public ScenarioDescriptiveStatistics DescriptiveStatistics(TextWriter tw)
{
//Calculate the mean at each interval...
int TT = T + 1;
int D = NodesAt(0)[0].Value.Length;
double[,] M = new double[TT, D];
double[,] S = new double[TT, D];
for (int i = 0; i < TT; i++)
{
List <TreeNode> nodes = NodesAt(i);
double[] mean = Mean(nodes);
double[] std = Std(nodes);
for (int d = 0; d < D; d++)
{
M[i, d] = mean[d];
S[i, d] = std[d];
}
}
tw.WriteLine("Mean:");
for (int d = 0; d < D; d++)
{
for (int i = 0; i < TT; i++)
{
tw.Write(M[i, d].ToString() + "\t");
}
tw.WriteLine();
}
tw.WriteLine("Std:");
for (int d = 0; d < D; d++)
{
for (int i = 0; i < TT; i++)
{
tw.Write(S[i, d].ToString() + "\t");
}
tw.WriteLine();
}
ScenarioDescriptiveStatistics sds = new ScenarioDescriptiveStatistics();
sds.means = M;
sds.variances = S;
return(sds);
}
public static double Distance2(ScenarioDescriptiveStatistics d1, ScenarioDescriptiveStatistics d2)
{
int I = d1.variances.GetLength(0);
int D = d1.variances.GetLength(1);
double d = 0;
double norm = 0;
for (int i = 0; i < I; i++)
{
for (int c = 0; c < D; c++)
{
if (d1.variances[i, c] > 0)
{
d += Math.Pow((d1.variances[i, c] - d2.variances[i, c]) / d1.variances[i, c], 2);
norm += 1;
}
}
}
return(Math.Sqrt(d) / Math.Sqrt(norm));
}
public static double Distance3(ScenarioDescriptiveStatistics d1, ScenarioDescriptiveStatistics d2)
{
int I = d1.variances.GetLength(0);
int D = d1.variances.GetLength(1);
double maxd = 0;
for (int c = 0; c < D; c++)
{
double d = 0;
double norm = 0;
for (int i = 0; i < I; i++)
{
d += Math.Abs(d1.variances[i, c] - d2.variances[i, c]);
norm += Math.Abs(d1.variances[i, c]);
}
maxd = Math.Max(maxd, d / norm);
}
return(maxd);
}
public static double Distance1(ScenarioDescriptiveStatistics d1, ScenarioDescriptiveStatistics d2)
{
int I = d1.variances.GetLength(0);
int D = d1.variances.GetLength(1);
double d = 0;
double norm = 0;
for (int i = 0; i < I; i++)
{
double d0 = 0;
double norm0 = 0;
for (int c = 0; c < D; c++)
{
d0 += Math.Pow(d1.variances[i, c] - d2.variances[i, c], 2);
norm0 += Math.Pow(d1.variances[i, c], 2);
}
d += Math.Sqrt(d0);
norm += Math.Sqrt(norm0);
}
return(d / norm);
}