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/*
* Copyright 2019 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/event_based_exponential_moving_average.h"
#include <cmath>
#include <cstdint>
#include <limits>
#include "rtc_base/checks.h"
namespace {
// For a normal distributed value, the 95% double sided confidence interval is
// is 1.96 * stddev.
constexpr double ninetyfive_percent_confidence = 1.96;
} // namespace
namespace rtc {
// `half_time` specifies how much weight will be given to old samples,
// a sample gets exponentially less weight so that it's 50%
// after `half_time` time units has passed.
EventBasedExponentialMovingAverage::EventBasedExponentialMovingAverage(
int half_time) {
SetHalfTime(half_time);
}
void EventBasedExponentialMovingAverage::SetHalfTime(int half_time) {
tau_ = static_cast<double>(half_time) / log(2);
Reset();
}
void EventBasedExponentialMovingAverage::Reset() {
value_ = std::nan("uninit");
sample_variance_ = std::numeric_limits<double>::infinity();
estimator_variance_ = 1;
last_observation_timestamp_.reset();
}
void EventBasedExponentialMovingAverage::AddSample(int64_t now, int sample) {
if (!last_observation_timestamp_.has_value()) {
value_ = sample;
} else {
// TODO(webrtc:11140): This should really be > (e.g not >=)
// but some pesky tests run with simulated clock and let
// samples arrive simultaneously!
RTC_DCHECK(now >= *last_observation_timestamp_);
// Variance gets computed after second sample.
int64_t age = now - *last_observation_timestamp_;
double e = exp(-age / tau_);
double alpha = e / (1 + e);
double one_minus_alpha = 1 - alpha;
double sample_diff = sample - value_;
value_ = one_minus_alpha * value_ + alpha * sample;
estimator_variance_ =
(one_minus_alpha * one_minus_alpha) * estimator_variance_ +
(alpha * alpha);
if (sample_variance_ == std::numeric_limits<double>::infinity()) {
// First variance.
sample_variance_ = sample_diff * sample_diff;
} else {
double new_variance = one_minus_alpha * sample_variance_ +
alpha * sample_diff * sample_diff;
sample_variance_ = new_variance;
}
}
last_observation_timestamp_ = now;
}
double EventBasedExponentialMovingAverage::GetConfidenceInterval() const {
return ninetyfive_percent_confidence *
sqrt(sample_variance_ * estimator_variance_);
}
} // namespace rtc