/*
* 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
*
*/
/*
* File: L5BPyramidalNeuron.java
* Created on 13.10.2009, 09:41:58
*
*/
package org.neugen.datastructures.neuron;
import java.io.Serializable;
import org.neugen.datastructures.DataStructureConstants;
import org.neugen.datastructures.parameter.ParameterConstants;
import org.neugen.utils.Vrand;
/**
*
* @author Jens u. Simone Eberhard
* @author Alexander Wanner
*
*/
public final class NeuronL5BPyramidal extends NeuronL5Pyramidal implements Serializable, Neuron {
/**
* Class for cell parameter of L5Bpyramidal neuron.
*/
public static final class Param extends L5PyramidalParam {
private static Param instance;
/** Constructs contained parameters. */
public Param(String lastKey) {
super(L5PyramidalParam.getInstance(), lastKey);
if (instance != null) {
throw new IllegalStateException("Already instantiated");
}
}
public static void setInstance(Param instance) {
Param.instance = instance;
}
/** Returns instance. */
public static Param getInstance() {
if(instance == null) {
Param param = new Param(ParameterConstants.SUFFIX_PATH_L5BPYRAMIDAL_PARAM);
param.setApicalParam(ParameterConstants.LAST_KEY_APICAL);
param.setBasalParam(ParameterConstants.LAST_KEY_BASAL);
Param.setInstance(param);
}
return instance;
}
}
private static final long serialVersionUID = -8689337817498031243L;
/** Constructor. */
public NeuronL5BPyramidal() {
super();
type = DataStructureConstants.L5B_PYRAMIDAL;
if (basalRandomNumber == null) {
basalRandomNumber = new Vrand(getParam().getDendriteParam().getSeedValue());
}
if (apicalRandomNumber == null) {
apicalRandomNumber = new Vrand(getParam().getApicalParam().getSeedValue());
}
if (drawNumber == null) {
drawNumber = new Vrand(getParam().getSeedValue());
}
}
@Override
public Param getParam() {
return Param.getInstance();
}
}