computer science

static void LoadGenes()

{

Random rand = new Random();

string rline;

string[] sline = new string[geneDim];

double[] dline;

int count = 0;

while ((rline = FileIn.ReadLine()) != null)

{

sline = rline.Split(' ');

dline = new double[sline.Length];

for(int i = 0; i<sline.Length; i++)

dline[i]= double.Parse(sline[i]);

List<double>data = new List<double>();

for (int j = 0; j < geneDim; j++)

{

data.Add(dline[j]);

}

GeneVector v = new GeneVector(data, count++);

GeneList.Add(v);

}

}

////////////////////////////////////////////////////////////////////////////

static void CreateSimilarityMatrix()

{

W = new double[numGenes, numGenes];

for(int i = 0; i< W.GetLength(0); i++)

{

for(int j = 0; j<W.GetLength (1); j++)

{

//use the affine similarity formula to assign W[i,j]

W[i, j] =

}

}

}

////////////////////////////////////////////////////////////////////////////

static void OutputSimilarityMatrix()

{

for (int i = 0; i < W.GetLength(0); i++)

{

for (int j = 0; j < W.GetLength(1); j++)

{

writer3.Write("{0} ", W[i, j].ToString("F2"));

}

writer3.WriteLine();

}

}