/usr/include/mongo/util/descriptive_stats-inl.h is in mongodb-dev 1:2.4.9-1ubuntu2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 | /* Copyright 2012 10gen Inc.
*
* 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.
*
*
* Based upon boost.accumulators (www.boost.org/libs/accumulators/),
* distributed under the Boost Software License, Version 1.0.
* See distrc/THIRD_PARTY_NOTICES for the full License Notice for Boost.
*
*/
#pragma once
#include <algorithm>
#include <limits>
#include "mongo/util/mongoutils/str.h"
namespace mongo {
template <class Sample>
BasicEstimators<Sample>::BasicEstimators() :
_count(0),
_sum(0),
_diff(0),
_min(std::numeric_limits<Sample>::max()),
_max(std::numeric_limits<Sample>::min()) {
}
template <class Sample>
BasicEstimators<Sample>& BasicEstimators<Sample>::operator <<(const Sample sample) {
const double oldMean = (_count > 0) ? _sum / _count : 0;
const double delta = oldMean - static_cast<double>(sample);
const double weight = static_cast<double>(_count) / (_count + 1);
_diff += delta * delta * weight;
_sum += static_cast<double>(sample);
_count++;
_min = std::min(sample, _min);
_max = std::max(sample, _max);
return *this;
}
template <class Sample>
void BasicEstimators<Sample>::appendBasicToBSONObjBuilder(BSONObjBuilder& b) const {
b << "count" << static_cast<long long>(count())
<< "mean" << mean()
<< "stddev" << stddev()
<< "min" << min()
<< "max" << max();
}
template <std::size_t NumQuantiles>
DistributionEstimators<NumQuantiles>::DistributionEstimators() :
_count(0) {
for(std::size_t i = 0; i < NumMarkers; i++) {
_actual_positions[i] = i + 1;
}
for(std::size_t i = 0; i < NumMarkers; i++) {
_desired_positions[i] = 1.0 + (2.0 * (NumQuantiles + 1.0) * _positions_increments(i));
}
}
/*
* The quantile estimation follows the extended_p_square implementation in boost.accumulators.
* It differs by removing the ability to request arbitrary quantiles and computing exactly
* 'NumQuantiles' equidistant quantiles (plus minimum and maximum) instead.
* See http://www.boost.org/doc/libs/1_51_0/doc/html/boost/accumulators/impl/extended_p_square_impl.html ,
* R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and histograms without storing observations, Communications of the ACM, Volume 28 (October), Number 10, 1985, p. 1076-1085. and
* K. E. E. Raatikainen, Simultaneous estimation of several quantiles, Simulation, Volume 49, Number 4 (October), 1986, p. 159-164.
*/
template <std::size_t NumQuantiles>
DistributionEstimators<NumQuantiles>&
DistributionEstimators<NumQuantiles>::operator <<(const double sample) {
// first accumulate num_markers samples
if (_count++ < NumMarkers) {
_heights[_count - 1] = sample;
if (_count == NumMarkers)
{
std::sort(_heights, _heights + NumMarkers);
}
}
else {
std::size_t sample_cell = 1;
// find cell k = sample_cell such that heights[k-1] <= sample < heights[k]
if(sample < _heights[0])
{
_heights[0] = sample;
sample_cell = 1;
}
else if (sample >= _heights[NumMarkers - 1])
{
_heights[NumMarkers - 1] = sample;
sample_cell = NumMarkers - 1;
}
else {
double* it = std::upper_bound(_heights,
_heights + NumMarkers,
sample);
sample_cell = std::distance(_heights, it);
}
// update actual positions of all markers above sample_cell index
for(std::size_t i = sample_cell; i < NumMarkers; i++) {
_actual_positions[i]++;
}
// update desired positions of all markers
for(std::size_t i = 0; i < NumMarkers; i++) {
_desired_positions[i] += _positions_increments(i);
}
// adjust heights and actual positions of markers 1 to num_markers-2 if necessary
for(std::size_t i = 1; i <= NumMarkers - 2; i++) {
// offset to desired position
double d = _desired_positions[i] - _actual_positions[i];
// offset to next position
double dp = _actual_positions[i + 1] - _actual_positions[i];
// offset to previous position
double dm = _actual_positions[i - 1] - _actual_positions[i];
// height ds
double hp = (_heights[i + 1] - _heights[i]) / dp;
double hm = (_heights[i - 1] - _heights[i]) / dm;
if((d >= 1 && dp > 1) || (d <= -1 && dm < -1))
{
short sign_d = static_cast<short>(d / std::abs(d));
double h = _heights[i] + sign_d / (dp - dm) * ((sign_d - dm)*hp
+ (dp - sign_d) * hm);
// try adjusting heights[i] using p-squared formula
if(_heights[i - 1] < h && h < _heights[i + 1])
{
_heights[i] = h;
}
else
{
// use linear formula
if(d > 0)
{
_heights[i] += hp;
}
if(d < 0)
{
_heights[i] -= hm;
}
}
_actual_positions[i] += sign_d;
}
}
}
return *this;
}
template <std::size_t NumQuantiles>
void DistributionEstimators<NumQuantiles>::appendQuantilesToBSONArrayBuilder(
BSONArrayBuilder& arr) const {
verify(quantilesReady());
for (std::size_t i = 0; i <= NumQuantiles + 1; i++) {
arr << quantile(i);
}
}
template <std::size_t NumQuantiles>
inline double DistributionEstimators<NumQuantiles>::_positions_increments(std::size_t i) const {
return static_cast<double>(i) / (2 * (NumQuantiles + 1));
}
template <class Sample, std::size_t NumQuantiles>
BSONObj SummaryEstimators<Sample, NumQuantiles>::statisticSummaryToBSONObj() const {
BSONObjBuilder b;
this->BasicEstimators<Sample>::appendBasicToBSONObjBuilder(b);
if (this->DistributionEstimators<NumQuantiles>::quantilesReady()) {
// Not using appendQuantiles to be explicit about which probability each quantile
// refers to. This way the user does not need to count the quantiles or know in
// advance how many quantiles were computed to figure out their meaning.
BSONObjBuilder quantilesBuilder(b.subobjStart("quantiles"));
for (size_t i = 1; i <= NumQuantiles; i++) {
const double probability =
this->DistributionEstimators<NumQuantiles>::probability(i);
const double quantile =
this->DistributionEstimators<NumQuantiles>::quantile(i);
quantilesBuilder.append(std::string(mongoutils::str::stream() << probability),
quantile);
}
quantilesBuilder.doneFast();
}
return b.obj();
}
} // namespace mongo
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