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;
}
private void InitEigenValue(Eigen eigen)
{
this.dataGridViewEigenValue.Rows.Clear();
for (int i = 0; i < eigen.Count; i++)
{
this.dataGridViewEigenValue.Rows.Add(i.ToString(), eigen.GetEigenValue(i).ToString());
}
}
private void InitEigenValue(Eigen eigen)
{
this.dataGridViewEigenValue.Rows.Clear();
for (int i = 0; i < eigen.Count; i++)
{
this.dataGridViewEigenValue.Rows.Add(i.ToString(), eigen.GetEigenValue(i).ToString());
}
}
public Eigen ComputeEigensByLib(SparseMatrix sparse, int count)
{
SparseMatrixDouble ds = new SparseMatrixDouble(sparse);
Eigen eigen = ComputeEigensByLib(ds, 0.0, count);
return(eigen);
}
private void dumpButton_Click(object sender, EventArgs e)
{
EnumLaplaceMatrix type = (EnumLaplaceMatrix)this.comboBoxLaplaceType.SelectedItem;
int count = int.Parse(textBoxEigenNumber.Text);
eigen = EigenManager.Instance.ComputeEigen(Mesh, type, count);
InitEigenValue(eigen);
}
private void dumpButton_Click(object sender, EventArgs e)
{
EnumLaplaceMatrix type = (EnumLaplaceMatrix)this.comboBoxLaplaceType.SelectedItem;
int count = int.Parse(textBoxEigenNumber.Text);
eigen=EigenManager.Instance.ComputeEigen(Mesh, type, count);
InitEigenValue(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);
}
private void InitEigenVector(Eigen eigen, int index)
{
this.dataGridViewEigenVector.Rows.Clear();
double[] vector = eigen.GetEigenVector(index).ToArray();
for (int i = 0; i < vector.Length; i++)
{
this.dataGridViewEigenVector.Rows.Add(i.ToString(), vector[i].ToString());
}
}
private void InitEigenVector(Eigen eigen,int index)
{
this.dataGridViewEigenVector.Rows.Clear();
double[] vector = eigen.GetEigenVector(index).ToArray();
for (int i = 0; i < vector.Length ; i++)
{
this.dataGridViewEigenVector.Rows.Add(i.ToString(), vector[i].ToString());
}
}
public double[] ColorEigenVector(TriMesh mesh, int index)
{
if (eigen == null)
{
eigen = EigenManager.Instance.ComputeEigen(mesh, eigenCount);
}
if (eigenIndex > eigenCount)
{
eigen = EigenManager.Instance.ComputeEigen(mesh, eigenCount);
}
return(eigen.GetEigenVector(eigenIndex).ToArray());
}
public double[] ColorEigenVector(TriMesh mesh, int index)
{
if (eigen == null)
{
eigen = EigenManager.Instance.ComputeEigen(mesh, eigenCount);
}
if (eigenIndex > eigenCount)
{
eigen = EigenManager.Instance.ComputeEigen(mesh, eigenCount);
}
return eigen.GetEigenVector(eigenIndex).ToArray();
}
public TriMesh Recon(TriMesh mesh, int reconNum)
{
Eigen eigen = EigenManager.Instance.ComputeEigen(mesh,
EnumLaplaceMatrix.LapalceCot, reconNum + 10);
List <double> X = TriMeshUtil.GetX(mesh);
List <double> Y = TriMeshUtil.GetY(mesh);
List <double> Z = TriMeshUtil.GetZ(mesh);
List <double> factorX = new List <double>(reconNum);
List <double> factorY = new List <double>(reconNum);
List <double> factorZ = new List <double>(reconNum);
for (int i = 0; i < reconNum; i++)
{
List <double> eigenVector = eigen.GetEigenVector(i);
double valueX = TriMeshUtil.Multiply(eigenVector, X);
double valueY = TriMeshUtil.Multiply(eigenVector, Y);
double valueZ = TriMeshUtil.Multiply(eigenVector, Z);
factorX.Add(valueX);
factorY.Add(valueY);
factorZ.Add(valueZ);
}
double[] reconX = new double[mesh.Vertices.Count];
double[] reconY = new double[mesh.Vertices.Count];
double[] reconZ = new double[mesh.Vertices.Count];
for (int i = 0; i < reconNum; i++)
{
List <double> eigenVector = eigen.GetEigenVector(i);
List <double> tempX = TriMeshUtil.Multiply(eigenVector, factorX[i]);
reconX = TriMeshUtil.Add(reconX, tempX);
List <double> tempY = TriMeshUtil.Multiply(eigenVector, factorY[i]);
reconY = TriMeshUtil.Add(reconY, tempY);
List <double> tempZ = TriMeshUtil.Multiply(eigenVector, factorZ[i]);
reconZ = TriMeshUtil.Add(reconZ, tempZ);
}
for (int i = 0; i < mesh.Vertices.Count; i++)
{
mesh.Vertices[i].Traits.Position.x = reconX[i];
mesh.Vertices[i].Traits.Position.y = reconY[i];
mesh.Vertices[i].Traits.Position.z = reconZ[i];
}
return(mesh);
}
public static double[] ComputeDistanceADF(TriMesh mesh, double parameterT, Eigen eigens)
{
double[] adfValues = new double[mesh.Vertices.Count];
for (int j = 1; j < eigens.Count; j++)
{
List <double> group = eigens.SortedEigens[j].EigenVector;
for (int i = 0; i < group.Count; i++)
{
adfValues[i] += Math.Exp(-parameterT * (eigens.SortedEigens[j].EigenValue / eigens.SortedEigens[1].EigenValue)) *
(group[i] * group[i]);
}
}
return(adfValues);
}
private void InitEigen(ToolStripMenuItem toolStrip, Eigen eigen)
{
toolStrip.DropDownItems.Clear();
int i = 0;
foreach (EigenPair pair in eigen.SortedEigens)
{
ToolStripMenuItem item = new ToolStripMenuItem();
item.Name = i.ToString() + "ToolStripMenuItem";
item.Text = i.ToString();
item.Tag = i;
item.Click += eigen_Click;
toolStrip.DropDownItems.Add(item);
i++;
}
}
private void InitEigen(ToolStripMenuItem toolStrip, Eigen eigen)
{
toolStrip.DropDownItems.Clear();
int i = 0;
foreach (EigenPair pair in eigen.SortedEigens)
{
ToolStripMenuItem item = new ToolStripMenuItem();
item.Name = i.ToString() + "ToolStripMenuItem";
item.Text = i.ToString();
item.Tag = i;
item.Click += eigen_Click;
toolStrip.DropDownItems.Add(item);
i++;
}
}
public static double[] ComputeEigenVector(TriMesh mesh, int i)
{
SparseMatrix matrix = null;
if (LaplaceManager.Instance.CurrentMatrix == null)
{
matrix = LaplaceManager.Instance.BuildMatrixCot(mesh);
}
else
{
matrix = LaplaceManager.Instance.CurrentMatrix;
}
Eigen eigen = EigenManager.Instance.ComputeEigen(matrix, "test", i + 2);
return(eigen.GetEigenVector(i).ToArray());;
}
public static double[] ComputeDistanceADF(TriMesh mesh, double parameterT, Eigen eigens)
{
double[] adfValues = new double[mesh.Vertices.Count];
for (int j = 1; j < eigens.Count; j++)
{
List<double> group = eigens.SortedEigens[j].EigenVector;
for (int i = 0; i < group.Count; i++)
{
adfValues[i] += Math.Exp(-parameterT * (eigens.SortedEigens[j].EigenValue / eigens.SortedEigens[1].EigenValue)) *
(group[i] * group[i]);
}
}
return adfValues;
}
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);
}
public static double[] ComputeEigenVector(Eigen eigen, int i)
{
return(eigen.GetEigenVector(i).ToArray());;
}
public static double[] ComputeEigenVector(SparseMatrix matrix, int i)
{
Eigen eigen = EigenManager.Instance.ComputeEigen(matrix, "test", i + 20);
return(eigen.GetEigenVector(i).ToArray());;
}
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;
}
public Eigen ComputeEigen(SparseMatrix matrix, string modelName, int count)
{
Eigen eigen = LinearSystem.Instance.ComputeEigen(matrix, count, modelName);
return(eigen);
}
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[] ComputeEigenVector(Eigen eigen, int i)
{
return eigen.GetEigenVector(i).ToArray(); ;
}
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;
}