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.features; import java.awt.geom.Point2D; import org.apache.commons.math3.stat.descriptive.moment.Mean; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import de.biomedical_imaging.traJ.Trajectory; import de.biomedical_imaging.traj.math.TrajectorySplineFit; /** * Implements the spline curve spatial analysis method according to: * [1] B. R. Long and T. Q. Vu, * Spatial structure and diffusive dynamics from single-particle trajectories using spline analysis,? * Biophys. J., vol. 98, no. 8, pp. 17121721, 2010. * @author Thorsten Wagner * */ public class SplineCurveSpatialFeature extends AbstractTrajectoryFeature { private Trajectory t; private int nSegments; private TrajectorySplineFit splinefit; public SplineCurveSpatialFeature(Trajectory t, int nSegments) { this.t = t; this.nSegments = nSegments; } @Override /** * @return [0] Mean distance [1] SD distance */ public double[] evaluate() { splinefit = new TrajectorySplineFit(t, nSegments); splinefit.calculateSpline(); if (!splinefit.wasSuccessfull()) { return new double[] { Double.NaN, Double.NaN }; } double[] data = new double[t.size()]; for (int i = 0; i < t.size(); i++) { Point2D.Double help = new Point2D.Double(splinefit.getRotatedTrajectory().get(i).x, splinefit.getRotatedTrajectory().get(i).y); data[i] = help.distance(splinefit.minDistancePointSpline(new Point2D.Double( splinefit.getRotatedTrajectory().get(i).x, splinefit.getRotatedTrajectory().get(i).y), 50)); } Mean m = new Mean(); StandardDeviation sd = new StandardDeviation(); result = new double[] { m.evaluate(data), sd.evaluate(data) }; return result; } public TrajectorySplineFit getTrajectorySplineFitInstance() { return splinefit; } @Override public String getName() { return "Spline curve spatial feature"; } @Override public void setTrajectory(Trajectory t) { this.t = t; result = null; } @Override public String getShortName() { // TODO Auto-generated method stub return "SCSA"; } }