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The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.
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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.
*/
package org.apache.commons.math3.stat.descriptive;
import java.io.Serializable;
import java.util.Collection;
import java.util.Iterator;
import org.apache.commons.math3.exception.NullArgumentException;
/**
*
* An aggregator for {@code SummaryStatistics} from several data sets or
* data set partitions. In its simplest usage mode, the client creates an
* instance via the zero-argument constructor, then uses
* {@link #createContributingStatistics()} to obtain a {@code SummaryStatistics}
* for each individual data set / partition. The per-set statistics objects
* are used as normal, and at any time the aggregate statistics for all the
* contributors can be obtained from this object.
*
* Clients with specialized requirements can use alternative constructors to
* control the statistics implementations and initial values used by the
* contributing and the internal aggregate {@code SummaryStatistics} objects.
*
* A static {@link #aggregate(Collection)} method is also included that computes
* aggregate statistics directly from a Collection of SummaryStatistics instances.
*
* When {@link #createContributingStatistics()} is used to create SummaryStatistics
* instances to be aggregated concurrently, the created instances'
* {@link SummaryStatistics#addValue(double)} methods must synchronize on the aggregating
* instance maintained by this class. In multithreaded environments, if the functionality
* provided by {@link #aggregate(Collection)} is adequate, that method should be used
* to avoid unnecessary computation and synchronization delays.
*
* @since 2.0
*
*/
public class AggregateSummaryStatistics implements StatisticalSummary,
Serializable {
/** Serializable version identifier */
private static final long serialVersionUID = -8207112444016386906L;
/**
* A SummaryStatistics serving as a prototype for creating SummaryStatistics
* contributing to this aggregate
*/
private final SummaryStatistics statisticsPrototype;
/**
* The SummaryStatistics in which aggregate statistics are accumulated.
*/
private final SummaryStatistics statistics;
/**
* Initializes a new AggregateSummaryStatistics with default statistics
* implementations.
*
*/
public AggregateSummaryStatistics() {
// No try-catch or throws NAE because arg is guaranteed non-null
this(new SummaryStatistics());
}
/**
* Initializes a new AggregateSummaryStatistics with the specified statistics
* object as a prototype for contributing statistics and for the internal
* aggregate statistics. This provides for customized statistics implementations
* to be used by contributing and aggregate statistics.
*
* @param prototypeStatistics a {@code SummaryStatistics} serving as a
* prototype both for the internal aggregate statistics and for
* contributing statistics obtained via the
* {@code createContributingStatistics()} method. Being a prototype
* means that other objects are initialized by copying this object's state.
* If {@code null}, a new, default statistics object is used. Any statistic
* values in the prototype are propagated to contributing statistics
* objects and (once) into these aggregate statistics.
* @throws NullArgumentException if prototypeStatistics is null
* @see #createContributingStatistics()
*/
public AggregateSummaryStatistics(SummaryStatistics prototypeStatistics) throws NullArgumentException {
this(prototypeStatistics,
prototypeStatistics == null ? null : new SummaryStatistics(prototypeStatistics));
}
/**
* Initializes a new AggregateSummaryStatistics with the specified statistics
* object as a prototype for contributing statistics and for the internal
* aggregate statistics. This provides for different statistics implementations
* to be used by contributing and aggregate statistics and for an initial
* state to be supplied for the aggregate statistics.
*
* @param prototypeStatistics a {@code SummaryStatistics} serving as a
* prototype both for the internal aggregate statistics and for
* contributing statistics obtained via the
* {@code createContributingStatistics()} method. Being a prototype
* means that other objects are initialized by copying this object's state.
* If {@code null}, a new, default statistics object is used. Any statistic
* values in the prototype are propagated to contributing statistics
* objects, but not into these aggregate statistics.
* @param initialStatistics a {@code SummaryStatistics} to serve as the
* internal aggregate statistics object. If {@code null}, a new, default
* statistics object is used.
* @see #createContributingStatistics()
*/
public AggregateSummaryStatistics(SummaryStatistics prototypeStatistics,
SummaryStatistics initialStatistics) {
this.statisticsPrototype =
(prototypeStatistics == null) ? new SummaryStatistics() : prototypeStatistics;
this.statistics =
(initialStatistics == null) ? new SummaryStatistics() : initialStatistics;
}
/**
* {@inheritDoc}. This version returns the maximum over all the aggregated
* data.
*
* @see StatisticalSummary#getMax()
*/
public double getMax() {
synchronized (statistics) {
return statistics.getMax();
}
}
/**
* {@inheritDoc}. This version returns the mean of all the aggregated data.
*
* @see StatisticalSummary#getMean()
*/
public double getMean() {
synchronized (statistics) {
return statistics.getMean();
}
}
/**
* {@inheritDoc}. This version returns the minimum over all the aggregated
* data.
*
* @see StatisticalSummary#getMin()
*/
public double getMin() {
synchronized (statistics) {
return statistics.getMin();
}
}
/**
* {@inheritDoc}. This version returns a count of all the aggregated data.
*
* @see StatisticalSummary#getN()
*/
public long getN() {
synchronized (statistics) {
return statistics.getN();
}
}
/**
* {@inheritDoc}. This version returns the standard deviation of all the
* aggregated data.
*
* @see StatisticalSummary#getStandardDeviation()
*/
public double getStandardDeviation() {
synchronized (statistics) {
return statistics.getStandardDeviation();
}
}
/**
* {@inheritDoc}. This version returns a sum of all the aggregated data.
*
* @see StatisticalSummary#getSum()
*/
public double getSum() {
synchronized (statistics) {
return statistics.getSum();
}
}
/**
* {@inheritDoc}. This version returns the variance of all the aggregated
* data.
*
* @see StatisticalSummary#getVariance()
*/
public double getVariance() {
synchronized (statistics) {
return statistics.getVariance();
}
}
/**
* Returns the sum of the logs of all the aggregated data.
*
* @return the sum of logs
* @see SummaryStatistics#getSumOfLogs()
*/
public double getSumOfLogs() {
synchronized (statistics) {
return statistics.getSumOfLogs();
}
}
/**
* Returns the geometric mean of all the aggregated data.
*
* @return the geometric mean
* @see SummaryStatistics#getGeometricMean()
*/
public double getGeometricMean() {
synchronized (statistics) {
return statistics.getGeometricMean();
}
}
/**
* Returns the sum of the squares of all the aggregated data.
*
* @return The sum of squares
* @see SummaryStatistics#getSumsq()
*/
public double getSumsq() {
synchronized (statistics) {
return statistics.getSumsq();
}
}
/**
* Returns a statistic related to the Second Central Moment. Specifically,
* what is returned is the sum of squared deviations from the sample mean
* among the all of the aggregated data.
*
* @return second central moment statistic
* @see SummaryStatistics#getSecondMoment()
*/
public double getSecondMoment() {
synchronized (statistics) {
return statistics.getSecondMoment();
}
}
/**
* Return a {@link StatisticalSummaryValues} instance reporting current
* aggregate statistics.
*
* @return Current values of aggregate statistics
*/
public StatisticalSummary getSummary() {
synchronized (statistics) {
return new StatisticalSummaryValues(getMean(), getVariance(), getN(),
getMax(), getMin(), getSum());
}
}
/**
* Creates and returns a {@code SummaryStatistics} whose data will be
* aggregated with those of this {@code AggregateSummaryStatistics}.
*
* @return a {@code SummaryStatistics} whose data will be aggregated with
* those of this {@code AggregateSummaryStatistics}. The initial state
* is a copy of the configured prototype statistics.
*/
public SummaryStatistics createContributingStatistics() {
SummaryStatistics contributingStatistics
= new AggregatingSummaryStatistics(statistics);
// No try - catch or advertising NAE because neither argument will ever be null
SummaryStatistics.copy(statisticsPrototype, contributingStatistics);
return contributingStatistics;
}
/**
* Computes aggregate summary statistics. This method can be used to combine statistics
* computed over partitions or subsamples - i.e., the StatisticalSummaryValues returned
* should contain the same values that would have been obtained by computing a single
* StatisticalSummary over the combined dataset.
*
* Returns null if the collection is empty or null.
*
*
* @param statistics collection of SummaryStatistics to aggregate
* @return summary statistics for the combined dataset
*/
public static StatisticalSummaryValues aggregate(Collection statistics) {
if (statistics == null) {
return null;
}
Iterator iterator = statistics.iterator();
if (!iterator.hasNext()) {
return null;
}
StatisticalSummary current = iterator.next();
long n = current.getN();
double min = current.getMin();
double sum = current.getSum();
double max = current.getMax();
double var = current.getVariance();
double m2 = var * (n - 1d);
double mean = current.getMean();
while (iterator.hasNext()) {
current = iterator.next();
if (current.getMin() < min || Double.isNaN(min)) {
min = current.getMin();
}
if (current.getMax() > max || Double.isNaN(max)) {
max = current.getMax();
}
sum += current.getSum();
final double oldN = n;
final double curN = current.getN();
n += curN;
final double meanDiff = current.getMean() - mean;
mean = sum / n;
final double curM2 = current.getVariance() * (curN - 1d);
m2 = m2 + curM2 + meanDiff * meanDiff * oldN * curN / n;
}
final double variance;
if (n == 0) {
variance = Double.NaN;
} else if (n == 1) {
variance = 0d;
} else {
variance = m2 / (n - 1);
}
return new StatisticalSummaryValues(mean, variance, n, max, min, sum);
}
/**
* A SummaryStatistics that also forwards all values added to it to a second
* {@code SummaryStatistics} for aggregation.
*
* @since 2.0
*/
private static class AggregatingSummaryStatistics extends SummaryStatistics {
/**
* The serialization version of this class
*/
private static final long serialVersionUID = 1L;
/**
* An additional SummaryStatistics into which values added to these
* statistics (and possibly others) are aggregated
*/
private final SummaryStatistics aggregateStatistics;
/**
* Initializes a new AggregatingSummaryStatistics with the specified
* aggregate statistics object
*
* @param aggregateStatistics a {@code SummaryStatistics} into which
* values added to this statistics object should be aggregated
*/
AggregatingSummaryStatistics(SummaryStatistics aggregateStatistics) {
this.aggregateStatistics = aggregateStatistics;
}
/**
* {@inheritDoc}. This version adds the provided value to the configured
* aggregate after adding it to these statistics.
*
* @see SummaryStatistics#addValue(double)
*/
@Override
public void addValue(double value) {
super.addValue(value);
synchronized (aggregateStatistics) {
aggregateStatistics.addValue(value);
}
}
/**
* Returns true iff object is a
* SummaryStatistics instance and all statistics have the
* same values as this.
* @param object the object to test equality against.
* @return true if object equals this
*/
@Override
public boolean equals(Object object) {
if (object == this) {
return true;
}
if (object instanceof AggregatingSummaryStatistics == false) {
return false;
}
AggregatingSummaryStatistics stat = (AggregatingSummaryStatistics)object;
return super.equals(stat) &&
aggregateStatistics.equals(stat.aggregateStatistics);
}
/**
* Returns hash code based on values of statistics
* @return hash code
*/
@Override
public int hashCode() {
return 123 + super.hashCode() + aggregateStatistics.hashCode();
}
}
}