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 #include "utils.h"
30
31 namespace art {
32
AddValue(Value value)33 template <class Value> inline void Histogram<Value>::AddValue(Value value) {
34 CHECK_GE(value, static_cast<Value>(0));
35 if (value >= max_) {
36 Value new_max = ((value + 1) / bucket_width_ + 1) * bucket_width_;
37 DCHECK_GT(new_max, max_);
38 GrowBuckets(new_max);
39 }
40 BucketiseValue(value);
41 }
42
AdjustAndAddValue(Value value)43 template <class Value> inline void Histogram<Value>::AdjustAndAddValue(Value value) {
44 AddValue(value / kAdjust);
45 }
46
Histogram(const char * name)47 template <class Value> inline Histogram<Value>::Histogram(const char* name)
48 : kAdjust(0),
49 kInitialBucketCount(0),
50 name_(name),
51 max_buckets_(0) {
52 }
53
54 template <class Value>
Histogram(const char * name,Value initial_bucket_width,size_t max_buckets)55 inline Histogram<Value>::Histogram(const char* name, Value initial_bucket_width,
56 size_t max_buckets)
57 : kAdjust(1000),
58 kInitialBucketCount(8),
59 name_(name),
60 max_buckets_(max_buckets),
61 bucket_width_(initial_bucket_width) {
62 Reset();
63 }
64
65 template <class Value>
GrowBuckets(Value new_max)66 inline void Histogram<Value>::GrowBuckets(Value new_max) {
67 while (max_ < new_max) {
68 // If we have reached the maximum number of buckets, merge buckets together.
69 if (frequency_.size() >= max_buckets_) {
70 CHECK_ALIGNED(frequency_.size(), 2);
71 // We double the width of each bucket to reduce the number of buckets by a factor of 2.
72 bucket_width_ *= 2;
73 const size_t limit = frequency_.size() / 2;
74 // Merge the frequencies by adding each adjacent two together.
75 for (size_t i = 0; i < limit; ++i) {
76 frequency_[i] = frequency_[i * 2] + frequency_[i * 2 + 1];
77 }
78 // Remove frequencies in the second half of the array which were added to the first half.
79 while (frequency_.size() > limit) {
80 frequency_.pop_back();
81 }
82 }
83 max_ += bucket_width_;
84 frequency_.push_back(0);
85 }
86 }
87
FindBucket(Value val)88 template <class Value> inline size_t Histogram<Value>::FindBucket(Value val) const {
89 // Since this is only a linear histogram, bucket index can be found simply with
90 // dividing the value by the bucket width.
91 DCHECK_GE(val, min_);
92 DCHECK_LE(val, max_);
93 const size_t bucket_idx = static_cast<size_t>((val - min_) / bucket_width_);
94 DCHECK_GE(bucket_idx, 0ul);
95 DCHECK_LE(bucket_idx, GetBucketCount());
96 return bucket_idx;
97 }
98
99 template <class Value>
BucketiseValue(Value val)100 inline void Histogram<Value>::BucketiseValue(Value val) {
101 CHECK_LT(val, max_);
102 sum_ += val;
103 sum_of_squares_ += val * val;
104 ++sample_size_;
105 ++frequency_[FindBucket(val)];
106 max_value_added_ = std::max(val, max_value_added_);
107 min_value_added_ = std::min(val, min_value_added_);
108 }
109
Initialize()110 template <class Value> inline void Histogram<Value>::Initialize() {
111 for (size_t idx = 0; idx < kInitialBucketCount; idx++) {
112 frequency_.push_back(0);
113 }
114 // Cumulative frequency and ranges has a length of 1 over frequency.
115 max_ = bucket_width_ * GetBucketCount();
116 }
117
GetBucketCount()118 template <class Value> inline size_t Histogram<Value>::GetBucketCount() const {
119 return frequency_.size();
120 }
121
Reset()122 template <class Value> inline void Histogram<Value>::Reset() {
123 sum_of_squares_ = 0;
124 sample_size_ = 0;
125 min_ = 0;
126 sum_ = 0;
127 min_value_added_ = std::numeric_limits<Value>::max();
128 max_value_added_ = std::numeric_limits<Value>::min();
129 frequency_.clear();
130 Initialize();
131 }
132
GetRange(size_t bucket_idx)133 template <class Value> inline Value Histogram<Value>::GetRange(size_t bucket_idx) const {
134 DCHECK_LE(bucket_idx, GetBucketCount());
135 return min_ + bucket_idx * bucket_width_;
136 }
137
Mean()138 template <class Value> inline double Histogram<Value>::Mean() const {
139 DCHECK_GT(sample_size_, 0ull);
140 return static_cast<double>(sum_) / static_cast<double>(sample_size_);
141 }
142
Variance()143 template <class Value> inline double Histogram<Value>::Variance() const {
144 DCHECK_GT(sample_size_, 0ull);
145 // Using algorithms for calculating variance over a population:
146 // http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance
147 Value sum_squared = sum_ * sum_;
148 double sum_squared_by_n_squared =
149 static_cast<double>(sum_squared) /
150 static_cast<double>(sample_size_ * sample_size_);
151 double sum_of_squares_by_n =
152 static_cast<double>(sum_of_squares_) / static_cast<double>(sample_size_);
153 return sum_of_squares_by_n - sum_squared_by_n_squared;
154 }
155
156 template <class Value>
PrintBins(std::ostream & os,const CumulativeData & data)157 inline void Histogram<Value>::PrintBins(std::ostream& os, const CumulativeData& data) const {
158 DCHECK_GT(sample_size_, 0ull);
159 for (size_t bin_idx = 0; bin_idx < data.freq_.size(); ++bin_idx) {
160 if (bin_idx > 0 && data.perc_[bin_idx] == data.perc_[bin_idx - 1]) {
161 bin_idx++;
162 continue;
163 }
164 os << GetRange(bin_idx) << ": " << data.freq_[bin_idx] << "\t"
165 << data.perc_[bin_idx] * 100.0 << "%\n";
166 }
167 }
168
169 template <class Value>
DumpBins(std::ostream & os)170 inline void Histogram<Value>::DumpBins(std::ostream& os) const {
171 DCHECK_GT(sample_size_, 0ull);
172 bool dumped_one = false;
173 for (size_t bin_idx = 0; bin_idx < frequency_.size(); ++bin_idx) {
174 if (frequency_[bin_idx] != 0U) {
175 if (dumped_one) {
176 // Prepend a comma if not the first bin.
177 os << ",";
178 } else {
179 dumped_one = true;
180 }
181 os << GetRange(bin_idx) << ":" << frequency_[bin_idx];
182 }
183 }
184 }
185
186 template <class Value>
PrintConfidenceIntervals(std::ostream & os,double interval,const CumulativeData & data)187 inline void Histogram<Value>::PrintConfidenceIntervals(std::ostream &os, double interval,
188 const CumulativeData& data) const {
189 static constexpr size_t kFractionalDigits = 3;
190 DCHECK_GT(interval, 0);
191 DCHECK_LT(interval, 1.0);
192 const double per_0 = (1.0 - interval) / 2.0;
193 const double per_1 = per_0 + interval;
194 const TimeUnit unit = GetAppropriateTimeUnit(Mean() * kAdjust);
195 os << Name() << ":\tSum: " << PrettyDuration(Sum() * kAdjust) << " "
196 << (interval * 100) << "% C.I. " << FormatDuration(Percentile(per_0, data) * kAdjust, unit,
197 kFractionalDigits)
198 << "-" << FormatDuration(Percentile(per_1, data) * kAdjust, unit, kFractionalDigits) << " "
199 << "Avg: " << FormatDuration(Mean() * kAdjust, unit, kFractionalDigits) << " Max: "
200 << FormatDuration(Max() * kAdjust, unit, kFractionalDigits) << "\n";
201 }
202
203 template <class Value>
PrintMemoryUse(std::ostream & os)204 inline void Histogram<Value>::PrintMemoryUse(std::ostream &os) const {
205 os << Name()
206 << ": Avg: " << PrettySize(Mean()) << " Max: "
207 << PrettySize(Max()) << " Min: " << PrettySize(Min()) << "\n";
208 }
209
210 template <class Value>
CreateHistogram(CumulativeData * out_data)211 inline void Histogram<Value>::CreateHistogram(CumulativeData* out_data) const {
212 DCHECK_GT(sample_size_, 0ull);
213 out_data->freq_.clear();
214 out_data->perc_.clear();
215 uint64_t accumulated = 0;
216 out_data->freq_.push_back(accumulated);
217 out_data->perc_.push_back(0.0);
218 for (size_t idx = 0; idx < frequency_.size(); idx++) {
219 accumulated += frequency_[idx];
220 out_data->freq_.push_back(accumulated);
221 out_data->perc_.push_back(static_cast<double>(accumulated) / static_cast<double>(sample_size_));
222 }
223 DCHECK_EQ(out_data->freq_.back(), sample_size_);
224 DCHECK_LE(std::abs(out_data->perc_.back() - 1.0), 0.001);
225 }
226
227 #if defined(__clang__)
228 #pragma clang diagnostic push
229 #pragma clang diagnostic ignored "-Wfloat-equal"
230 #endif
231
232 template <class Value>
Percentile(double per,const CumulativeData & data)233 inline double Histogram<Value>::Percentile(double per, const CumulativeData& data) const {
234 DCHECK_GT(data.perc_.size(), 0ull);
235 size_t upper_idx = 0, lower_idx = 0;
236 for (size_t idx = 0; idx < data.perc_.size(); idx++) {
237 if (per <= data.perc_[idx]) {
238 upper_idx = idx;
239 break;
240 }
241
242 if (per >= data.perc_[idx] && idx != 0 && data.perc_[idx] != data.perc_[idx - 1]) {
243 lower_idx = idx;
244 }
245 }
246
247 const double lower_perc = data.perc_[lower_idx];
248 const double lower_value = static_cast<double>(GetRange(lower_idx));
249 if (per == lower_perc) {
250 return lower_value;
251 }
252
253 const double upper_perc = data.perc_[upper_idx];
254 const double upper_value = static_cast<double>(GetRange(upper_idx));
255 if (per == upper_perc) {
256 return upper_value;
257 }
258 DCHECK_GT(upper_perc, lower_perc);
259
260 double value = lower_value + (upper_value - lower_value) *
261 (per - lower_perc) / (upper_perc - lower_perc);
262
263 if (value < min_value_added_) {
264 value = min_value_added_;
265 } else if (value > max_value_added_) {
266 value = max_value_added_;
267 }
268
269 return value;
270 }
271
272 #if defined(__clang__)
273 #pragma clang diagnostic pop
274 #endif
275
276 } // namespace art
277 #endif // ART_RUNTIME_BASE_HISTOGRAM_INL_H_
278