| /* |
| * Copyright (C) 2013 The Android Open Source Project |
| * |
| * Licensed under the Apache License, Version 2.0 (the "License"); |
| * you may not use this file except in compliance with the License. |
| * You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| #ifndef ART_RUNTIME_BASE_HISTOGRAM_INL_H_ |
| #define ART_RUNTIME_BASE_HISTOGRAM_INL_H_ |
| |
| #include "histogram.h" |
| |
| #include "utils.h" |
| |
| #include <algorithm> |
| #include <cmath> |
| #include <limits> |
| #include <ostream> |
| |
| namespace art { |
| |
| template <class Value> inline void Histogram<Value>::AddValue(Value value) { |
| CHECK_GE(value, static_cast<Value>(0)); |
| if (value >= max_) { |
| Value new_max = ((value + 1) / bucket_width_ + 1) * bucket_width_; |
| DCHECK_GT(new_max, max_); |
| GrowBuckets(new_max); |
| } |
| BucketiseValue(value); |
| } |
| |
| template <class Value> inline void Histogram<Value>::AdjustAndAddValue(Value value) { |
| AddValue(value / kAdjust); |
| } |
| |
| template <class Value> inline Histogram<Value>::Histogram(const char* name) |
| : kAdjust(0), |
| kInitialBucketCount(0), |
| name_(name), |
| max_buckets_(0) { |
| } |
| |
| template <class Value> |
| inline Histogram<Value>::Histogram(const char* name, Value initial_bucket_width, |
| size_t max_buckets) |
| : kAdjust(1000), |
| kInitialBucketCount(8), |
| name_(name), |
| max_buckets_(max_buckets), |
| bucket_width_(initial_bucket_width) { |
| Reset(); |
| } |
| |
| template <class Value> |
| inline void Histogram<Value>::GrowBuckets(Value new_max) { |
| while (max_ < new_max) { |
| // If we have reached the maximum number of buckets, merge buckets together. |
| if (frequency_.size() >= max_buckets_) { |
| CHECK(IsAligned<2>(frequency_.size())); |
| // We double the width of each bucket to reduce the number of buckets by a factor of 2. |
| bucket_width_ *= 2; |
| const size_t limit = frequency_.size() / 2; |
| // Merge the frequencies by adding each adjacent two together. |
| for (size_t i = 0; i < limit; ++i) { |
| frequency_[i] = frequency_[i * 2] + frequency_[i * 2 + 1]; |
| } |
| // Remove frequencies in the second half of the array which were added to the first half. |
| while (frequency_.size() > limit) { |
| frequency_.pop_back(); |
| } |
| } |
| max_ += bucket_width_; |
| frequency_.push_back(0); |
| } |
| } |
| |
| template <class Value> inline size_t Histogram<Value>::FindBucket(Value val) const { |
| // Since this is only a linear histogram, bucket index can be found simply with |
| // dividing the value by the bucket width. |
| DCHECK_GE(val, min_); |
| DCHECK_LE(val, max_); |
| const size_t bucket_idx = static_cast<size_t>((val - min_) / bucket_width_); |
| DCHECK_GE(bucket_idx, 0ul); |
| DCHECK_LE(bucket_idx, GetBucketCount()); |
| return bucket_idx; |
| } |
| |
| template <class Value> |
| inline void Histogram<Value>::BucketiseValue(Value val) { |
| CHECK_LT(val, max_); |
| sum_ += val; |
| sum_of_squares_ += val * val; |
| ++sample_size_; |
| ++frequency_[FindBucket(val)]; |
| max_value_added_ = std::max(val, max_value_added_); |
| min_value_added_ = std::min(val, min_value_added_); |
| } |
| |
| template <class Value> inline void Histogram<Value>::Initialize() { |
| for (size_t idx = 0; idx < kInitialBucketCount; idx++) { |
| frequency_.push_back(0); |
| } |
| // Cumulative frequency and ranges has a length of 1 over frequency. |
| max_ = bucket_width_ * GetBucketCount(); |
| } |
| |
| template <class Value> inline size_t Histogram<Value>::GetBucketCount() const { |
| return frequency_.size(); |
| } |
| |
| template <class Value> inline void Histogram<Value>::Reset() { |
| sum_of_squares_ = 0; |
| sample_size_ = 0; |
| min_ = 0; |
| sum_ = 0; |
| min_value_added_ = std::numeric_limits<Value>::max(); |
| max_value_added_ = std::numeric_limits<Value>::min(); |
| frequency_.clear(); |
| Initialize(); |
| } |
| |
| template <class Value> inline Value Histogram<Value>::GetRange(size_t bucket_idx) const { |
| DCHECK_LE(bucket_idx, GetBucketCount()); |
| return min_ + bucket_idx * bucket_width_; |
| } |
| |
| template <class Value> inline double Histogram<Value>::Mean() const { |
| DCHECK_GT(sample_size_, 0ull); |
| return static_cast<double>(sum_) / static_cast<double>(sample_size_); |
| } |
| |
| template <class Value> inline double Histogram<Value>::Variance() const { |
| DCHECK_GT(sample_size_, 0ull); |
| // Using algorithms for calculating variance over a population: |
| // http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance |
| Value sum_squared = sum_ * sum_; |
| double sum_squared_by_n_squared = |
| static_cast<double>(sum_squared) / |
| static_cast<double>(sample_size_ * sample_size_); |
| double sum_of_squares_by_n = |
| static_cast<double>(sum_of_squares_) / static_cast<double>(sample_size_); |
| return sum_of_squares_by_n - sum_squared_by_n_squared; |
| } |
| |
| template <class Value> |
| inline void Histogram<Value>::PrintBins(std::ostream& os, const CumulativeData& data) const { |
| DCHECK_GT(sample_size_, 0ull); |
| for (size_t bin_idx = 0; bin_idx < data.freq_.size(); ++bin_idx) { |
| if (bin_idx > 0 && data.perc_[bin_idx] == data.perc_[bin_idx - 1]) { |
| bin_idx++; |
| continue; |
| } |
| os << GetRange(bin_idx) << ": " << data.freq_[bin_idx] << "\t" |
| << data.perc_[bin_idx] * 100.0 << "%\n"; |
| } |
| } |
| |
| template <class Value> |
| inline void Histogram<Value>::PrintConfidenceIntervals(std::ostream &os, double interval, |
| const CumulativeData& data) const { |
| static constexpr size_t kFractionalDigits = 3; |
| DCHECK_GT(interval, 0); |
| DCHECK_LT(interval, 1.0); |
| const double per_0 = (1.0 - interval) / 2.0; |
| const double per_1 = per_0 + interval; |
| const TimeUnit unit = GetAppropriateTimeUnit(Mean() * kAdjust); |
| os << Name() << ":\tSum: " << PrettyDuration(Sum() * kAdjust) << " " |
| << (interval * 100) << "% C.I. " << FormatDuration(Percentile(per_0, data) * kAdjust, unit, |
| kFractionalDigits) |
| << "-" << FormatDuration(Percentile(per_1, data) * kAdjust, unit, kFractionalDigits) << " " |
| << "Avg: " << FormatDuration(Mean() * kAdjust, unit, kFractionalDigits) << " Max: " |
| << FormatDuration(Max() * kAdjust, unit, kFractionalDigits) << "\n"; |
| } |
| |
| template <class Value> |
| inline void Histogram<Value>::CreateHistogram(CumulativeData* out_data) const { |
| DCHECK_GT(sample_size_, 0ull); |
| out_data->freq_.clear(); |
| out_data->perc_.clear(); |
| uint64_t accumulated = 0; |
| out_data->freq_.push_back(accumulated); |
| out_data->perc_.push_back(0.0); |
| for (size_t idx = 0; idx < frequency_.size(); idx++) { |
| accumulated += frequency_[idx]; |
| out_data->freq_.push_back(accumulated); |
| out_data->perc_.push_back(static_cast<double>(accumulated) / static_cast<double>(sample_size_)); |
| } |
| DCHECK_EQ(out_data->freq_.back(), sample_size_); |
| DCHECK_LE(std::abs(out_data->perc_.back() - 1.0), 0.001); |
| } |
| |
| #if defined(__clang__) |
| #pragma clang diagnostic push |
| #pragma clang diagnostic ignored "-Wfloat-equal" |
| #endif |
| |
| template <class Value> |
| inline double Histogram<Value>::Percentile(double per, const CumulativeData& data) const { |
| DCHECK_GT(data.perc_.size(), 0ull); |
| size_t upper_idx = 0, lower_idx = 0; |
| for (size_t idx = 0; idx < data.perc_.size(); idx++) { |
| if (per <= data.perc_[idx]) { |
| upper_idx = idx; |
| break; |
| } |
| |
| if (per >= data.perc_[idx] && idx != 0 && data.perc_[idx] != data.perc_[idx - 1]) { |
| lower_idx = idx; |
| } |
| } |
| |
| const double lower_perc = data.perc_[lower_idx]; |
| const double lower_value = static_cast<double>(GetRange(lower_idx)); |
| if (per == lower_perc) { |
| return lower_value; |
| } |
| |
| const double upper_perc = data.perc_[upper_idx]; |
| const double upper_value = static_cast<double>(GetRange(upper_idx)); |
| if (per == upper_perc) { |
| return upper_value; |
| } |
| DCHECK_GT(upper_perc, lower_perc); |
| |
| double value = lower_value + (upper_value - lower_value) * |
| (per - lower_perc) / (upper_perc - lower_perc); |
| |
| if (value < min_value_added_) { |
| value = min_value_added_; |
| } else if (value > max_value_added_) { |
| value = max_value_added_; |
| } |
| |
| return value; |
| } |
| |
| #if defined(__clang__) |
| #pragma clang diagnostic pop |
| #endif |
| |
| } // namespace art |
| #endif // ART_RUNTIME_BASE_HISTOGRAM_INL_H_ |
| |