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package de.lmu.ifi.dbs.elki.math;
import de.lmu.ifi.dbs.elki.utilities.exceptions.AbortException;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2012
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
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/>.
*/
/**
* Class collecting mean, variance, minimum and maximum statistics.
*
* @author Erich Schubert
*/
public class MeanVarianceMinMax extends MeanVariance {
/**
* Minimum value
*/
double min = Double.POSITIVE_INFINITY;
/**
* Maximum value
*/
double max = Double.NEGATIVE_INFINITY;
/**
* Constructor.
*/
public MeanVarianceMinMax() {
super();
}
/**
* Constructor cloning existing statistics.
*
* @param other Existing statistics
*/
public MeanVarianceMinMax(MeanVarianceMinMax other) {
super(other);
this.min = other.min;
this.max = other.max;
}
@Override
public void put(double val) {
super.put(val);
min = Math.min(min, val);
max = Math.max(max, val);
}
@Override
public void put(double val, double weight) {
super.put(val, weight);
min = Math.min(min, val);
max = Math.max(max, val);
}
@Override
public void put(Mean other) {
if(other instanceof MeanVarianceMinMax) {
super.put(other);
min = Math.min(min, ((MeanVarianceMinMax) other).min);
max = Math.max(max, ((MeanVarianceMinMax) other).max);
}
else {
throw new AbortException("Cannot aggregate into a minmax statistic: " + other.getClass());
}
}
/**
* Get the current minimum.
*
* @return current minimum.
*/
public double getMin() {
return this.min;
}
/**
* Get the current maximum.
*
* @return current maximum.
*/
public double getMax() {
return this.max;
}
/**
* Return the difference between minimum and maximum.
*
* @return Difference of current Minimum and Maximum.
*/
public double getDiff() {
return this.getMax() - this.getMin();
}
/**
* Create and initialize a new array of MeanVarianceMinMax
*
* @param dimensionality Dimensionality
* @return New and initialized Array
*/
public static MeanVarianceMinMax[] newArray(int dimensionality) {
MeanVarianceMinMax[] arr = new MeanVarianceMinMax[dimensionality];
for(int i = 0; i < dimensionality; i++) {
arr[i] = new MeanVarianceMinMax();
}
return arr;
}
@Override
public String toString() {
return "MeanVarianceMinMax(mean=" + getMean() + ",var=" + getSampleVariance() + ",min=" + getMin() + ",max=" + getMax() + ")";
}
@Override
public void reset() {
super.reset();
min = Double.POSITIVE_INFINITY;
max = Double.NEGATIVE_INFINITY;
}
}
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