/*
* 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());
}
}