public static double[] ComputeDistanceBiharmonic(int sourceVertex, Eigen eigens)
{
double[] biharmonicDistance = new double[eigens.EigenVectorSize];
for (int i = 0; i < biharmonicDistance.Length; i++)
{
biharmonicDistance[i] = 0;
}
for (int i = 1; i < eigens.Count; i++)
{
EigenPair pair = eigens.SortedEigens[i];
double eigenValue = pair.EigenValue;
List <double> eigenVector = pair.EigenVector;
for (int j = 0; j < eigenVector.Count; j++)
{
double orig = eigenVector[sourceVertex];
double y = eigenVector[j];
double res = orig - y;
biharmonicDistance[j] += (res * res) / ((eigenValue) * (eigenValue));
}
}
for (int i = 0; i < biharmonicDistance.Length; i++)
{
biharmonicDistance[i] = Math.Sqrt(biharmonicDistance[i]);
}
return(biharmonicDistance);
}
public static double[] ComputeDistanceDiffusion(int originVertexIndex,
double parameterT,
Eigen eigens)
{
double[] diffusionDistance = new double[eigens.EigenVectorSize];
for (int i = 0; i < diffusionDistance.Length; i++)
{
diffusionDistance[i] = 0;
}
double optParamterT = parameterT / (2 * eigens.GetEigenValue(1));
for (int i = 1; i < eigens.Count; i++)
{
EigenPair pair = eigens.SortedEigens[i];
double eigenValue = pair.EigenValue;
List <double> eigenVector = pair.EigenVector;
for (int j = 0; j < eigenVector.Count; j++)
{
double orig = eigenVector[originVertexIndex];
double y = eigenVector[j];
double res = orig - y;
diffusionDistance[j] += Math.Exp(-2 * optParamterT * eigenValue)
* (res * res);
}
}
for (int i = 0; i < diffusionDistance.Length; i++)
{
diffusionDistance[i] = Math.Sqrt(diffusionDistance[i]);
}
return(diffusionDistance);
}
public static double[] ComputeDistanceCommuteTime(int originVertexIndex,
Eigen eigens)
{
double[] diffusionDistance = new double[eigens.EigenVectorSize];
for (int i = 0; i < diffusionDistance.Length; i++)
{
diffusionDistance[i] = 0;
}
for (int i = 1; i < eigens.Count; i++)
{
EigenPair pair = eigens.SortedEigens[i];
double eigenValue = pair.EigenValue;
List <double> eigenVector = pair.EigenVector;
for (int j = 0; j < eigenVector.Count; j++)
{
double orig = eigenVector[originVertexIndex];
double y = eigenVector[j];
double res = orig - y;
diffusionDistance[j] += (1 / eigenValue) * (res * res);
}
}
for (int i = 0; i < diffusionDistance.Length; i++)
{
diffusionDistance[i] = Math.Sqrt(diffusionDistance[i]);
}
return(diffusionDistance);
}
public Eigen ReadEigen(string modelName)
{
string fileName = Path.GetFileNameWithoutExtension(modelName);
string path = GetPath() + fileName + ".eigens";
Eigen eigen = new Eigen();
List <EigenPair> list = new List <EigenPair>();
//Read File
using (StreamReader sr = new StreamReader(path))
{
String line = null;
List <double> currentVector = null;
while ((line = sr.ReadLine()) != null)
{
if (line != "" && line[0] == '#')
{
String[] tokens = line.Split(' ');
List <double> aVector = new List <double>();
currentVector = aVector;
EigenPair pair = new EigenPair(double.Parse(tokens[1]), aVector);
list.Add(pair);
}
else if (line != "")
{
double value = double.Parse(line);
currentVector.Add(value);
}
}
}
list.Sort();
eigen.SortedEigens = list.ToArray();
return(eigen);
}
public Eigen ComputeEigensByLib(SparseMatrixDouble sparse, double sigma, int count)
{
int[] pCol;
int[] iRow;
double[] Values;
int NNZ;
int m = sparse.RowCount;
sparse.ToCCS(out pCol, out iRow, out Values, out NNZ);
double[] ImagePart = new double[count];
double[] RealPart = new double[count];
double[] Vectors = new double[count * m];
fixed(int *ri = iRow, cp = pCol)
fixed(double *val = Values, vets = Vectors, imgPart = ImagePart, relPart = RealPart)
{
int result = ComputeEigenNoSymmetricShiftModeCRS(ri, cp, val, NNZ, m, count, sigma, relPart, imgPart, vets);
}
List <EigenPair> list = new List <EigenPair>();
for (int i = 0; i < count; i++)
{
double realPart = RealPart[i];
List <double> vector = new List <double>();
int startIndex = i * m;
int endIndex = i * m + m;
for (int j = startIndex; j < endIndex; j++)
{
double value = Vectors[j];
vector.Add(value);
}
EigenPair newPair = new EigenPair(realPart, vector);
list.Add(newPair);
}
list.Sort();
Eigen eigen = new Eigen();
eigen.SortedEigens = list.ToArray();
return(eigen);
}
public Eigen GetEigen(SparseMatrix sparse, int num)
{
OutPut(sparse, "L");
matlab.Execute(@"[EV,ED] = eigs(L," + num.ToString() + ",'sm') ");
double[,] eigVector = GetMatrix("EV");
double[,] eigValue = GetMatrix("ED");
int len = eigVector.GetLength(0);
List <EigenPair> list = new List <EigenPair>();
for (int i = 0; i < num; i++)
{
double realPart = eigValue[i, i];
List <double> vector = new List <double>();
for (int j = 0; j < len; j++)
{
double value = eigVector[j, i];
vector.Add(value);
}
EigenPair newPair = new EigenPair(realPart, vector);
list.Add(newPair);
}
list.Sort();
Eigen eigen = new Eigen();
eigen.SortedEigens = list.ToArray();
return(eigen);
}
