/*
* Copyright 2003-2004 The Apache Software Foundation.
*
* 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.
*/
package org.apache.commons.math.stat.descriptive;
import java.io.Serializable;
import org.apache.commons.math.util.ResizableDoubleArray;
/**
* Default implementation of
* {@link org.apache.commons.math.stat.descriptive.DescriptiveStatistics}.
*
* @version $Revision: 1.1 $ $Date: 2004/10/08 05:08:17 $
*/
public class DescriptiveStatisticsImpl extends DescriptiveStatistics implements Serializable {
/** Serializable version identifier */
static final long serialVersionUID = -1868088725461221010L;
/** hold the window size **/
protected int windowSize;
/**
* Stored data values
*/
protected ResizableDoubleArray eDA;
/**
* Construct a DescriptiveStatisticsImpl with infinite window
*/
public DescriptiveStatisticsImpl() {
this(INFINITE_WINDOW);
}
/**
* Construct a DescriptiveStatisticsImpl with finite window
* @param window the finite window size.
*/
public DescriptiveStatisticsImpl(int window) {
super();
eDA = new ResizableDoubleArray();
setWindowSize(window);
}
/**
* Access the window size.
* @return the current window size.
*/
public int getWindowSize() {
return windowSize;
}
/**
* @see org.apache.commons.math.stat.descriptive.DescriptiveStatistics#getValues()
*/
public double[] getValues() {
double[] copiedArray = new double[eDA.getNumElements()];
System.arraycopy(
eDA.getElements(),
0,
copiedArray,
0,
eDA.getNumElements());
return copiedArray;
}
/**
* @see org.apache.commons.math.stat.descriptive.DescriptiveStatistics#getElement(int)
*/
public double getElement(int index) {
return eDA.getElement(index);
}
/**
* @see org.apache.commons.math.stat.descriptive.DescriptiveStatistics#getN()
*/
public long getN() {
return eDA.getNumElements();
}
/**
* @see org.apache.commons.math.stat.descriptive.DescriptiveStatistics#addValue(double)
*/
public void addValue(double v) {
if (windowSize != INFINITE_WINDOW) {
if (getN() == windowSize) {
eDA.addElementRolling(v);
} else if (getN() < windowSize) {
eDA.addElement(v);
}
} else {
eDA.addElement(v);
}
}
/**
* @see org.apache.commons.math.stat.descriptive.DescriptiveStatistics#clear()
*/
public void clear() {
eDA.clear();
}
/**
* @see org.apache.commons.math.stat.descriptive.DescriptiveStatistics#setWindowSize(int)
*/
public void setWindowSize(int windowSize) {
if (windowSize < 1) {
if (windowSize != INFINITE_WINDOW) {
throw new IllegalArgumentException("window size must be positive.");
}
}
this.windowSize = windowSize;
// We need to check to see if we need to discard elements
// from the front of the array. If the windowSize is less than
// the current number of elements.
if (windowSize != INFINITE_WINDOW && windowSize < eDA.getNumElements()) {
eDA.discardFrontElements(eDA.getNumElements() - windowSize);
}
}
/**
* Apply the given statistic to this univariate collection.
* @param stat the statistic to apply
* @return the computed value of the statistic.
*/
public double apply(UnivariateStatistic stat) {
return stat.evaluate(eDA.getValues(), eDA.start(), eDA.getNumElements());
}
}