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/**
* Copyright (c) 2011 10gen Inc.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License, version 3,
* as published by the Free Software Foundation.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
* As a special exception, the copyright holders give permission to link the
* code of portions of this program with the OpenSSL library under certain
* conditions as described in each individual source file and distribute
* linked combinations including the program with the OpenSSL library. You
* must comply with the GNU Affero General Public License in all respects for
* all of the code used other than as permitted herein. If you modify file(s)
* with this exception, you may extend this exception to your version of the
* file(s), but you are not obligated to do so. If you do not wish to do so,
* delete this exception statement from your version. If you delete this
* exception statement from all source files in the program, then also delete
* it in the license file.
*/
#include "mongo/platform/basic.h"
#include "mongo/db/pipeline/accumulator.h"
#include "mongo/db/pipeline/document.h"
#include "mongo/db/pipeline/expression_context.h"
#include "mongo/db/pipeline/value.h"
namespace mongo {
using boost::intrusive_ptr;
void AccumulatorStdDev::processInternal(const Value& input, bool merging) {
if (!merging) {
// non numeric types have no impact on standard deviation
if (!input.numeric())
return;
const double val = input.getDouble();
// This is an implementation of the following algorithm:
// http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Online_algorithm
_count += 1;
const double delta = val - _mean;
_mean += delta / _count;
_m2 += delta * (val - _mean);
} else {
// This is what getValue(true) produced below.
verify(input.getType() == Object);
const double m2 = input["m2"].getDouble();
const double mean = input["mean"].getDouble();
const long long count = input["count"].getLong();
if (count == 0)
return; // This partition had no data to contribute.
// This is an implementation of the following algorithm:
// http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
const double delta = mean - _mean;
const long long newCount = count + _count;
_mean = ((_count * _mean) + (count * mean)) / newCount;
_m2 += m2 + (delta * delta * (double(_count) * count / newCount));
_count = newCount;
}
}
Value AccumulatorStdDev::getValue(bool toBeMerged) const {
if (!toBeMerged) {
const long long adjustedCount = (_isSamp ? _count - 1 : _count);
if (adjustedCount <= 0)
return Value(BSONNULL); // standard deviation not well defined in this case
return Value(sqrt(_m2 / adjustedCount));
} else {
return Value(DOC("m2" << _m2 << "mean" << _mean << "count" << _count));
}
}
intrusive_ptr<Accumulator> AccumulatorStdDev::createSamp() {
return new AccumulatorStdDev(true);
}
intrusive_ptr<Accumulator> AccumulatorStdDev::createPop() {
return new AccumulatorStdDev(false);
}
AccumulatorStdDev::AccumulatorStdDev(bool isSamp) : _isSamp(isSamp), _count(0), _mean(0), _m2(0) {
// This is a fixed size Accumulator so we never need to update this
_memUsageBytes = sizeof(*this);
}
void AccumulatorStdDev::reset() {
_count = 0;
_mean = 0;
_m2 = 0;
}
const char* AccumulatorStdDev::getOpName() const {
return (_isSamp ? "$stdDevSamp" : "$stdDevPop");
}
}
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