/// <summary>
/// Learns a model that can map the given inputs to the given outputs by using (gradient free) optimization algorithm
/// </summary>
/// <param name="x">The model inputs.</param>
/// <param name="y">The desired outputs associated with each <paramref name="x">inputs</paramref>.</param>
/// <param name="gradientFreeSolver">The optimization solver<paramref name="gradientFreeSolver">inputs</paramref>.</param>
/// <returns>
/// A model that has learned how to produce <paramref name="y" /> given <paramref name="x" />.
/// </returns>
public NonlinearRegression Learn(Double[][] x, double[] y, BaseOptimizationMethod gradientFreeSolver)
{
NonlinearRegression problemFormulation = null;
Func <double[][], double[], double[], double> error = ErrorFunction;
var errorForInputAndOutput = error.Curry()(x)(y);
gradientFreeSolver.Function = errorForInputAndOutput;
gradientFreeSolver.NumberOfVariables = this.NumberOfParameters;
bool success = gradientFreeSolver.Minimize();
problemFormulation = new NonlinearRegression(gradientFreeSolver.NumberOfVariables, this.Function);
for (int idx = 0; idx < gradientFreeSolver.Solution.Length; idx++)
{
problemFormulation.Coefficients.SetValue(gradientFreeSolver.Solution[idx], idx);
}
return(problemFormulation);
}
public Network(double width, double height, ArrayList users, BaseOptimizationMethod mehod, Canvas canvas)
{
this.users = users;
this.mehod = mehod;
this.width = width;
this.height = height;
this.canvas = canvas;
this.lbp = new ArrayList();
this.ubp = new ArrayList();
this.InitialParameters = new ArrayList();
this.mehod.FitnessFunction = FitnessFunction;
this.mehod.GenerationCreated += ShowAntibodies;
X = (int)this.width / (R[R.Length - 1] * 2);
Y = (int)this.height / (R[R.Length - 1] * 2);
this.actualRegionindex = 0;
for (int i = 0; i < Y; i++)
{
for (int j = 0; j < X; j++)
{
int heightDown = i * (R[R.Length - 1] * 2);
int heightUp = (i + 1) * (R[R.Length - 1] * 2);
int widhtDown = j * (R[R.Length - 1] * 2);
int widhtUp = (j + 1) * (R[R.Length - 1] * 2);
List <User> regionUser = new List <User>();
foreach (Point user in this.users)
{
if (user.X >= widhtDown && user.X <= widhtUp && user.Y >= heightDown && user.Y <= heightUp)
{
regionUser.Add(new User()
{
position = user, isCover = false
});
}
}
Region region = new Region(actualRegionindex++, new Point(j, i), regionUser.ToArray(), 0, heightDown, heightUp, widhtDown, widhtUp);
region.Towers = new Tower[1];
int r = (int)(Math.Sqrt((R[R.Length - 1] * R[R.Length - 1]) + (R[R.Length - 1] * R[R.Length - 1])) / 2);
region.Towers[0] = new Tower(new Point(widhtDown + R[R.Length - 1], heightDown + R[R.Length - 1]), r * 2, regionUser.Count);
regions.Add(region);
}
}
this.actualRegionindex = 0;
List <int> neighbors;
foreach (Region region in this.regions)
{
neighbors = new List <int>();
foreach (Region neighbor in this.regions)
{
if (neighbor.pos.Y == region.pos.Y - 1)
{
if (neighbor.pos.X == region.pos.X - 1 || neighbor.pos.X == region.pos.X || neighbor.pos.X == region.pos.X + 1)
{
neighbors.Add(neighbor.id);
}
}
else
if (neighbor.pos.Y == region.pos.Y)
{
if (neighbor.pos.X == region.pos.X - 1 || neighbor.pos.X == region.pos.X + 1)
{
neighbors.Add(neighbor.id);
}
}
else
if (neighbor.pos.Y == region.pos.Y + 1)
{
if (neighbor.pos.X == region.pos.X - 1 || neighbor.pos.X == region.pos.X || neighbor.pos.X == region.pos.X + 1)
{
neighbors.Add(neighbor.id);
}
}
}
region.Neighbor = neighbors.ToArray();
}
}
