static void Main(string[] args)
{
grid_x = 10;
grid_y = 10;
Stopwatch sw = new Stopwatch();
sw.Start();
FileOperations.Read(@"..\..\..\Datasets\emlak-veri.csv");
Console.WriteLine("Running SOM...");
SOM.Run(grid_x, grid_y, 500 * (grid_x * grid_y), 0.1, (grid_x + grid_y) / 2);
sw.Stop();
FileOperations.Write("output_weights.txt");
Console.WriteLine("Total time: " + sw.Elapsed);
Application.EnableVisualStyles();
Application.Run(new Visualize());
}
public double[,] CreateHeatMapForSOM()//Creates heatmap with creating u-matrix
{
List <List <int> > neighbours = new List <List <int> >();
for (int i = 0; i < Program.neuron_locs.Count; i++)//find neighbours of each neuron
{
List <int> temp = new List <int>();
for (int j = 0; j < Program.neuron_locs.Count; j++)
{
if (i != j && SOM.EuclideanDistance(Program.neuron_locs[i], Program.neuron_locs[j]) <= 2)
{
temp.Add(j);
}
}
neighbours.Add(temp);
}
double[,] heat_map = new double[2 * Program.grid_x - 1, 2 * Program.grid_y - 1];
for (int i = 0; i < Program.neuron_locs.Count; i++)// fill cells between neurons with distances
{
for (int j = 0; j < neighbours[i].Count; j++)
{
if (Program.neuron_locs[i][0] == Program.neuron_locs[neighbours[i][j]][0]) //if they are in same x axis
{
if (Program.neuron_locs[neighbours[i][j]][1] < Program.neuron_locs[i][1]) //left-side check
{
if (heat_map[Convert.ToInt32(Program.neuron_locs[i][0]), Convert.ToInt32(Program.neuron_locs[i][1])] == 0)
{
heat_map[Convert.ToInt32(Program.neuron_locs[i][0]), Convert.ToInt32(Program.neuron_locs[i][1]) - 1] = SOM.EuclideanDistance(Program.weights[i], Program.weights[neighbours[i][j]]);
}
}
else if (Program.neuron_locs[neighbours[i][j]][1] > Program.neuron_locs[i][1])//right-side check
{
if (heat_map[Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][0]), Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][1])] == 0)
{
heat_map[Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][0]), Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][1]) - 1] = SOM.EuclideanDistance(Program.weights[i], Program.weights[neighbours[i][j]]);
}
}
}
else//if they are in same y axis
{
if (Program.neuron_locs[neighbours[i][j]][0] < Program.neuron_locs[i][0])//up-side check
{
if (heat_map[Convert.ToInt32(Program.neuron_locs[i][0]), Convert.ToInt32(Program.neuron_locs[i][1])] == 0)
{
heat_map[Convert.ToInt32(Program.neuron_locs[i][0]) - 1, Convert.ToInt32(Program.neuron_locs[i][1])] = SOM.EuclideanDistance(Program.weights[i], Program.weights[neighbours[i][j]]);
}
}
else if (Program.neuron_locs[neighbours[i][j]][0] > Program.neuron_locs[i][0])//down-side check
{
if (heat_map[Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][0]), Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][1])] == 0)
{
heat_map[Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][0]) - 1, Convert.ToInt32(Program.neuron_locs[neighbours[i][j]][1])] = SOM.EuclideanDistance(Program.weights[i], Program.weights[neighbours[i][j]]);
}
}
}
}
}
for (int i = 0; i < 2 * Program.grid_x - 1; i++)//fills neuron cells with surrounded cell averages
{
for (int j = 0; j < 2 * Program.grid_y - 1; j++)
{
if (heat_map[i, j] == 0)
{
double sum = 0;
int count = 0;
if (j - 1 >= 0)
{
sum += heat_map[i, j - 1];
count++;
}
if (i - 1 >= 0)
{
sum += heat_map[i - 1, j];
count++;
}
if (i + 1 <= 2 * Program.grid_x - 2)
{
sum += heat_map[i + 1, j];
count++;
}
if (j + 1 <= 2 * Program.grid_y - 2)
{
sum += heat_map[i, j + 1];
count++;
}
heat_map[i, j] = sum / count;
}
}
}
for (int i = 0; i < 2 * Program.grid_x - 1; i++)
{
for (int j = 0; j < 2 * Program.grid_y - 1; j++)
{
if (heat_map[i, j] < Min_Value)
{
Min_Value = heat_map[i, j];
}
if (heat_map[i, j] > Max_Value)
{
Max_Value = heat_map[i, j];
}
}
}
return(heat_map);
}
