C# DenseMatrix.Clone方法代码示例

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseQR"/> class. This object will compute the
        /// QR factorization when the constructor is called and cache it's factorization.
        /// </summary>
        /// <param name="matrix">The matrix to factor.</param>
        /// <param name="method">The QR factorization method to use.</param>
        /// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
        /// <exception cref="ArgumentException">If <paramref name="matrix"/> row count is less then column count</exception>
        public static DenseQR Create(DenseMatrix matrix, QRMethod method = QRMethod.Full)
        {
            if (matrix.RowCount < matrix.ColumnCount)
            {
                throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
            }

            var tau = new float[Math.Min(matrix.RowCount, matrix.ColumnCount)];
            Matrix<float> q;
            Matrix<float> r;

            if (method == QRMethod.Full)
            {
                r = matrix.Clone();
                q = new DenseMatrix(matrix.RowCount);
                Control.LinearAlgebraProvider.QRFactor(((DenseMatrix) r).Values, matrix.RowCount, matrix.ColumnCount, ((DenseMatrix) q).Values, tau);
            }
            else
            {
                q = matrix.Clone();
                r = new DenseMatrix(matrix.ColumnCount);
                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix) q).Values, matrix.RowCount, matrix.ColumnCount, ((DenseMatrix) r).Values, tau);
            }

            return new DenseQR(q, r, method, tau);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseQR"/> class. This object will compute the
        /// QR factorization when the constructor is called and cache it's factorization.
        /// </summary>
        /// <param name="matrix">The matrix to factor.</param>
        /// <param name="method">The QR factorization method to use.</param>
        /// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
        /// <exception cref="ArgumentException">If <paramref name="matrix"/> row count is less then column count</exception>
        public DenseQR(DenseMatrix matrix, QRMethod method = QRMethod.Full)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

            if (matrix.RowCount < matrix.ColumnCount)
            {
                throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
            }

            Tau = new Complex32[Math.Min(matrix.RowCount, matrix.ColumnCount)];

            if (method == QRMethod.Full)
            {
                MatrixR = matrix.Clone();
                MatrixQ = new DenseMatrix(matrix.RowCount);
                Control.LinearAlgebraProvider.QRFactor(((DenseMatrix)MatrixR).Values, matrix.RowCount, matrix.ColumnCount,
                                                       ((DenseMatrix)MatrixQ).Values, Tau);
            }
            else
            {
                MatrixQ = matrix.Clone();
                MatrixR = new DenseMatrix(matrix.ColumnCount);
                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix)MatrixQ).Values, matrix.RowCount, matrix.ColumnCount,
                                                       ((DenseMatrix)MatrixR).Values, Tau);
            }
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseSvd"/> class. This object will compute the
        /// the singular value decomposition when the constructor is called and cache it's decomposition.
        /// </summary>
        /// <param name="matrix">The matrix to factor.</param>
        /// <param name="computeVectors">Compute the singular U and VT vectors or not.</param>
        /// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
        /// <exception cref="ArgumentException">If SVD algorithm failed to converge with matrix <paramref name="matrix"/>.</exception>
        public static DenseSvd Create(DenseMatrix matrix, bool computeVectors)
        {
            var nm = Math.Min(matrix.RowCount, matrix.ColumnCount);
            var s = new DenseVector(nm);
            var u = new DenseMatrix(matrix.RowCount);
            var vt = new DenseMatrix(matrix.ColumnCount);
            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix) matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, s.Values, u.Values, vt.Values);

            return new DenseSvd(s, u, vt, computeVectors);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseCholesky"/> 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 static DenseCholesky Create(DenseMatrix matrix)
        {
            if (matrix.RowCount != matrix.ColumnCount)
            {
                throw new ArgumentException(Resources.ArgumentMatrixSquare);
            }

            // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
            var factor = (DenseMatrix) matrix.Clone();
            Control.LinearAlgebraProvider.CholeskyFactor(factor.Values, factor.RowCount);
            return new DenseCholesky(factor);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseGramSchmidt"/> class. This object creates an unitary matrix 
        /// using the modified Gram-Schmidt method.
        /// </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"/> row count is less then column count</exception>
        /// <exception cref="ArgumentException">If <paramref name="matrix"/> is rank deficient</exception>
        public static DenseGramSchmidt Create(DenseMatrix matrix)
        {
            if (matrix.RowCount < matrix.ColumnCount)
            {
                throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
            }

            var q = (DenseMatrix)matrix.Clone();
            var r = new DenseMatrix(matrix.ColumnCount, matrix.ColumnCount);
            Factorize(q.Values, q.RowCount, q.ColumnCount, r.Values);

            return new DenseGramSchmidt(q, r);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseSvd"/> class. This object will compute the
        /// the singular value decomposition when the constructor is called and cache it's decomposition.
        /// </summary>
        /// <param name="matrix">The matrix to factor.</param>
        /// <param name="computeVectors">Compute the singular U and VT vectors or not.</param>
        /// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
        /// <exception cref="ArgumentException">If SVD algorithm failed to converge with matrix <paramref name="matrix"/>.</exception>
        public DenseSvd(DenseMatrix matrix, bool computeVectors)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

            ComputeVectors = computeVectors;
            var nm = Math.Min(matrix.RowCount, matrix.ColumnCount);
            VectorS = new DenseVector(nm);
            MatrixU = new DenseMatrix(matrix.RowCount);
            MatrixVT = new DenseMatrix(matrix.ColumnCount);
            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Data, matrix.RowCount, matrix.ColumnCount, ((DenseVector)VectorS).Data, ((DenseMatrix)MatrixU).Data, ((DenseMatrix)MatrixVT).Data);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseGramSchmidt"/> class. This object creates an orthogonal matrix 
        /// using the modified Gram-Schmidt method.
        /// </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"/> row count is less then column count</exception>
        /// <exception cref="ArgumentException">If <paramref name="matrix"/> is rank deficient</exception>
        public DenseGramSchmidt(DenseMatrix matrix)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

            if (matrix.RowCount < matrix.ColumnCount)
            {
                throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
            }

            MatrixQ = matrix.Clone();
            MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
            Factorize(((DenseMatrix)MatrixQ).Values, MatrixQ.RowCount, MatrixQ.ColumnCount, ((DenseMatrix)MatrixR).Values);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseGramSchmidt"/> class. This object creates an orthogonal matrix 
        /// using the modified Gram-Schmidt method.
        /// </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"/> row count is less then column count</exception>
        /// <exception cref="ArgumentException">If <paramref name="matrix"/> is rank deficient</exception>
        public DenseGramSchmidt(DenseMatrix matrix)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

            if (matrix.RowCount < matrix.ColumnCount)
            {
                throw new ArgumentException(Resources.ArgumentMatrixDimensions);
            }

            MatrixQ = matrix.Clone();
            MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
            Factorize(((DenseMatrix)MatrixQ).Data, MatrixQ.RowCount, MatrixQ.ColumnCount, ((DenseMatrix)MatrixR).Data);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseQR"/> class. This object will compute the
        /// QR 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>
        public DenseQR(DenseMatrix matrix)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

            if (matrix.RowCount < matrix.ColumnCount)
            {
                throw new ArgumentException(Resources.ArgumentMatrixDimensions);
            }

            MatrixR = matrix.Clone();
            MatrixQ = new DenseMatrix(matrix.RowCount);
            Control.LinearAlgebraProvider.QRFactor(((DenseMatrix)MatrixR).Data, matrix.RowCount, matrix.ColumnCount, ((DenseMatrix)MatrixQ).Data);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseCholesky"/> 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 DenseCholesky(DenseMatrix 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).
            var factor = (DenseMatrix)matrix.Clone();
            Control.LinearAlgebraProvider.CholeskyFactor(factor.Data, factor.RowCount);
            CholeskyFactor = factor;
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseQR"/> class. This object will compute the
        /// QR 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"/> row count is less then column count</exception>
        public DenseQR(DenseMatrix matrix)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

            if (matrix.RowCount < matrix.ColumnCount)
            {
                throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
            }

            MatrixR = matrix.Clone();
            MatrixQ = new DenseMatrix(matrix.RowCount);
            Tau = new Complex32[Math.Min(matrix.RowCount, matrix.ColumnCount)];
            Control.LinearAlgebraProvider.QRFactor(((DenseMatrix)MatrixR).Data, matrix.RowCount, matrix.ColumnCount, ((DenseMatrix)MatrixQ).Data, Tau);
        }

        /// <summary>
        /// Initializes a new instance of the <see cref="DenseLU"/> class. This object will compute the
        /// LU 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>
        public DenseLU(DenseMatrix matrix)
        {
            if (matrix == null)
            {
                throw new ArgumentNullException("matrix");
            }

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

            // Create an array for the pivot indices.
            Pivots = new int[matrix.RowCount];

            // Create a new matrix for the LU factors, then perform factorization (while overwriting).
            var factors = (DenseMatrix)matrix.Clone();
            Control.LinearAlgebraProvider.LUFactor(factors.Data, factors.RowCount, Pivots);
            Factors = factors;
        }