This class computes the Cholesky factorization of a n by n ComplexDoubleMatrix.

A Levinson solver for square Toeplitz systems of Complex type.

This class computes the LU factorization of a general n by n ComplexDoubleMatrix.

Defines a matrix of ComplexDoubles.

This class computes the QR factorization of a general m by n ComplexDoubleMatrix.

This class computes the SVD factorization of a general ComplexDoubleMatrix.

A Levinson solver for symmetric square Toeplitz systems of Complex type.

This class computes the Cholesky factorization of a n by n ComplexFloatMatrix.

A Levinson solver for square Toeplitz systems of ComplexFloat type.

This class computes the LU factorization of a general n by n ComplexFloatMatrix.

Defines a matrix of ComplexFloats.

This class computes the QR factorization of a general m by n ComplexFloatMatrix.

This class computes the SVD factorization of a general ComplexFloatMatrix.

A Levinson solver for symmetric square Toeplitz systems of ComplexFloat type.

Represents a band matrix in compact storage format (stored as a linear array).

This class computes the Cholesky factorization of a general n by n DoubleMatrix.

A Levinson solver for square Toeplitz systems of double type.

This class computes the LU factorization of a general n by n DoubleMatrix.

Defines a matrix of doubles.

Wraps a linear array to a read-write matrix. The linear array is in column-major order, i.e. the first elements of the linear array belong to the first column of the matrix (i.e. the row values change more quickly). The index of the linear array is calculated as index = row + column*NumberOfRows. This representation is used for instance by LAPACK, Fortran, Julia, MATLAB, Octave, Scilab, GLSL and HLSL.

Wraps a linear array to a read-write matrix. The array is in row-major order, i.e. the first elements of the linear array belong to the first row of the matrix (the column values change more quickly). The index of the linear array is calculated as index = column + row * NumberOfColumns. This representation is used for instance by C, C++, Mathematica, Pascal and Python.

This class computes the QR factorization of a general m by n DoubleMatrix.

This class computes the SVD factorization of a general DoubleMatrix.

A Levinson solver for symmetric square Toeplitz systems of double type.

Implementation of an algorithm that finds a vector x with all elements xi>=0 which minimizes |X*x-y|.

This class computes the Cholesky factorization of a general n by n FloatMatrix.

A Levinson solver for square Toeplitz systems of float type.

This class computes the LU factorization of a general n by n FloatMatrix.

Defines a matrix of floats.

This class computes the QR factorization of a general m by n FloatMatrix.

This class computes the SVD factorization of a general FloatMatrix.

A Levinson solver for symmetric square Toeplitz systems of float type.

Provides implementation of Gaussian elimination with partial pivoting

Extends IComplexDoubleMatrix in a way that another matrix of appropriate dimensions can be appended to the bottom of the matrix.

Extends IComplexFloatMatrix in a way that another matrix of appropriate dimensions can be appended to the bottom of the matrix.

IBottomExtensibleMatrix extends IMatrix in a way that another matrix of appropriate dimensions can be appended to the bottom of the matrix.

Cholesky Decomposition of a symmetric, positive definite matrix.

Represents the simplest form of a 2D matrix of Complex values, which is readable and writeable.

Interface for a readable and writeable vector of Complex values.

Represents the simplest form of a 2D matrix of ComplexFloat values, which is readable and writeable.

Interface for a readable and writeable vector of Complex values.

Determines the eigenvalues and eigenvectors of a real square matrix.

Extends IComplexDoubleMatrix in a way that another matrix of appropriate dimensions can be appended either to the right or to the bottom of the matrix.

Special vector to which another vector can be appended to.

Extends IComplexFloatMatrix in a way that another matrix of appropriate dimensions can be appended either to the right or to the bottom of the matrix.

Special vector to which another vector can be appended to.

IExtensibleMatrix extends IMatrix in a way that another matrix of appropriate dimensions can be appended either to the right or to the bottom of the matrix.

Extends IVector in a way that another vector can be appended at the end of this vector.

Interface to a solver for linear equations. The procedure can either be non-destructive (keeping the matrix and the vector b), or destructive (not keeping matrix m and vector b). The destructive solving process may be faster, since saving of the matrix and the vector is not required.

LU decomposition of a rectangular matrix.

Matrix provides the fundamental operations of numerical linear algebra.

IMatrix represents the simplest form of a 2D matrix, which is readable and writeable.

Designates that the matrix is represented as a linear array of values. The linear array is in column-major order, i.e. the first elements of the linear array belong to the first column of the matrix (i.e. the row values change more quickly). The index of the linear array is calculated as index = row + column*NumberOfRows. This representation is used for instance by Fortran, Julia, MATLAB, Octave, Scilab, GLSL and HLSL.

Designates that the matrix is represented as a linear array of values. The array is in row-major order, i.e. the first elements of the linear array belong to the first row of the matrix (the column values change more quickly). The index of the linear array is calculated as index = column + row*NumberOfColumns. This representation is used for instance by C, C++, Mathematica, Pascal and Python.

Vector of integer elements.

Interface to a sequence of elements with unknown length.

The exception is thrown when a singular matrix is passed a method not expecting one.

The exception is thrown when a singular matrix is passed a method not expecting one.

QR decomposition for a rectangular matrix.

Extends IComplexDoubleMatrix in a way that another matrix of appropriate dimensions can be appended to the right of the matrix.

Extends IComplexFloatMatrix in a way that another matrix of appropriate dimensions can be appended to the right of the matrix.

IRightExtensibleMatrix extends IMatrix in a way that another matrix of appropriate dimensions can be appended to the right of the matrix.

IROMatrix represents a read-only matrix of Complex values.

Interface for a read-only vector of Complex values.

IROMatrix represents a read-only matrix of ComplexFloat values.

Interface for a read-only vector of Complex values.

IROMatrix represents a read-only matrix of values.

Operations on matrices which do not change the matrix instance.

Interface for a read-only vector of values. The first valid index of this vector is 0, the last one in (IROVector.Length-1).

Singular Value Decomposition for a rectangular matrix.

Interface for a a readable and writeable vector vector of values.

This provides array math for a special case of matrices, so called jagged arrays.

JaggedArrayMatrix is a matrix implementation that is relatively easy to extend to the bottom, i.e. to append rows. It is horizontal oriented, i.e. the storage is as a number of horizontal vectors. Furthermore, as a compromise, it provides fully access to its underlying jagged array.

Represents errors that occur when using the dnA library.

Matrix provides the fundamental operations of numerical linear algebra.

Represents errors that occur when using the matrix classes.

Class MatrixMath provides common static methods for matrix manipulation and arithmetic in tow dimensions. Class MatrixMath provides common static methods for matrix manipulation and arithmetic in tow dimensions.

Very thin wrapper structure that wraps a column major order linear array, i.e. consecutive elements of the linear array belong most probably to the same column, to provide information on number of rows and columns. Attention: this is not LAPACK convention (!)).

Very thin wrapper structure around a jagged array just to provided number of rows and columns along with the array itself. The spine array is oriented vertically, thus access to the array is down by array[row][column].

Thin wrapper structure that wraps a row major order linear array, i.e. consecutive elements of the linear array belong most probably to the same row, to provide information on number of rows and columns. Attention: this is not LAPACK convention (!)). If using LAPACK, you need column major order (MatrixWrapperStructForColumnMajorOrderLinearArray).

Very thin wrapper structure around a jagged array just to provided number of rows and columns along with the array itself. The spine array is oriented vertically, i.e. the rows protruding to the right from the spine array. Access to the underlying array is done by array[row][column].

The exception is thrown when a none positive definite matrix is passed a method not expecting one.

The exception is thrown when a none square matrix is passed a method not expecting one.

Wraps a linear array to a read-only matrix. The linear array is in column-major order, i.e. the first elements of the linear array belong to the first column of the matrix (i.e. the row values change more quickly). The index of the linear array is calculated as index = row + column*NumberOfRows. This representation is used for instance by LAPACK, Fortran, Julia, MATLAB, Octave, Scilab, GLSL and HLSL.

Wraps a linear array to a read-only matrix. The array is in row-major order, i.e. the first elements of the linear array belong to the first row of the matrix (the column values change more quickly). The index of the linear array is calculated as index = column + row*NumberOfColumns. This representation is used for instance by C, C++, Mathematica, Pascal and Python.

The exception is thrown when a singular matrix is passed a method not expecting one.

Sparse matrix class

VectorMath provides common static functions concerning vectors.

Statistics of the spacing between adjacent vector elements. The spaces are defined in the forward direction, i.e. as vec[i+1]-vec[i].

Designates the mode for enumeration and mapping of matrix elements.