Dictionary <string, MMNode> createModels(List <MMNodeFactory.Model> modelsToTrain)
{
Dictionary <string, MMNode> models = new Dictionary <string, MMNode>();
int neuronsCount = 50;
//for (int neuronsCount = 10; neuronsCount < 100; neuronsCount += 20)
{
foreach (MMNodeFactory.Model selectedModel in modelsToTrain)
{
//Create the model
//MNNodeFactory.Model selectedModel;
//Enum.TryParse<MNNodeFactory.Model>(uncastedMdl.ToString(), out selectedModel);
models[selectedModel.ToString() + "_" + neuronsCount] = MMNodeFactory.obtain(selectedModel, neuronsCount);
MMNode network = models[selectedModel.ToString() + "_" + neuronsCount];
network.onEpoch += network_onEpoch;
//network.addModality( new Signal(2,1), "XY-t0");
//network.addModality( new Signal(2,1), "XY-t1");
network.addModality(new Signal(retinaSize * 4, retinaSize), "Vision-t0-Color");
network.addModality(new Signal(retinaSize * 2, retinaSize), "Vision-t0-Orientation");
//network.addModality(new Signal(retinaSize * 4, retinaSize), "Vision-t0-Shape");
network.addModality(new Signal(4, 1), "Saccade");
network.addModality(new Signal(retinaSize * 4, retinaSize), "Vision-t1-Color");
network.addModality(new Signal(retinaSize * 2, retinaSize), "Vision-t1-Orientation");
//network.addModality(new Signal(retinaSize * 4, retinaSize), "Vision-t1-Shape");
//Apply a treshold function on the modalities
network.onDivergence += network_onDivergence;
}
}
return(models);
}
//Thread
//public Thread mainLoopThread;
public ModalPx()
{
InitializeComponent();
//Generate the world
world = new World(worldWidth, worldHeight, shapeCount, orientationVariability);
world.Randomize(seedsNumber);
getWorldVisualization();
//Generate the network
//1-Areas
CA3 = MMNodeFactory.obtain(modelUsed);
//2-Inputs
LEC_Color = new Signal[retinaSize, retinaSize];
for (int i = 0; i < retinaSize; i++)
{
for (int j = 0; j < retinaSize; j++)
{
LEC_Color[i, j] = new CDZNET.Core.Signal(4, 1);
CA3.addModality(LEC_Color[i, j], "Color_" + i + "_" + j);
}
}
//Gui purpose
ctrlCA3.attach(CA3);
}
//Thread
//public Thread mainLoopThread;
public MainWindow()
{
InitializeComponent();
//Generate the world
world = new World(worldWidth, worldHeight, shapeCount, orientationVariability);
world.Randomize(seedsNumber);
getWorldVisualization();
//Generate the network
//1-Inputs
LEC_Color = new CDZNET.Core.Signal(retinaSize * 4, retinaSize); //Visual matrix (RED=0001 / BLUE=0010 / GREEN=0100 / YELLOW=1000)
LEC_Orientation = new CDZNET.Core.Signal(retinaSize * 2, retinaSize); //Visual matrix (an orientation is encoded on 2 bits)
LEC_Shape = new CDZNET.Core.Signal(retinaSize, retinaSize); //Visual matrix
MEC = new CDZNET.Core.Signal(worldWidth + worldHeight, 1); //Proprioception/Grid Cells
//2-Areas
CA3 = MMNodeFactory.obtain(modelUsed);
//Define which signal will enter CA3
CA3.addModality(LEC_Color, "Color");
CA3.addModality(LEC_Orientation, "Orientation");
//CA3.addModality(LEC_Shape, "Shape");
CA3.addModality(MEC, "XY");
//Gui purpose
ctrlCA3.attach(CA3);
//mainLoopThread = new Thread(mainLoop);
//mainLoopThread.Start();
}
//Thread
//public Thread mainLoopThread;
public Saccades()
{
InitializeComponent();
//Generate the world
world = new World(worldWidth, worldHeight, shapeCount, orientationVariability);
world.Randomize(seedsNumber);
getWorldVisualization();
//Generate the network
//1-Inputs
LEC_ColorT0 = new CDZNET.Core.Signal(retinaSize * 4, retinaSize); //Visual matrix (RED=0001 / BLUE=0010 / GREEN=0100 / YELLOW=1000)
LEC_ColorT1 = new CDZNET.Core.Signal(retinaSize * 4, retinaSize); //Visual matrix (RED=0001 / BLUE=0010 / GREEN=0100 / YELLOW=1000)
MEC = new CDZNET.Core.Signal(4, 1);
//dX dY
//Right = 0 1 0 0
//Left = 1 0 0 0
//Up = 0 0 0 1
//Down = 0 0 1 0
//2-Areas
CA3 = MMNodeFactory.obtain(modelUsed);
//Define which signal will enter CA3
CA3.addModality(LEC_ColorT0, "ColorT0");
CA3.addModality(LEC_ColorT1, "ColorT1");
//CA3.addModality(LEC_Shape, "Shape");
CA3.addModality(MEC, "dXdY");
//Gui purpose
ctrlCA3.attach(CA3);
//mainLoopThread = new Thread(mainLoop);
//mainLoopThread.Start();
}
