : thresholds) {
state->BeginArray();
state->AppendDouble(t.threshold);
state->AppendDouble(t.ge_fraction);
state->EndArray();
}
state->EndArray();
windowed_analyzer_.AsValueInto(state);
}
} // namespace frame_metrics
} // namespace ui
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