/* * Copyright (c) 2005–2012 Goethe Center for Scientific Computing - Simulation and Modelling (G-CSC Frankfurt) * Copyright (c) 2012-2015 Goethe Center for Scientific Computing - Computational Neuroscience (G-CSC Frankfurt) * * This file is part of NeuGen. * * NeuGen is free software: you can redistribute it and/or modify * it under the terms of the GNU Lesser General Public License version 3 * as published by the Free Software Foundation. * * see: http://opensource.org/licenses/LGPL-3.0 * file://path/to/NeuGen/LICENSE * * NeuGen is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU Lesser General Public License for more details. * * This version of NeuGen includes copyright notice and attribution requirements. * According to the LGPL this information must be displayed even if you modify * the source code of NeuGen. The copyright statement/attribution may not be removed. * * Attribution Requirements: * * If you create derived work you must do the following regarding copyright * notice and author attribution. * * Add an additional notice, stating that you modified NeuGen. In addition * you must cite the publications listed below. A suitable notice might read * "NeuGen source code modified by YourName 2012". * * Note, that these requirements are in full accordance with the LGPL v3 * (see 7. Additional Terms, b). * * Publications: * * S. Wolf, S. Grein, G. Queisser. NeuGen 2.0 - * Employing NeuGen 2.0 to automatically generate realistic * morphologies of hippocapal neurons and neural networks in 3D. * Neuroinformatics, 2013, 11(2), pp. 137-148, doi: 10.1007/s12021-012-9170-1 * * * J. P. Eberhard, A. Wanner, G. Wittum. NeuGen - * A tool for the generation of realistic morphology * of cortical neurons and neural networks in 3D. * Neurocomputing, 70(1-3), pp. 327-343, doi: 10.1016/j.neucom.2006.01.028 * */ package org.neugen.parsers; import org.neugen.utils.Utils; import java.io.BufferedInputStream; import org.neugen.gui.*; import java.io.FileInputStream; import java.io.IOException; import java.io.ObjectInputStream; import org.apache.log4j.Logger; import org.jdesktop.application.Application; import org.jdesktop.application.Task; import org.neugen.datastructures.Net; import org.neugen.datastructures.Region; import org.neugen.datastructures.neuron.Neuron; /** * @author Sergei Wolf */ public final class NeuGenReaderTask extends Task<Void, Void> { private final static Logger logger = Logger.getLogger(NeuroMLReaderTask.class.getName()); public NeuGenView ngView; public NeuGenReaderTask(Application app) { super(app); ngView = NeuGenView.getInstance(); } public void setMyProgress(int value, int min, int max) { setProgress(value, min, max); } @Override protected Void doInBackground() throws IOException { try { ngView.outPrintln("Reading NeuGen Project data.."); String netSer = ngView.getProjectDirPath() + System.getProperty("file.separator") + "net.ser"; ObjectInputStream netIn = new ObjectInputStream(new BufferedInputStream(new FileInputStream(netSer))); try { Net net = (Net) netIn.readObject(); if(net != null) { Region.setInstance(net.getRegion()); for (Neuron neuron : net.getNeuronList()) { neuron.infoNeuron(); } //net.setTotalNumberOfSegments(); ngView.setNet(net); String synMes = "\n"; synMes += " number of synapses: " + net.getNumSynapse() + "\n"; long nbilSyn = net.getNumSynapse() - net.getNumNonFunSynapses(); synMes += " number of bilateral synapses: " + nbilSyn + "\n"; synMes += " nonfunctional synapses: " + net.getNumNonFunSynapses() + "\n"; ngView.outPrintln(synMes); } } catch (ClassNotFoundException ex) { logger.error(ex, ex); } netIn.close(); } catch (IOException ex) { logger.error(ex, ex); } return null; } @Override protected void succeeded(Void result) { ngView.setNetExist(true); ngView.enableButtons(); System.gc(); ngView.outPrintln(Utils.getMemoryStatus()); } }