# 14 Matrix Calculations

A very powerful feature of REDUCE is the ease with which matrix calculations can be performed. To extend our syntax to this class of calculations we need to add another prefix operator, mat, and a further variable and expression type as follows:

## 14.1 MAT Operator

This prefix operator is used to represent n × m matrices. mat has n arguments interpreted as rows of the matrix, each of which is a list of m expressions representing elements in that row. For example, the matrix

julia> [:a :b :c; :d :e :f]
2×3 Array{Symbol,2}:
:a  :b  :c
:d  :e  :f

would be written as R"mat((a,b,c),(d,e,f))".

Note that the single column matrix

julia> [:x; :y]
2-element Array{Symbol,1}:
:x
:y

becomes R"mat((x),(y))". The inside parentheses are required to distinguish it from the single row matrix

julia> [:x :y]
1×2 Array{Symbol,2}:
:x  :y

that would be written as R"mat((x,y))".

## 14.2 Matrix Variables

An identifier may be declared a matrix variable by the declaration matrix. The size of the matrix may be declared explicitly in the matrix declaration, or by default in assigning such a variable to a matrix expression. For example,

julia> Algebra.matrix(:(x(2,1)),:(y(3,4)),:z)

declares x to be a 2 x 1 (column) matrix, y to be a 3 x 4 matrix and z a matrix whose size is to be declared later.

Matrix declarations can appear anywhere in a program. Once a symbol is declared to name a matrix, it can not also be used to name an array, operator or a procedure, or used as an ordinary variable. It can however be redeclared to be a matrix, and its size may be changed at that time. Note however that matrices once declared are global in scope, and so can then be referenced anywhere in the program. In other words, a declaration within a block (or a procedure) does not limit the scope of the matrix to that block, nor does the matrix go away on exiting the block (use clear instead for this purpose). An element of a matrix is referred to in the expected manner; thus x(1,1) gives the first element of the matrix x defined above. References to elements of a matrix whose size has not yet been declared leads to an error. All elements of a matrix whose size is declared are initialized to 0. As a result, a matrix element has an instant evaluation property and cannot stand for itself. If this is required, then an operator should be used to name the matrix elements as in:

julia> Algebra.matrix(:m); Algebra.operator(:x);  rcall("m := mat((x(1,1),x(1,2)))");

## 14.3 Matrix Expressions

These follow the normal rules of matrix algebra as defined by the following syntax:

⟨matrix expression⟩  ::=  MAT⟨matrix description⟩∣⟨matrix variable⟩∣
⟨scalar expression⟩*⟨matrix expression⟩∣
⟨matrix expression⟩*⟨matrix expression⟩∣
⟨matrix expression⟩+⟨matrix expression⟩∣
⟨matrix expression⟩^⟨integer⟩∣
⟨matrix expression⟩/⟨matrix expression⟩

Sums and products of matrix expressions must be of compatible size; otherwise an error will result during their evaluation. Similarly, only square matrices may be raised to a power. A negative power is computed as the inverse of the matrix raised to the corresponding positive power. a/b is interpreted as a*b^(-1).

Examples:

Assuming x and y have been declared as matrices, the following are matrix expressions

        y
y^2*x-3*y^(-2)*x
y + mat((1,a),(b,c))/2

The computation of the quotient of two matrices normally uses a two-step elimination method due to Bareiss. An alternative method using Cramer’s method is also available. This is usually less efficient than the Bareiss method unless the matrices are large and dense, although we have no solid statistics on this as yet. To use Cramer’s method instead, the switch cramer should be turned on.

## 14.4 Operators with Matrix Arguments

The operator length applied to a matrix returns a list of the number of rows and columns in the matrix. Other operators useful in matrix calculations are defined in the following subsections. Attention is also drawn to the LINALG (section 16.37) and NORMFORM (section 16.42) packages.

Reduce.Algebra.detFunction
det(exprn)

Syntax:

        det(EXPRN:matrix_expression):algebraic.

The operator det is used to represent the determinant of a square matrix expression. E.g.,

Algebra.det(:(y^2))

is a scalar expression whose value is the determinant of the square of the matrix y, and

Algebra.det([:a :b :c; :d :e :f; :g :h :j])

is a scalar expression whose value is the determinant of the matrix

3×3 Array{Symbol,2}:
:a  :b  :c
:d  :e  :f
:g  :h  :j

Determinant expressions have the instant evaluation property. In other words, the statement

        let det mat((a,b),(c,d)) = 2;

sets the value of the determinant to 2, and does not set up a rule for the determinant itself.

source
Missing docstring.

Missing docstring for Reduce.Algebra.mateigen. Check Documenter's build log for details.

Reduce.Algebra.tpFunction
tp(exprn)

Syntax:

        tp(EXPRN:matrix_expression):matrix.

This operator takes a single matrix argument and returns its transpose.

source
Reduce.Algebra.traceFunction
trace(exprn)

Syntax:

        TRACE(EXPRN:matrix_expression):algebraic.

The operator TRACE is used to represent the trace of a square matrix.

source
Missing docstring.

Missing docstring for Reduce.Algebra.cofactor. Check Documenter's build log for details.

Reduce.Algebra.nullspaceFunction
nullspace(exprn)

Syntax:

        NULLSPACE(EXPRN:matrix_expression):list

nullspace calculates for a matrix a a list of linear independent vectors (a basis) whose linear combinations satisfy the equation $Ax = 0$. The basis is provided in a form such that as many upper components as possible are isolated.

Note that with b := nullspace a the expression length b is the nullity of a, and that second length a - length b calculates the rank of a. The rank of a matrix expression can also be found more directly by the rank operator described below.

Example: The command

        nullspace mat((1,2,3,4),(5,6,7,8));

gives the output

        {
[ 1  ]
[ 0  ]
[ - 3]
[ 2  ]
,
[ 0  ]
[ 1  ]
[ - 2]
[ 1  ]
}

In addition to the REDUCE matrix form, nullspace accepts as input a matrix given as a list of lists, that is interpreted as a row matrix. If that form of input is chosen, the vectors in the result will be represented by lists as well. This additional input syntax facilitates the use of nullspace in applications different from classical linear algebra.

source
Reduce.Algebra.rankFunction
rank(exprn)

Syntax:

        RANK(EXPRN:matrix_expression):integer

rank calculates the rank of its argument, that, like nullspace can either be a standard matrix expression, or a list of lists, that can be interpreted either as a row matrix or a set of equations.

Example:

Algebra.rank([:a :b :c; :d :e :f])

returns the value 2.

source

## 14.5 Matrix Assignments

Matrix expressions may appear in the right-hand side of assignment statements. If the left-hand side of the assignment, which must be a variable, has not already been declared a matrix, it is declared by default to the size of the right-hand side. The variable is then set to the value of the right-hand side.

Such an assignment may be used very conveniently to find the solution of a set of linear equations. For example, to find the solution of the following set of equations

        a11*x(1) + a12*x(2) = y1
a21*x(1) + a22*x(2) = y2

we simply write

Algebra.:*(Algebra.inv([:a11 :a12; :a21 :a22]),[:y1,:y2])

## 14.6 Evaluating Matrix Elements

Once an element of a matrix has been assigned, it may be referred to in standard array element notation. Thus y(2,1) refers to the element in the second row and first column of the matrix y.