/**
* "FNS" (Firnet NeuroScience), ver.3.x
*
* FNS is an event-driven Spiking Neural Network framework, oriented
* to data-driven neural simulations.
*
* (c) 2020, Gianluca Susi, Emanuele Paracone, Mario Salerno,
* Alessandro Cristini, Fernando Maestú.
*
* CITATION:
* When using FNS for scientific publications, cite us as follows:
*
* Gianluca Susi, Pilar Garcés, Alessandro Cristini, Emanuele Paracone,
* Mario Salerno, Fernando Maestú, Ernesto Pereda (2020).
* "FNS: an event-driven spiking neural network simulator based on the
* LIFL neuron model".
* Laboratory of Cognitive and Computational Neuroscience, UPM-UCM
* Centre for Biomedical Technology, Technical University of Madrid;
* University of Rome "Tor Vergata".
* Paper under review.
*
* FNS is free software: you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 3 as
* published by the Free Software Foundation.
*
* FNS 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with FNS. If not, see <http://www.gnu.org/licenses/>.
*
* -----------------------------------------------------------
*
* Website: http://www.fnsneuralsimulator.org
*
* Contacts: fnsneuralsimulator (at) gmail.com
* gianluca.susi82 (at) gmail.com
* emanuele.paracone (at) gmail.com
*
*
* -----------------------------------------------------------
* -----------------------------------------------------------
**/
package utils.configuration;
import javax.xml.bind.annotation.XmlAccessType;
import javax.xml.bind.annotation.XmlAccessorType;
import javax.xml.bind.annotation.XmlRootElement;
import utils.constants.Constants;
@XmlAccessorType(XmlAccessType.FIELD)
@XmlRootElement(name = "node")
public class NodeCfg {
private Integer id;
private Double rewiring_P;
private Integer k;
private Long n;
private Double R;
private Double mu_w_exc;
private Double mu_w_inh;
private Double sigma_w_exc;
private Double sigma_w_inh;
private Double w_pre_exc;
private Double w_pre_inh;
private Integer external_inputs_number;
private Integer external_inputs_type;
private Double external_inputs_time_offset;
private Integer external_inputs_fireduration;
private Double external_inputs_timestep;
private Integer external_inputs_outdegree;
//private Double external_inputs_firerate;
private Double external_inputs_amplitude;
private Boolean small_world_topology;
private Integer Bn;
private Double IBI;
private NeuManCfg neuron_manager;
private Boolean plasticity;
private Double etap;
private Double etam;
private Double taup;
private Double taum;
private Double w_max;
private Double to;
public Integer getId() {
return id;
}
public void setId(Integer id) {
this.id = id;
}
public Double get_rewiring_P() {
return rewiring_P;
}
public void set_rewiring_P(Double prew) {
this.rewiring_P = prew;
}
public Integer getK() {
return k;
}
public void setK(Integer k) {
this.k = k;
}
public Long getN() {
return n;
}
public void setN(Long n) {
this.n = n;
}
public Double getExcitatory_inhibitory_ratio() {
return R;
}
public void setExcitatory_inhibitory_ratio(Double excitRatio) {
this.R = excitRatio;
}
public Double getW_pre_exc() {
return w_pre_exc;
}
public void setW_pre_exc(Double exc_ampl) {
this.w_pre_exc = exc_ampl;
}
public Double getW_pre_inh() {
return w_pre_inh;
}
public void setW_pre_inh(Double inh_ampl) {
this.w_pre_inh = inh_ampl;
}
public Double getMu_w_exc() {
return mu_w_exc;
}
public Double getMu_w_inh() {
return mu_w_inh;
}
public void setMu_w_exc(Double mu_w_exc) {
this.mu_w_exc = mu_w_exc;
}
public void setMu_w_inh(Double mu_w_inh) {
this.mu_w_inh = mu_w_inh;
}
public Double getSigma_w_exc() {
return sigma_w_exc;
}
public Double getSigma_w_inh() {
return sigma_w_inh;
}
public void setSigma_w_exc(Double sigma_w_exc) {
this.sigma_w_exc = sigma_w_exc;
}
public void setSigma_w_inh(Double sigma_w_inh) {
this.sigma_w_inh = sigma_w_inh;
}
public Integer getExternal_inputs_number() {
return external_inputs_number;
}
public void setExternal_inputs_number(Integer external_inputs_number) {
this.external_inputs_number = external_inputs_number;
}
public Boolean getSmall_world_topology() {
return small_world_topology;
}
public void setSmall_world_topology(Boolean smallWorld) {
this.small_world_topology = smallWorld;
}
public Integer getExternal_inputs_type() {
return external_inputs_type;
}
public void setExternal_inputs_type(Integer external_inputs_type) {
this.external_inputs_type = external_inputs_type;
}
public Double getExternal_inputs_time_offset() {
return external_inputs_time_offset;
}
public void setExternal_inputs_time_offset(Double external_inputs_time_offset) {
this.external_inputs_time_offset = external_inputs_time_offset;
}
public Double getExternal_inputs_timestep() {
return external_inputs_timestep;
}
public void setExternal_inputs_timestep(Double external_inputs_timestep) {
this.external_inputs_timestep = external_inputs_timestep;
}
//public Double getExternal_inputs_firerate() {
// return external_inputs_firerate;
//}
//public void setExternal_inputs_firerate(Double external_inputs_firerate) {
// this.external_inputs_firerate = external_inputs_firerate;
//}
public Double getExternal_inputs_amplitude() {
return external_inputs_amplitude;
}
public void setExternal_inputs_amplitude(Double external_inputs_amplitude) {
this.external_inputs_amplitude = external_inputs_amplitude;
}
public Integer getExternal_inputs_fireduration() {
return external_inputs_fireduration;
}
public void setExternal_inputs_fireduration(Integer external_inputs_fireduration) {
this.external_inputs_fireduration = external_inputs_fireduration;
}
public Integer getExternal_inputs_outdegree() {
return external_inputs_outdegree;
}
public void setExternal_inputs_outdegree(Integer external_inputs_outdegree) {
this.external_inputs_outdegree = external_inputs_outdegree;
}
public Integer getBn() {
return Bn;
}
public void setBn(Integer bn) {
Bn = bn;
}
public Double getIBI() {
return IBI;
}
public void setIBI(Double iBI) {
IBI = iBI;
}
public Boolean getPlasticity() {
return plasticity;
}
public void setPlasticity(Boolean plasticity) {
this.plasticity = plasticity;
}
public Double getEtap() {
return etap;
}
public void setEtap(Double etap) {
this.etap = etap;
}
public Double getEtam() {
return etam;
}
public void setEtam(Double etam) {
this.etam = etam;
}
public Double getTaup() {
return taup;
}
public void setTaup(Double taup) {
this.taup = taup;
}
public Double getTaum() {
return taum;
}
public void setTaum(Double taum) {
this.taum = taum;
}
public Double getW_max() {
return w_max;
}
public void setW_max(Double w_max) {
this.w_max = w_max;
}
public Double getTo() {
return to;
}
public void setTo(Double to) {
this.to = to;
}
public NeuManCfg getNeuron_manager(){
return neuron_manager;
}
public void setNeuron_manager(NeuManCfg neuron_manager){
this.neuron_manager=neuron_manager;
}
}