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//
// Copyright (C) 2004-2006 Rational Discovery LLC
//
// @@ All Rights Reserved @@
// This file is part of the RDKit.
// The contents are covered by the terms of the BSD license
// which is included in the file license.txt, found at the root
// of the RDKit source tree.
//
#include <RDGeneral/export.h>
#ifndef _RD_POWER_EIGENSOLVER_H
#define _RD_POWER_EIGENSOLVER_H
#include <Numerics/Vector.h>
#include <Numerics/Matrix.h>
#include <Numerics/SymmMatrix.h>
namespace RDNumeric {
namespace EigenSolvers {
//! Compute the \c numEig largest eigenvalues and, optionally, the
//corresponding
//! eigenvectors.
/*!
\param numEig the number of eigenvalues we are interested in
\param mat symmetric input matrix of dimension N*N
\param eigenValues Vector used to return the eigenvalues (size = numEig)
\param eigenVectors Optional matrix used to return the eigenvectors (size =
N*numEig)
\param seed Optional values to seed the random value generator used to
initialize the eigen vectors
\return a boolean indicating whether or not the calculation converged.
<b>Notes:</b>
- The matrix, \c mat, is changed in this function
<b>Algorithm:</b>
We use the iterative power method, which works like this:
\verbatim
u = arbitrary unit vector
tol = 0.001
currEigVal = 0.0;
prevEigVal = -1.0e100
while (abs(currEigVal - prevEigVal) > tol) :
v = Au
prevEigVal = currEigVal
currEigVal = v[i] // where i is the id os the largest absolute component
u = c*v
\endverbatim
*/
bool RDKIT_EIGENSOLVERS_EXPORT powerEigenSolver(unsigned int numEig, DoubleSymmMatrix &mat,
DoubleVector &eigenValues, DoubleMatrix *eigenVectors = 0,
int seed = -1);
//! \overload
static inline bool powerEigenSolver(unsigned int numEig, DoubleSymmMatrix &mat,
DoubleVector &eigenValues,
DoubleMatrix &eigenVectors, int seed = -1) {
return powerEigenSolver(numEig, mat, eigenValues, &eigenVectors, seed);
}
};
};
#endif
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