Meta.Numerics.Matrices Namespace

You can create matrices of real values using the RectangularMatrix and SquareMatrix classes, and vectors of real values using the ColumnVector and RowVector classes. Operator overloads are defined that allow you to perform allowed arithmetic operations, such as adding two vectors or matrices, or multiplying a vector by a scalar, vector, or matrix. Each type defines methods corresponding to common linear algebra operations, such as inversion (Inverse), finding eigenvalues and eigenvectors (Eigenvalues and Eigendecomposition), and decompositions (QRDecomposition and SingularValueDecomposition).

The fastest way to solve a linear system A x = b is to form the LUDecomposition of A and call Solve(IReadOnlyListDouble) with the right-hand-side b.

There are several additional matrix containers that support smaller storage requirements and faster operations for matrices with particular structures, such as DiagonalMatrix, TridiagonalMatrix, SymmetricMatrix, and SparseSquareMatrix.

Where possible, we quickly return new matrix objects that implement a new view of existing stored values, without copying or otherwise disturbing the original values. Examples include Transpose and Row(Int32). For read-only purposes, this is much faster and requires less memory that computing and storing new values. The returned matrix objects are, however, necessarily read-only. Whether an matrix object is read-only can be determined from IsReadOnly. If you want to modify a read-only matrix object, simply make a copy using the object's Copy method (e.g. Copy or Copy).