/* * 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(); } }