Java tutorial
/* * The MIT License (MIT) * Copyright (c) 2015-2016 Thorsten Wagner (wagner@biomedical-imaging.de) * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in all * copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ package de.biomedical_imaging.traj.math; import org.apache.commons.math3.linear.Array2DRowRealMatrix; import de.biomedical_imaging.traJ.Trajectory; public class RadiusGyrationTensor2D { private Trajectory t; public RadiusGyrationTensor2D(Trajectory t) { this.t = t; } /** * Calculates the radius of gyration tensor according to formula (6.3) in * * ELEMENTS OF THE RANDOM WALK by Rudnick and Gaspari * * @return Radius of gyration tensor */ public Array2DRowRealMatrix getRadiusOfGyrationTensor() { return getRadiusOfGyrationTensor(t); } /** * Calculates the radius of gyration tensor according to formula (6.3) in * * ELEMENTS OF THE RANDOM WALK by Rudnick and Gaspari * * @return Radius of gyration tensor */ public static Array2DRowRealMatrix getRadiusOfGyrationTensor(Trajectory t) { double meanx = 0; double meany = 0; for (int i = 0; i < t.size(); i++) { meanx += t.get(i).x; meany += t.get(i).y; } meanx = meanx / t.size(); meany = meany / t.size(); double e11 = 0; double e12 = 0; double e21 = 0; double e22 = 0; for (int i = 0; i < t.size(); i++) { e11 += Math.pow(t.get(i).x - meanx, 2); e12 += (t.get(i).x - meanx) * (t.get(i).y - meany); e22 += Math.pow(t.get(i).y - meany, 2); } e11 = e11 / t.size(); e12 = e12 / t.size(); e21 = e12; e22 = e22 / t.size(); int rows = 2; int columns = 2; Array2DRowRealMatrix gyr = new Array2DRowRealMatrix(rows, columns); gyr.addToEntry(0, 0, e11); gyr.addToEntry(0, 1, e12); gyr.addToEntry(1, 0, e21); gyr.addToEntry(1, 1, e22); return gyr; } }