public Matrix ReadNext(bool overwrite)
{
Matrix m = null;
switch (_type)
{
case Type.MatrixFile:
m = MatrixReader.ReadMatrixFromFile(_sourceFile, _networkId);
break;
case Type.VectorFile:
m = MatrixReader.ReadVectorFromFile(_sourceFile, _networkId);
break;
case Type.RandomDiagonal:
m = RandomMatrix.LoadDiagonal(_rows, true);
m.NetworkId = _networkId;
break;
case Type.RandomSymmetric:
m = RandomMatrix.LoadSymmetric(_rows, range, pmin, pmax);
m.NetworkId = _networkId;
break;
case Type.RandomNonSymmetric:
m = RandomMatrix.LoadNonSymmetric(_rows, range, pmin, pmax);
m.NetworkId = _networkId;
break;
case Type.RandomVector:
m = RandomMatrix.LoadVector(_rows);
m.NetworkId = _networkId;
break;
case Type.RandomWithProbRange:
m = RandomMatrix.LoadWithProbabilisticRange(_rows, _cols, _min, _max);
m.NetworkId = _networkId;
break;
case Type.NullFile:
return(null);
}
_networkId = m.NetworkId + 1;
if (!string.IsNullOrEmpty(_outputFile) && _type != Type.NullFile)
{
WriteMatrixToFile(m, _isdyadic, overwrite);
}
/*
* if (m.NetworkId < 1000)
* m.NetworkId = int.Parse("1" + m.NetworkId);
*/
//else
// m.NetworkId = int.Parse("2" + m.NetworkId);
//m.NetworkId = int.Parse("1" + m.NetworkId);
return(m);
}
public static Vector EigenvectorCentrality(Matrix m)
{
Vector v = RandomMatrix.LoadRealUnitVector(m.Rows);
v.Labels.CopyFrom(m.RowLabels);
int numIter = Math.Max(Constants.MinimumNumberOfConvergenceSteps, m.Rows);
while (numIter-- > 0)
{
v = m * v;
v.Normalize();
}
for (int i = 0; i < v.Size; ++i)
{
v[i] *= 100.0 * Math.Sqrt(2);
}
return(v);
}