webrtc_m130/rtc_base/numerics/event_based_exponential_moving_average.cc
Jonas Oreland 63dced9f45 Add class for ExponentialMovingAverage
Bug: webrtc:11120
Change-Id: I210671e00276546e9d63b148385263cb1256e2b0
Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/160307
Reviewed-by: Harald Alvestrand <hta@webrtc.org>
Reviewed-by: Niels Moller <nisse@webrtc.org>
Commit-Queue: Jonas Oreland <jonaso@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#29901}
2019-11-25 13:17:59 +00:00

67 lines
2.2 KiB
C++

/*
* 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 "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)
: tau_(static_cast<double>(half_time) / log(2)) {}
void EventBasedExponentialMovingAverage::AddSample(int64_t now, int sample) {
if (!last_observation_timestamp_.has_value()) {
value_ = sample;
} else {
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