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Open Source Chemistry Library
/*
* Copyright (c) 1997 - 2018
* Idorsia Pharmaceuticals Ltd.
* Hegenheimermattweg 91
* CH-4123 Allschwil, Switzerland
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
* 3. Neither the name of the the copyright holder nor the
* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
* ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
* @author Modest v. Korff
*/
package com.actelion.research.calc.statistics.median;
import java.util.Collections;
import java.util.List;
/**
* MedianStatisticFunctions
* Aug 5, 2011 MvK: Start implementation
*/
public class MedianStatisticFunctions {
/**
*
* @param liScore list has to be sorted in ascending order.
* @param fraction 0.25 lower quartile, 0,5 median and 0.75 upper quartile.
* @return
*/
public static double getPercentileFromSorted(List liScore, double fraction) {
if(liScore.size()==1){
return liScore.get(0);
}
double percentile=0;
int len = liScore.size();
if(((int)(len*fraction))==(len*fraction)) {
int index1 = (int)(len*fraction)-1;
int index2 = index1+1;
if(index1<0){
throw new RuntimeException("Fraction to small.");
}
percentile = (liScore.get(index1)+liScore.get(index2))/2.0;
} else {
int index1 = (int)(len*fraction);
percentile = liScore.get(index1);
}
return percentile;
}
public static double getPercentileFromSorted(double [] arr, double fraction) {
return getPercentileFromSorted(arr, fraction, 0, arr.length);
}
public static double getPercentileFromSorted(float [] arr, double fraction) {
return getPercentileFromSorted(arr, fraction, 0, arr.length);
}
public static double getPercentileFromSorted(double [] arr, double fraction, int indexStart, int length) {
if(arr.length==1){
return arr[0];
}
double percentile=0;
if(((int)(length*fraction))==(length*fraction)) {
int index1 = (int)(length*fraction)-1 + indexStart;
int index2 = index1+1 + indexStart;
if(index1<0){
throw new RuntimeException("Fraction to small.");
}
percentile = (arr[index1]+arr[index2])/2.0;
} else {
int index1 = (int)(length*fraction) + indexStart;
percentile = arr[index1];
}
return percentile;
}
public static double getPercentileFromSorted(float [] arr, double fraction, int indexStart, int length) {
if(arr.length==1){
return arr[0];
}
double percentile=0;
if(((int)(length*fraction))==(length*fraction)) {
int index1 = (int)(length*fraction)-1 + indexStart;
int index2 = index1+1 + indexStart;
if(index1<0){
throw new RuntimeException("Fraction to small.");
}
percentile = (arr[index1]+arr[index2])/2.0;
} else {
int index1 = (int)(length*fraction) + indexStart;
percentile = arr[index1];
}
return percentile;
}
public static double getPercentileFromSortedInt(List liScore, double fraction) {
if(liScore.size()==1){
return liScore.get(0);
}
double percentile=0;
int len = liScore.size();
if(((int)(len*fraction))==(len*fraction)) {
int index1 = (int)((len*fraction)+0.5)-1;
int index2 = index1+1;
if(index1<0){
index1=0;
}
percentile = (liScore.get(index1)+liScore.get(index2))/2.0;
} else {
int index1 = (int)(len*fraction);
percentile = liScore.get(index1);
}
return percentile;
}
public static double getPercentileFromSortedLong(List liScore, double fraction) {
if(liScore.size()==1){
return liScore.get(0);
}
long percentile=0;
int len = liScore.size();
if(((int)(len*fraction))==(len*fraction)) {
int index1 = (int)((len*fraction)+0.5)-1;
int index2 = index1+1;
if(index1<0){
index1=0;
}
percentile = (long)((liScore.get(index1)+liScore.get(index2))/2.0);
} else {
int index1 = (int)(len*fraction);
percentile = liScore.get(index1);
}
return percentile;
}
/**
*
* @param liScore the list is sorted in the method.
* @return
*/
public static ModelMedianInteger getMedianForInteger(List liScore) {
Collections.sort(liScore);
ModelMedianInteger modelMedian = new ModelMedianInteger();
modelMedian.lowerQuartile = (int)(MedianStatisticFunctions.getPercentileFromSortedInt(liScore, 0.25) + 0.5);
modelMedian.median = (int)(MedianStatisticFunctions.getPercentileFromSortedInt(liScore, 0.5) + 0.5);
modelMedian.upperQuartile = (int)(MedianStatisticFunctions.getPercentileFromSortedInt(liScore, 0.75) + 0.5);
modelMedian.size = liScore.size();
return modelMedian;
}
public static ModelMedianLong getMedianForLong(List liScore) {
Collections.sort(liScore);
ModelMedianLong modelMedian = new ModelMedianLong();
modelMedian.lowerQuartile = (long)(MedianStatisticFunctions.getPercentileFromSortedLong(liScore, 0.25) + 0.5);
modelMedian.median = (long)(MedianStatisticFunctions.getPercentileFromSortedLong(liScore, 0.5) + 0.5);
modelMedian.upperQuartile = (long)(MedianStatisticFunctions.getPercentileFromSortedLong(liScore, 0.75) + 0.5);
modelMedian.size = liScore.size();
return modelMedian;
}
/**
*
* @param liScore the list is sorted in the method.
* @return
*/
public static ModelMedianDouble getMedianForDouble(List liScore) {
Collections.sort(liScore);
ModelMedianDouble modelMedian = new ModelMedianDouble();
modelMedian.lowerQuartile = MedianStatisticFunctions.getPercentileFromSorted(liScore, 0.25);
modelMedian.median = MedianStatisticFunctions.getPercentileFromSorted(liScore, 0.5);
modelMedian.upperQuartile = MedianStatisticFunctions.getPercentileFromSorted(liScore, 0.75);
modelMedian.size = liScore.size();
return modelMedian;
}
}