1 files changed, 67 insertions, 15 deletions

diff --git a/chromium/third_party/libjingle/source/talk/base/rollingaccumulator.h b/chromium/third_party/libjingle/source/talk/base/rollingaccumulator.h
index cdad0251f3f..dfda8fec072 100644
--- a/chromium/third_party/libjingle/source/talk/base/rollingaccumulator.h
+++ b/chromium/third_party/libjingle/source/talk/base/rollingaccumulator.h
@@ -42,11 +42,8 @@ template<typename T>
 class RollingAccumulator {
  public:
   explicit RollingAccumulator(size_t max_count)
-    : count_(0),
-      next_index_(0),
-      sum_(0.0),
-      sum_2_(0.0),
-      samples_(max_count) {
+    : samples_(max_count) {
+    Reset();
   }
   ~RollingAccumulator() {
   }
@@ -59,12 +56,29 @@ class RollingAccumulator {
     return count_;
   }
 
+  void Reset() {
+    count_ = 0U;
+    next_index_ = 0U;
+    sum_ = 0.0;
+    sum_2_ = 0.0;
+    max_ = T();
+    max_stale_ = false;
+    min_ = T();
+    min_stale_ = false;
+  }
+
   void AddSample(T sample) {
     if (count_ == max_count()) {
       // Remove oldest sample.
       T sample_to_remove = samples_[next_index_];
       sum_ -= sample_to_remove;
       sum_2_ -= sample_to_remove * sample_to_remove;
+      if (sample_to_remove >= max_) {
+        max_stale_ = true;
+      }
+      if (sample_to_remove <= min_) {
+        min_stale_ = true;
+      }
     } else {
       // Increase count of samples.
       ++count_;
@@ -73,6 +87,14 @@ class RollingAccumulator {
     samples_[next_index_] = sample;
     sum_ += sample;
     sum_2_ += sample * sample;
+    if (count_ == 1 || sample >= max_) {
+      max_ = sample;
+      max_stale_ = false;
+    }
+    if (count_ == 1 || sample <= min_) {
+      min_ = sample;
+      min_stale_ = false;
+    }
     // Update next_index_.
     next_index_ = (next_index_ + 1) % max_count();
   }
@@ -81,17 +103,43 @@ class RollingAccumulator {
     return static_cast<T>(sum_);
   }
 
-  T ComputeMean() const {
+  double ComputeMean() const {
     if (count_ == 0) {
-      return static_cast<T>(0);
+      return 0.0;
+    }
+    return sum_ / count_;
+  }
+
+  T ComputeMax() const {
+    if (max_stale_) {
+      ASSERT(count_ > 0 &&
+          "It shouldn't be possible for max_stale_ && count_ == 0");
+      max_ = samples_[next_index_];
+      for (size_t i = 1u; i < count_; i++) {
+        max_ = _max(max_, samples_[(next_index_ + i) % max_count()]);
+      }
+      max_stale_ = false;
+    }
+    return max_;
+  }
+
+  T ComputeMin() const {
+    if (min_stale_) {
+      ASSERT(count_ > 0 &&
+          "It shouldn't be possible for min_stale_ && count_ == 0");
+      min_ = samples_[next_index_];
+      for (size_t i = 1u; i < count_; i++) {
+        min_ = _min(min_, samples_[(next_index_ + i) % max_count()]);
+      }
+      min_stale_ = false;
     }
-    return static_cast<T>(sum_ / count_);
+    return min_;
   }
 
   // O(n) time complexity.
   // Weights nth sample with weight (learning_rate)^n. Learning_rate should be
   // between (0.0, 1.0], otherwise the non-weighted mean is returned.
-  T ComputeWeightedMean(double learning_rate) const {
+  double ComputeWeightedMean(double learning_rate) const {
     if (count_ < 1 || learning_rate <= 0.0 || learning_rate >= 1.0) {
       return ComputeMean();
     }
@@ -106,27 +154,31 @@ class RollingAccumulator {
       size_t index = (next_index_ + max_size - i - 1) % max_size;
       weighted_mean += current_weight * samples_[index];
     }
-    return static_cast<T>(weighted_mean / weight_sum);
+    return weighted_mean / weight_sum;
   }
 
   // Compute estimated variance.  Estimation is more accurate
   // as the number of samples grows.
-  T ComputeVariance() const {
+  double ComputeVariance() const {
     if (count_ == 0) {
-      return static_cast<T>(0);
+      return 0.0;
     }
     // Var = E[x^2] - (E[x])^2
     double count_inv = 1.0 / count_;
     double mean_2 = sum_2_ * count_inv;
     double mean = sum_ * count_inv;
-    return static_cast<T>(mean_2 - (mean * mean));
+    return mean_2 - (mean * mean);
   }
 
  private:
   size_t count_;
   size_t next_index_;
-  double sum_;    // Sum(x)
-  double sum_2_;  // Sum(x*x)
+  double sum_;    // Sum(x) - double to avoid overflow
+  double sum_2_;  // Sum(x*x) - double to avoid overflow
+  mutable T max_;
+  mutable bool max_stale_;
+  mutable T min_;
+  mutable bool min_stale_;
   std::vector<T> samples_;
 
   DISALLOW_COPY_AND_ASSIGN(RollingAccumulator);