PowerEigenSolver.h

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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 of the largest absolute component
     u = c*v
\endverbatim
 
 
*/
bool RDKIT_EIGENSOLVERS_EXPORT powerEigenSolver(
    unsigned int numEig, DoubleSymmMatrix &mat, DoubleVector &eigenValues,
    DoubleMatrix *eigenVectors = nullptr, 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);
}
};  // namespace EigenSolvers
};  // namespace RDNumeric
 
#endif