content: /*
   * 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 com.actelion.research.util.ArrayUtils;
  
  import java.util.ArrayList;
  import java.util.Collection;
  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<Double> 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<Integer> 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<Long> 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<Integer> 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 ModelMedianInteger getMedianForInteger(int [] a) {
  		return getMedianForInteger(ArrayUtils.toList(a));
  	}
  
  	public static ModelMedianLong getMedianForLong(List<Long> 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
  	 * @return
  	 */
  	public static ModelMedianDouble getMedianForDouble(Collection<Double> liScoreRaw) {
  
  		if(liScoreRaw.size()<1)
  			return null;
  
  		List<Double> liScore = new ArrayList<>(liScoreRaw);
  
  		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;
  
  	}
  
  	
  
  }
  