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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 "histogram.h"
21 
22 #include "utils.h"
23 
24 #include <algorithm>
25 #include <cmath>
26 #include <limits>
27 #include <ostream>
28 
29 namespace art {
30 
AddValue(Value value)31 template <class Value> inline void Histogram<Value>::AddValue(Value value) {
32   CHECK_GE(value, static_cast<Value>(0));
33   if (value >= max_) {
34     Value new_max = ((value + 1) / bucket_width_ + 1) * bucket_width_;
35     DCHECK_GT(new_max, max_);
36     GrowBuckets(new_max);
37   }
38 
39   BucketiseValue(value);
40 }
41 
42 template <class Value>
Histogram(const char * name,Value initial_bucket_width,size_t max_buckets)43 inline Histogram<Value>::Histogram(const char* name, Value initial_bucket_width,
44                                    size_t max_buckets)
45     : kAdjust(1000),
46       kInitialBucketCount(8),
47       name_(name),
48       max_buckets_(max_buckets),
49       bucket_width_(initial_bucket_width) {
50   Reset();
51 }
52 
53 template <class Value>
GrowBuckets(Value new_max)54 inline void Histogram<Value>::GrowBuckets(Value new_max) {
55   while (max_ < new_max) {
56     // If we have reached the maximum number of buckets, merge buckets together.
57     if (frequency_.size() >= max_buckets_) {
58       CHECK(IsAligned<2>(frequency_.size()));
59       // We double the width of each bucket to reduce the number of buckets by a factor of 2.
60       bucket_width_ *= 2;
61       const size_t limit = frequency_.size() / 2;
62       // Merge the frequencies by adding each adjacent two together.
63       for (size_t i = 0; i < limit; ++i) {
64         frequency_[i] = frequency_[i * 2] + frequency_[i * 2 + 1];
65       }
66       // Remove frequencies in the second half of the array which were added to the first half.
67       while (frequency_.size() > limit) {
68         frequency_.pop_back();
69       }
70     }
71     max_ += bucket_width_;
72     frequency_.push_back(0);
73   }
74 }
75 
FindBucket(Value val)76 template <class Value> inline size_t Histogram<Value>::FindBucket(Value val) const {
77   // Since this is only a linear histogram, bucket index can be found simply with
78   // dividing the value by the bucket width.
79   DCHECK_GE(val, min_);
80   DCHECK_LE(val, max_);
81   const size_t bucket_idx = static_cast<size_t>((val - min_) / bucket_width_);
82   DCHECK_GE(bucket_idx, 0ul);
83   DCHECK_LE(bucket_idx, GetBucketCount());
84   return bucket_idx;
85 }
86 
87 template <class Value>
BucketiseValue(Value val)88 inline void Histogram<Value>::BucketiseValue(Value val) {
89   CHECK_LT(val, max_);
90   sum_ += val;
91   sum_of_squares_ += val * val;
92   ++sample_size_;
93   ++frequency_[FindBucket(val)];
94   max_value_added_ = std::max(val, max_value_added_);
95   min_value_added_ = std::min(val, min_value_added_);
96 }
97 
Initialize()98 template <class Value> inline void Histogram<Value>::Initialize() {
99   for (size_t idx = 0; idx < kInitialBucketCount; idx++) {
100     frequency_.push_back(0);
101   }
102   // Cumulative frequency and ranges has a length of 1 over frequency.
103   max_ = bucket_width_ * GetBucketCount();
104 }
105 
GetBucketCount()106 template <class Value> inline size_t Histogram<Value>::GetBucketCount() const {
107   return frequency_.size();
108 }
109 
Reset()110 template <class Value> inline void Histogram<Value>::Reset() {
111   sum_of_squares_ = 0;
112   sample_size_ = 0;
113   min_ = 0;
114   sum_ = 0;
115   min_value_added_ = std::numeric_limits<Value>::max();
116   max_value_added_ = std::numeric_limits<Value>::min();
117   frequency_.clear();
118   Initialize();
119 }
120 
GetRange(size_t bucket_idx)121 template <class Value> inline Value Histogram<Value>::GetRange(size_t bucket_idx) const {
122   DCHECK_LE(bucket_idx, GetBucketCount());
123   return min_ + bucket_idx * bucket_width_;
124 }
125 
Mean()126 template <class Value> inline double Histogram<Value>::Mean() const {
127   DCHECK_GT(sample_size_, 0ull);
128   return static_cast<double>(sum_) / static_cast<double>(sample_size_);
129 }
130 
Variance()131 template <class Value> inline double Histogram<Value>::Variance() const {
132   DCHECK_GT(sample_size_, 0ull);
133   // Using algorithms for calculating variance over a population:
134   // http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance
135   Value sum_squared = sum_ * sum_;
136   double sum_squared_by_n_squared =
137       static_cast<double>(sum_squared) /
138       static_cast<double>(sample_size_ * sample_size_);
139   double sum_of_squares_by_n =
140       static_cast<double>(sum_of_squares_) / static_cast<double>(sample_size_);
141   return sum_of_squares_by_n - sum_squared_by_n_squared;
142 }
143 
144 template <class Value>
PrintBins(std::ostream & os,const CumulativeData & data)145 inline void Histogram<Value>::PrintBins(std::ostream& os, const CumulativeData& data) const {
146   DCHECK_GT(sample_size_, 0ull);
147   for (size_t bin_idx = 0; bin_idx < data.freq_.size(); ++bin_idx) {
148     if (bin_idx > 0 && data.perc_[bin_idx] == data.perc_[bin_idx - 1]) {
149       bin_idx++;
150       continue;
151     }
152     os << GetRange(bin_idx) << ": " << data.freq_[bin_idx] << "\t"
153        << data.perc_[bin_idx] * 100.0 << "%\n";
154   }
155 }
156 
157 template <class Value>
PrintConfidenceIntervals(std::ostream & os,double interval,const CumulativeData & data)158 inline void Histogram<Value>::PrintConfidenceIntervals(std::ostream &os, double interval,
159                                                        const CumulativeData& data) const {
160   DCHECK_GT(interval, 0);
161   DCHECK_LT(interval, 1.0);
162 
163   double per_0 = (1.0 - interval) / 2.0;
164   double per_1 = per_0 + interval;
165   os << Name() << ":\t";
166   TimeUnit unit = GetAppropriateTimeUnit(Mean() * kAdjust);
167   os << (interval * 100) << "% C.I. " << FormatDuration(Percentile(per_0, data) * kAdjust, unit);
168   os << "-" << FormatDuration(Percentile(per_1, data) * kAdjust, unit) << " ";
169   os << "Avg: " << FormatDuration(Mean() * kAdjust, unit) << " Max: ";
170   os << FormatDuration(Max() * kAdjust, unit) << "\n";
171 }
172 
CreateHistogram(CumulativeData & out_data)173 template <class Value> inline void Histogram<Value>::CreateHistogram(CumulativeData& out_data) {
174   DCHECK_GT(sample_size_, 0ull);
175   out_data.freq_.clear();
176   out_data.perc_.clear();
177   uint64_t accumulated = 0;
178   out_data.freq_.push_back(accumulated);
179   out_data.perc_.push_back(0.0);
180   for (size_t idx = 0; idx < frequency_.size(); idx++) {
181     accumulated += frequency_[idx];
182     out_data.freq_.push_back(accumulated);
183     out_data.perc_.push_back(static_cast<double>(accumulated) / static_cast<double>(sample_size_));
184   }
185   DCHECK_EQ(out_data.freq_.back(), sample_size_);
186   DCHECK_LE(std::abs(out_data.perc_.back() - 1.0), 0.001);
187 }
188 
189 template <class Value>
Percentile(double per,const CumulativeData & data)190 inline double Histogram<Value>::Percentile(double per, const CumulativeData& data) const {
191   DCHECK_GT(data.perc_.size(), 0ull);
192   size_t upper_idx = 0, lower_idx = 0;
193   for (size_t idx = 0; idx < data.perc_.size(); idx++) {
194     if (per <= data.perc_[idx]) {
195       upper_idx = idx;
196       break;
197     }
198 
199     if (per >= data.perc_[idx] && idx != 0 && data.perc_[idx] != data.perc_[idx - 1]) {
200       lower_idx = idx;
201     }
202   }
203 
204   const double lower_perc = data.perc_[lower_idx];
205   const double lower_value = static_cast<double>(GetRange(lower_idx));
206   if (per == lower_perc) {
207     return lower_value;
208   }
209 
210   const double upper_perc = data.perc_[upper_idx];
211   const double upper_value = static_cast<double>(GetRange(upper_idx));
212   if (per == upper_perc) {
213     return upper_value;
214   }
215   DCHECK_GT(upper_perc, lower_perc);
216 
217   double value = lower_value + (upper_value - lower_value) *
218                                (per - lower_perc) / (upper_perc - lower_perc);
219 
220   if (value < min_value_added_) {
221     value = min_value_added_;
222   } else if (value > max_value_added_) {
223     value = max_value_added_;
224   }
225 
226   return value;
227 }
228 
229 }  // namespace art
230 #endif  // ART_RUNTIME_BASE_HISTOGRAM_INL_H_
231 
232