Avoid precision loss in TrendlineEstimator from int64_t -> double conversion

webrtc/modules/congestion_controller/trendline_estimator.cc

Index: webrtc/modules/congestion_controller/trendline_estimator.cc
diff --git a/webrtc/modules/congestion_controller/trendline_estimator.cc b/webrtc/modules/congestion_controller/trendline_estimator.cc
index a086f6aaa1bae4055caddaa77fa3d48962f7bcdf..ad05a64e1e0262c480d202331d91f5a3cc0ba9d5 100644
--- a/webrtc/modules/congestion_controller/trendline_estimator.cc
+++ b/webrtc/modules/congestion_controller/trendline_estimator.cc
@@ -13,12 +13,14 @@
 #include <algorithm>
 
 #include "webrtc/base/checks.h"
+#include "webrtc/base/optional.h"
 #include "webrtc/modules/remote_bitrate_estimator/test/bwe_test_logging.h"
 
 namespace webrtc {
 
 namespace {
-double LinearFitSlope(const std::list<std::pair<double, double>> points) {
+rtc::Optional<double> LinearFitSlope(
+    const std::list<std::pair<double, double>> points) {
   RTC_DCHECK(points.size() >= 2);
   // Compute the "center of mass".
   double sum_x = 0;
@@ -36,7 +38,9 @@ double LinearFitSlope(const std::list<std::pair<double, double>> points) {
     numerator += (point.first - x_avg) * (point.second - y_avg);
     denominator += (point.first - x_avg) * (point.first - x_avg);
   }
-  return numerator / denominator;
+  if (denominator == 0)
+    return rtc::Optional<double>();
+  return rtc::Optional<double>(numerator / denominator);
 }
 }  // namespace
 
@@ -49,6 +53,7 @@ TrendlineEstimator::TrendlineEstimator(size_t window_size,
       smoothing_coef_(smoothing_coef),
       threshold_gain_(threshold_gain),
       num_of_deltas_(0),
+      first_arrival_time_ms(-1),
       accumulated_delay_(0),
       smoothed_delay_(0),
       delay_hist_(),
@@ -58,30 +63,35 @@ TrendlineEstimator::~TrendlineEstimator() {}
 
 void TrendlineEstimator::Update(double recv_delta_ms,
                                 double send_delta_ms,
-                                double now_ms) {
+                                int64_t arrival_time_ms) {
   const double delta_ms = recv_delta_ms - send_delta_ms;
   ++num_of_deltas_;
-  if (num_of_deltas_ > kDeltaCounterMax) {
+  if (num_of_deltas_ > kDeltaCounterMax)
     num_of_deltas_ = kDeltaCounterMax;
-  }
+  if (first_arrival_time_ms == -1)
+    first_arrival_time_ms = arrival_time_ms;
 
   // Exponential backoff filter.
   accumulated_delay_ += delta_ms;
-  BWE_TEST_LOGGING_PLOT(1, "accumulated_delay_ms", now_ms, accumulated_delay_);
+  BWE_TEST_LOGGING_PLOT(1, "accumulated_delay_ms", arrival_time_ms,
+                        accumulated_delay_);
   smoothed_delay_ = smoothing_coef_ * smoothed_delay_ +
                     (1 - smoothing_coef_) * accumulated_delay_;
-  BWE_TEST_LOGGING_PLOT(1, "smoothed_delay_ms", now_ms, smoothed_delay_);
+  BWE_TEST_LOGGING_PLOT(1, "smoothed_delay_ms", arrival_time_ms,
+                        smoothed_delay_);
 
   // Simple linear regression.
-  delay_hist_.push_back(std::make_pair(now_ms, smoothed_delay_));
-  if (delay_hist_.size() > window_size_) {
+  delay_hist_.push_back(std::make_pair(
+      static_cast<double>(arrival_time_ms - first_arrival_time_ms),
+      smoothed_delay_));
+  if (delay_hist_.size() > window_size_)
     delay_hist_.pop_front();
-  }
   if (delay_hist_.size() == window_size_) {
-    trendline_ = LinearFitSlope(delay_hist_);
+    // Only update trendline_ if it is possible to fit a line to the data.
+    trendline_ = LinearFitSlope(delay_hist_).value_or(trendline_);
   }
 
-  BWE_TEST_LOGGING_PLOT(1, "trendline_slope", now_ms, trendline_);
+  BWE_TEST_LOGGING_PLOT(1, "trendline_slope", arrival_time_ms, trendline_);
 }
 
 }  // namespace webrtc