com.actelion.research.calc.regression.linear.simple.LinearRegression Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of openchemlib Show documentation
Show all versions of openchemlib Show documentation
Open Source Chemistry Library
/*
* Copyright (c) 1997 - 2016
* Actelion Pharmaceuticals Ltd.
* Gewerbestrasse 16
* 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.
*
*/
package com.actelion.research.calc.regression.linear.simple;
import java.awt.Point;
import java.util.List;
import java.util.Vector;
import com.actelion.research.util.datamodel.DoubleArray;
import com.actelion.research.util.datamodel.PointDouble;
/**
* LinearRegression
* 2009 MvK: Start implementation
*/
public class LinearRegression {
private double intercept; // Intercept
private double slope; // Slope
//vector of points
private Vector v;
//vector of residuals
private Vector residuals;
private double xMean;
private double yMean;
/**
*
*/
public LinearRegression() {
v = new Vector();
residuals = new Vector();
xMean = 0;
yMean = 0;
}
/**
* add a point to the vector of points
* @param p the point to be added
*/
public void addPoint(Point p){
v.addElement(new PointDouble(p));
}
public void addPoint(PointDouble p){
v.addElement(p);
}
public void addPoint(double x, double y){
v.addElement(new PointDouble(x, y));
}
public void clear(){
v = new Vector();
}
public List getValues(){
return v;
}
public double [][] getValuesAsArray(){
double [][] arr = new double [2][v.size()];
for (int i = 0; i < v.size(); i++) {
arr[0][i]=v.get(i).x;
arr[1][i]=v.get(i).y;
}
return arr;
}
public DoubleArray getValuesAsArrayX(){
DoubleArray arr = new DoubleArray(v.size());
for (int i = 0; i < v.size(); i++) {
arr.add(v.get(i).x);
}
return arr;
}
public DoubleArray getValuesAsArrayY(){
DoubleArray arr = new DoubleArray(v.size());
for (int i = 0; i < v.size(); i++) {
arr.add(v.get(i).y);
}
return arr;
}
public Vector regress() {
xMean = 0;
yMean = 0;
for (PointDouble p : v) {
xMean += p.x;
yMean += p.y;
}
xMean /= v.size();
yMean /= v.size();
double sxy2=0;
double sxx2=0;
for (PointDouble p : v) {
sxy2 += (p.x-xMean)*(p.y-yMean);
sxx2 += (p.x-xMean)*(p.x-xMean);
}
slope = sxy2/sxx2;
intercept = yMean - slope * xMean;
Vector resid = new Vector();
PointDouble q;
for (PointDouble p : v) {
double currentResidual = p.y-(intercept+slope*p.x);
q = new PointDouble(p.x, (int)currentResidual);
resid.addElement(q);
}
return resid;
}
public void calculate() {
if (v.size() >1) {
residuals=regress();
}
}
public Vector getResiduals(){
return residuals;
}
public PointDouble getMean(){
return new PointDouble(xMean+0.5, yMean+0.5);
}
public double getIntercept() {
return intercept;
}
public double getSlope() {
return slope;
}
public double getXMean() {
return xMean;
}
public double getYMean() {
return yMean;
}
public double getY(double x) {
return intercept + slope*x;
}
public void setSlope(double slope) {
this.slope = slope;
}
}