Exemplo n.º 1
0
        /// <summary>
        /// Solves a system of linear equations, <b>AX = B</b>, with A Cholesky factorized.
        /// </summary>
        /// <param name="input">The right hand side <see cref="Matrix{T}"/>, <b>B</b>.</param>
        /// <param name="result">The left hand side <see cref="Matrix{T}"/>, <b>X</b>.</param>
        public override void Solve(Matrix <Complex> input, Matrix <Complex> result)
        {
            if (input == null)
            {
                throw new ArgumentNullException("input");
            }

            if (result == null)
            {
                throw new ArgumentNullException("result");
            }

            // Check for proper dimensions.
            if (result.RowCount != input.RowCount)
            {
                throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
            }

            if (result.ColumnCount != input.ColumnCount)
            {
                throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
            }

            if (input.RowCount != CholeskyFactor.RowCount)
            {
                throw Matrix.DimensionsDontMatch <ArgumentException>(input, CholeskyFactor);
            }

            input.CopyTo(result);
            var order = CholeskyFactor.RowCount;

            for (var c = 0; c < result.ColumnCount; c++)
            {
                // Solve L*Y = B;
                Complex sum;
                for (var i = 0; i < order; i++)
                {
                    sum = result.At(i, c);
                    for (var k = i - 1; k >= 0; k--)
                    {
                        sum -= CholeskyFactor.At(i, k) * result.At(k, c);
                    }

                    result.At(i, c, sum / CholeskyFactor.At(i, i));
                }

                // Solve L'*X = Y;
                for (var i = order - 1; i >= 0; i--)
                {
                    sum = result.At(i, c);
                    for (var k = i + 1; k < order; k++)
                    {
                        sum -= CholeskyFactor.At(k, i).Conjugate() * result.At(k, c);
                    }

                    result.At(i, c, sum / CholeskyFactor.At(i, i));
                }
            }
        }
Exemplo n.º 2
0
        /// <summary>
        /// Solves a system of linear equations, <b>Ax = b</b>, with A Cholesky factorized.
        /// </summary>
        /// <param name="input">The right hand side vector, <b>b</b>.</param>
        /// <param name="result">The left hand side <see cref="Matrix{T}"/>, <b>x</b>.</param>
        public override void Solve(Vector <Complex> input, Vector <Complex> result)
        {
            // Check for proper arguments.
            if (input == null)
            {
                throw new ArgumentNullException("input");
            }

            if (result == null)
            {
                throw new ArgumentNullException("result");
            }

            // Check for proper dimensions.
            if (input.Count != result.Count)
            {
                throw new ArgumentException(Resources.ArgumentVectorsSameLength);
            }

            if (input.Count != CholeskyFactor.RowCount)
            {
                throw Matrix.DimensionsDontMatch <ArgumentException>(input, CholeskyFactor);
            }

            input.CopyTo(result);
            var order = CholeskyFactor.RowCount;

            // Solve L*Y = B;
            Complex sum;

            for (var i = 0; i < order; i++)
            {
                sum = result[i];
                for (var k = i - 1; k >= 0; k--)
                {
                    sum -= CholeskyFactor.At(i, k) * result[k];
                }

                result[i] = sum / CholeskyFactor.At(i, i);
            }

            // Solve L'*X = Y;
            for (var i = order - 1; i >= 0; i--)
            {
                sum = result[i];
                for (var k = i + 1; k < order; k++)
                {
                    sum -= CholeskyFactor.At(k, i).Conjugate() * result[k];
                }

                result[i] = sum / CholeskyFactor.At(i, i);
            }
        }
Exemplo n.º 3
0
        /// <summary>
        /// Initializes a new instance of the <see cref="UserCholesky"/> class. This object will compute the
        /// Cholesky factorization when the constructor is called and cache it's factorization.
        /// </summary>
        /// <param name="matrix">The matrix to factor.</param>
        /// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
        /// <exception cref="ArgumentException">If <paramref name="matrix"/> is not a square matrix.</exception>
        /// <exception cref="ArgumentException">If <paramref name="matrix"/> is not positive definite.</exception>
        public UserCholesky(Matrix <Complex> matrix)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

            if (matrix.RowCount != matrix.ColumnCount)
            {
                throw new ArgumentException(Resources.ArgumentMatrixSquare);
            }

            // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
            CholeskyFactor = matrix.Clone();
            var tmpColumn = new Complex[CholeskyFactor.RowCount];

            // Main loop - along the diagonal
            for (var ij = 0; ij < CholeskyFactor.RowCount; ij++)
            {
                // "Pivot" element
                var tmpVal = CholeskyFactor.At(ij, ij);

                if (tmpVal.Real > 0.0)
                {
                    tmpVal = tmpVal.SquareRoot();
                    CholeskyFactor.At(ij, ij, tmpVal);
                    tmpColumn[ij] = tmpVal;

                    // Calculate multipliers and copy to local column
                    // Current column, below the diagonal
                    for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
                    {
                        CholeskyFactor.At(i, ij, CholeskyFactor.At(i, ij) / tmpVal);
                        tmpColumn[i] = CholeskyFactor.At(i, ij);
                    }

                    // Remaining columns, below the diagonal
                    DoCholeskyStep(CholeskyFactor, CholeskyFactor.RowCount, ij + 1, CholeskyFactor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
                }
                else
                {
                    throw new ArgumentException(Resources.ArgumentMatrixPositiveDefinite);
                }

                for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
                {
                    CholeskyFactor.At(ij, i, Complex.Zero);
                }
            }
        }