1 /* 2 * Copyright (C) 2013 The Android Open Source Project 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 17 #ifndef ART_RUNTIME_BASE_HISTOGRAM_INL_H_ 18 #define ART_RUNTIME_BASE_HISTOGRAM_INL_H_ 19 20 #include <algorithm> 21 #include <cmath> 22 #include <limits> 23 #include <ostream> 24 25 #include "histogram.h" 26 27 #include "base/bit_utils.h" 28 #include "base/time_utils.h" 29 30 namespace art { 31 32 template <class Value> inline void Histogram<Value>::AddValue(Value value) { 33 CHECK_GE(value, static_cast<Value>(0)); 34 if (value >= max_) { 35 Value new_max = ((value + 1) / bucket_width_ + 1) * bucket_width_; 36 DCHECK_GT(new_max, max_); 37 GrowBuckets(new_max); 38 } 39 BucketiseValue(value); 40 } 41 42 template <class Value> inline void Histogram<Value>::AdjustAndAddValue(Value value) { 43 AddValue(value / kAdjust); 44 } 45 46 template <class Value> inline Histogram<Value>::Histogram(const char* name) 47 : kAdjust(0), 48 kInitialBucketCount(0), 49 name_(name), 50 max_buckets_(0) { 51 } 52 53 template <class Value> 54 inline Histogram<Value>::Histogram(const char* name, Value initial_bucket_width, 55 size_t max_buckets) 56 : kAdjust(1000), 57 kInitialBucketCount(8), 58 name_(name), 59 max_buckets_(max_buckets), 60 bucket_width_(initial_bucket_width) { 61 Reset(); 62 } 63 64 template <class Value> 65 inline void Histogram<Value>::GrowBuckets(Value new_max) { 66 while (max_ < new_max) { 67 // If we have reached the maximum number of buckets, merge buckets together. 68 if (frequency_.size() >= max_buckets_) { 69 CHECK(IsAligned<2>(frequency_.size())); 70 // We double the width of each bucket to reduce the number of buckets by a factor of 2. 71 bucket_width_ *= 2; 72 const size_t limit = frequency_.size() / 2; 73 // Merge the frequencies by adding each adjacent two together. 74 for (size_t i = 0; i < limit; ++i) { 75 frequency_[i] = frequency_[i * 2] + frequency_[i * 2 + 1]; 76 } 77 // Remove frequencies in the second half of the array which were added to the first half. 78 while (frequency_.size() > limit) { 79 frequency_.pop_back(); 80 } 81 } 82 max_ += bucket_width_; 83 frequency_.push_back(0); 84 } 85 } 86 87 template <class Value> inline size_t Histogram<Value>::FindBucket(Value val) const { 88 // Since this is only a linear histogram, bucket index can be found simply with 89 // dividing the value by the bucket width. 90 DCHECK_GE(val, min_); 91 DCHECK_LE(val, max_); 92 const size_t bucket_idx = static_cast<size_t>((val - min_) / bucket_width_); 93 DCHECK_GE(bucket_idx, 0ul); 94 DCHECK_LE(bucket_idx, GetBucketCount()); 95 return bucket_idx; 96 } 97 98 template <class Value> 99 inline void Histogram<Value>::BucketiseValue(Value val) { 100 CHECK_LT(val, max_); 101 sum_ += val; 102 sum_of_squares_ += val * val; 103 ++sample_size_; 104 ++frequency_[FindBucket(val)]; 105 max_value_added_ = std::max(val, max_value_added_); 106 min_value_added_ = std::min(val, min_value_added_); 107 } 108 109 template <class Value> inline void Histogram<Value>::Initialize() { 110 for (size_t idx = 0; idx < kInitialBucketCount; idx++) { 111 frequency_.push_back(0); 112 } 113 // Cumulative frequency and ranges has a length of 1 over frequency. 114 max_ = bucket_width_ * GetBucketCount(); 115 } 116 117 template <class Value> inline size_t Histogram<Value>::GetBucketCount() const { 118 return frequency_.size(); 119 } 120 121 template <class Value> inline void Histogram<Value>::Reset() { 122 sum_of_squares_ = 0; 123 sample_size_ = 0; 124 min_ = 0; 125 sum_ = 0; 126 min_value_added_ = std::numeric_limits<Value>::max(); 127 max_value_added_ = std::numeric_limits<Value>::min(); 128 frequency_.clear(); 129 Initialize(); 130 } 131 132 template <class Value> inline Value Histogram<Value>::GetRange(size_t bucket_idx) const { 133 DCHECK_LE(bucket_idx, GetBucketCount()); 134 return min_ + bucket_idx * bucket_width_; 135 } 136 137 template <class Value> inline double Histogram<Value>::Mean() const { 138 DCHECK_GT(sample_size_, 0ull); 139 return static_cast<double>(sum_) / static_cast<double>(sample_size_); 140 } 141 142 template <class Value> inline double Histogram<Value>::Variance() const { 143 DCHECK_GT(sample_size_, 0ull); 144 // Using algorithms for calculating variance over a population: 145 // http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance 146 Value sum_squared = sum_ * sum_; 147 double sum_squared_by_n_squared = 148 static_cast<double>(sum_squared) / 149 static_cast<double>(sample_size_ * sample_size_); 150 double sum_of_squares_by_n = 151 static_cast<double>(sum_of_squares_) / static_cast<double>(sample_size_); 152 return sum_of_squares_by_n - sum_squared_by_n_squared; 153 } 154 155 template <class Value> 156 inline void Histogram<Value>::PrintBins(std::ostream& os, const CumulativeData& data) const { 157 DCHECK_GT(sample_size_, 0ull); 158 for (size_t bin_idx = 0; bin_idx < data.freq_.size(); ++bin_idx) { 159 if (bin_idx > 0 && data.perc_[bin_idx] == data.perc_[bin_idx - 1]) { 160 bin_idx++; 161 continue; 162 } 163 os << GetRange(bin_idx) << ": " << data.freq_[bin_idx] << "\t" 164 << data.perc_[bin_idx] * 100.0 << "%\n"; 165 } 166 } 167 168 template <class Value> 169 inline void Histogram<Value>::DumpBins(std::ostream& os) const { 170 DCHECK_GT(sample_size_, 0ull); 171 bool dumped_one = false; 172 for (size_t bin_idx = 0; bin_idx < frequency_.size(); ++bin_idx) { 173 if (frequency_[bin_idx] != 0U) { 174 if (dumped_one) { 175 // Prepend a comma if not the first bin. 176 os << ","; 177 } else { 178 dumped_one = true; 179 } 180 os << GetRange(bin_idx) << ":" << frequency_[bin_idx]; 181 } 182 } 183 } 184 185 template <class Value> 186 inline void Histogram<Value>::PrintConfidenceIntervals(std::ostream &os, double interval, 187 const CumulativeData& data) const { 188 static constexpr size_t kFractionalDigits = 3; 189 DCHECK_GT(interval, 0); 190 DCHECK_LT(interval, 1.0); 191 const double per_0 = (1.0 - interval) / 2.0; 192 const double per_1 = per_0 + interval; 193 const TimeUnit unit = GetAppropriateTimeUnit(Mean() * kAdjust); 194 os << Name() << ":\tSum: " << PrettyDuration(Sum() * kAdjust) << " " 195 << (interval * 100) << "% C.I. " << FormatDuration(Percentile(per_0, data) * kAdjust, unit, 196 kFractionalDigits) 197 << "-" << FormatDuration(Percentile(per_1, data) * kAdjust, unit, kFractionalDigits) << " " 198 << "Avg: " << FormatDuration(Mean() * kAdjust, unit, kFractionalDigits) << " Max: " 199 << FormatDuration(Max() * kAdjust, unit, kFractionalDigits) << "\n"; 200 } 201 202 template <class Value> 203 inline void Histogram<Value>::CreateHistogram(CumulativeData* out_data) const { 204 DCHECK_GT(sample_size_, 0ull); 205 out_data->freq_.clear(); 206 out_data->perc_.clear(); 207 uint64_t accumulated = 0; 208 out_data->freq_.push_back(accumulated); 209 out_data->perc_.push_back(0.0); 210 for (size_t idx = 0; idx < frequency_.size(); idx++) { 211 accumulated += frequency_[idx]; 212 out_data->freq_.push_back(accumulated); 213 out_data->perc_.push_back(static_cast<double>(accumulated) / static_cast<double>(sample_size_)); 214 } 215 DCHECK_EQ(out_data->freq_.back(), sample_size_); 216 DCHECK_LE(std::abs(out_data->perc_.back() - 1.0), 0.001); 217 } 218 219 #if defined(__clang__) 220 #pragma clang diagnostic push 221 #pragma clang diagnostic ignored "-Wfloat-equal" 222 #endif 223 224 template <class Value> 225 inline double Histogram<Value>::Percentile(double per, const CumulativeData& data) const { 226 DCHECK_GT(data.perc_.size(), 0ull); 227 size_t upper_idx = 0, lower_idx = 0; 228 for (size_t idx = 0; idx < data.perc_.size(); idx++) { 229 if (per <= data.perc_[idx]) { 230 upper_idx = idx; 231 break; 232 } 233 234 if (per >= data.perc_[idx] && idx != 0 && data.perc_[idx] != data.perc_[idx - 1]) { 235 lower_idx = idx; 236 } 237 } 238 239 const double lower_perc = data.perc_[lower_idx]; 240 const double lower_value = static_cast<double>(GetRange(lower_idx)); 241 if (per == lower_perc) { 242 return lower_value; 243 } 244 245 const double upper_perc = data.perc_[upper_idx]; 246 const double upper_value = static_cast<double>(GetRange(upper_idx)); 247 if (per == upper_perc) { 248 return upper_value; 249 } 250 DCHECK_GT(upper_perc, lower_perc); 251 252 double value = lower_value + (upper_value - lower_value) * 253 (per - lower_perc) / (upper_perc - lower_perc); 254 255 if (value < min_value_added_) { 256 value = min_value_added_; 257 } else if (value > max_value_added_) { 258 value = max_value_added_; 259 } 260 261 return value; 262 } 263 264 #if defined(__clang__) 265 #pragma clang diagnostic pop 266 #endif 267 268 } // namespace art 269 #endif // ART_RUNTIME_BASE_HISTOGRAM_INL_H_ 270
