public static void main(String[] args) {
ECM.setRandomSeed(2L);
Cell c = CellFactory.getCellInstance(new double[] {0.0, 0.0, 0.0});
c.addCellModule(new DividingModule());
Scheduler.simulateOneStep();
Scheduler.simulateOneStep();
ini.cx3d.utilities.SystemUtilities.tic();
for (int i = 0; i < 5000; i++) {
Scheduler.simulateOneStep();
}
ini.cx3d.utilities.SystemUtilities.tac();
}
public static void main(String[] args) {
Param.NEURITE_MAX_LENGTH = 20;
double pi = Math.PI;
// get a 2.5D ECM
ECM ecm = ECM.getInstance();
ECM.setRandomSeed(5L);
ecm.setArtificialWallsForCylinders(true);
ecm.setArtificialWallsForSpheres(true);
ecm.setBoundaries(-10000, 10000, -10000, 10000, -5, 5);
// eighteen extra PhysicalNodes :
for (int i = 0; i < 12; i++) {
double[] loc = concat(randomNoise(600, 2), randomNoise(100, 1));
ecm.getPhysicalNodeInstance(loc);
}
// set the inter object force
X_Adhesive_Force nogo = new X_Adhesive_Force();
nogo.setAttractionRange(3);
nogo.setAttractionStrength(5);
PhysicalObject.setInterObjectForce(nogo);
// generate cells
int nbOfCells = 20;
int minNbOfNeurites = 4;
int maxNbOfNeurites = 8;
for (int i = 0; i < nbOfCells; i++) {
Color c = Param.X_SOLID_GRAY;
double[] cellLocation =
new double[] {
-200 + ECM.getRandomDouble() * 400,
-200 + ECM.getRandomDouble() * 400,
-5 + ECM.getRandomDouble() * 10
};
if (i == 0) {
c = Param.X_SOLID_RED;
cellLocation = new double[] {0, 0, 0};
}
Cell cell = CellFactory.getCellInstance(cellLocation);
SomaElement soma = cell.getSomaElement();
PhysicalSphere sphere = soma.getPhysicalSphere();
if (i == 0) {
cell.setNeuroMLType(Cell.InhibitoryCell);
} else {
cell.setNeuroMLType(Cell.ExcitatoryCell);
}
sphere.setColor(c);
sphere.setAdherence(100);
int nbOfNeurites =
minNbOfNeurites + ((int) ((maxNbOfNeurites - minNbOfNeurites) * ECM.getRandomDouble()));
for (int j = 0; j < nbOfNeurites; j++) {
double angleOfAxon = pi * 2 * ECM.getRandomDouble();
double growthSpeed = 75;
double probaToBranch = 0.003;
double linearDiameterDecrease = 0.001;
NeuriteElement ne;
if (j == 0) {
ne = cell.getSomaElement().extendNewNeurite(3.0, Math.PI * 0.5, angleOfAxon);
ne.setIsAnAxon(true);
growthSpeed = 150;
probaToBranch = 0.009;
linearDiameterDecrease = 0;
ne.getPhysicalCylinder().setDiameter(1.5);
} else if (j == 1) {
ne =
cell.getSomaElement()
.extendNewNeurite(
3.0, Math.PI * 0.5, angleOfAxon + Math.PI - 0.5 + ECM.getRandomDouble());
ne.setIsAnAxon(false);
} else {
ne =
cell.getSomaElement()
.extendNewNeurite(3.0, Math.PI * 0.5, Math.PI * 2 * ECM.getRandomDouble());
ne.setIsAnAxon(false);
}
X_Bifurcation_Module br = new X_Bifurcation_Module();
br.shift = probaToBranch;
ne.addLocalBiologyModule(br);
X_Movement_Module mr = new X_Movement_Module();
mr.setRandomness(0.7);
mr.setSpeed(growthSpeed);
mr.setLinearDiameterDecrease(linearDiameterDecrease);
ne.addLocalBiologyModule(mr);
}
}
for (int i = 0; i < 350; i++) { // 350
Scheduler.simulateOneStep();
}
TestSynapses.extendExcressencesAndSynapseOnEveryNeuriteElement(0.4);
Exporter.saveExport();
}