}                                           // private constructor for singleton pattern

        /// <summary>
        /// See http://www.dotnumerics.com/NumericalLibraries/LinearAlgebra/CSharpCodeFiles/dgeev.aspx
        /// </summary>
        public void Dgeev(string jobVl, string jobVr, int n, ref double[] a, int offsetA, int ldA, ref double[] wr, int offsetWr,
                          ref double[] wi, int offsetWi, ref double[] vl, int offsetVl, int ldVl, ref double[] vr, int offsetVr, int ldVr,
                          ref double[] work, int offsetWork, int lWork, ref int info)
        {
            dgeev.Run(jobVl, jobVr, n, ref a, offsetA, ldA, ref wr, offsetWr, ref wi, offsetWi, ref vl, offsetVl, ldVl,
                      ref vr, offsetVr, ldVr, ref work, offsetWork, lWork, ref info);
        }
Exemple #2
0
        /// <summary>
        /// Computes the eigenvalues for an N-by-N real nonsymmetric matrix A.
        /// </summary>
        /// <param name="A">N-by-N real nonsymmetric matrix A.</param>
        /// <returns>The eigenvalues.</returns>
        public ComplexMatrix GetEigenvalues(Matrix A)
        {
            if (this._dgeev == null)
            {
                this._dgeev = new DGEEV();
            }

            this.CheckDimensions(A);


            Matrix ACopy = A.Clone();

            double[] ACopyData    = ACopy.Data;
            Matrix   RealEVectors = new Matrix(1, 1);

            double[]      EigenVectsData = RealEVectors.Data;
            ComplexMatrix EigenVals      = new ComplexMatrix(A.RowCount, 1);

            double[] REigVal = new double[A.RowCount];
            double[] IEigVal = new double[A.RowCount];

            //double[] EigenValsData = EigenVals.Data;
            int Info = 0;

            double[] VL = new double[A.RowCount];

            double[] Work  = new double[1];
            int      LWork = -1;

            //Calculamos LWORK
            _dgeev.Run("N", "N", A.RowCount, ref ACopyData, 0, ACopy.RowCount, ref REigVal, 0, ref IEigVal, 0, ref VL, 0, 1, ref EigenVectsData, 0, A.RowCount, ref Work, 0, LWork, ref Info);

            LWork = Convert.ToInt32(Work[0]);
            if (LWork > 0)
            {
                Work = new double[LWork];
                _dgeev.Run("N", "N", A.RowCount, ref ACopyData, 0, ACopy.RowCount, ref REigVal, 0, ref IEigVal, 0, ref VL, 0, 1, ref EigenVectsData, 0, A.RowCount, ref Work, 0, LWork, ref Info);
            }
            else
            {
                //Error
            }


            #region Error
            //= 0:  successful exit
            //.LT. 0:  if INFO = -i, the i-th argument had an illegal value.
            //.GT. 0:  if INFO = i, the QR algorithm failed to compute all the
            // eigenvalues, and no eigenvectors have been computed;
            // elements i+1:N of WR and WI contain eigenvalues which
            // have converged.

            if (Info < 0)
            {
                string infoSTg = Math.Abs(Info).ToString();
                throw new ArgumentException("the " + infoSTg + " -th argument had an illegal value");
            }
            else if (Info > 0)
            {
                string infoSTg = Math.Abs(Info).ToString();
                throw new Exception("The QR algorithm failed to compute all the eigenvalues.");
            }

            #endregion


            for (int i = 0; i < EigenVals.RowCount; i++)
            {
                EigenVals[i, 0] = new Complex(REigVal[i], IEigVal[i]);
            }


            return(EigenVals);
        }