Ops.mcnode: Operations on mcnode Objects

Description

This function alters the way operations are performed on mcnode objects for a better consistancy of the theory.

Usage

"Ops"(e1, e2)

Arguments

An mcnode object, a vector or an array.

An optionnal mcnode object, a vector or a matrix with at least one of both objects as an mcnode.

Value

The results as a mcnode object.

Details

This method will be used for any of the Group Ops functions.

The rules are as following (illustrated with a + function and ignoring the nvariates dimension):

0 + 0 = 0;
0 + V = V: classical recycling of the scalar;
0 + U = U: classical recycling of the scalar;
0 + VU = VU: classical recycling of the scalar;
V + V = V: if both of the same (nsv) dimension;
V + U = VU: the U object will be recycled "by row". The V object will be recycled classically "by column";
V + VU = VU: if the dimension of the V is (nsv) and the dimension of the VU is (nsv x nsu). The V object will be recycled classically "by column";
U + U = U: if both of the same (nsu) dimension;
U + VU = VU: if the dimension of the U is (nsu) and the dimension of the VU is (nsv x nsu). The U object will be recycled "by row";
VU + VU = VU: if the dimension of the VU nodes is (nsu x nsv);

A vector or an array may be combined with an mcnode of size (nsv x nsu) if an mcnode of this dimension may be built from this vector/array using the mcdata function. See mcdata for the rules.

The outm attribute is transferred as following: each + each = each; none + other = other; other1 + other2 = other1. The outm attribute of the resulting node may be changed using the outm function.

For multivariate nodes, a recycling on the nvariates dimension is done if a (nsu x nsv x nvariates) node is combined with a (nsu x nsv x 1) node.

Examples

Run this code

oldvar <- ndvar()
oldunc <- ndunc()
ndvar(30)
ndunc(20)

## Given
x0 <- mcdata(3, type="0")
xV <- mcdata(1:ndvar(), type="V")
xU <- mcdata(1:ndunc(), type="U")
xVU <- mcdata(1:(ndunc()*ndvar()), type="VU")
x0M <- mcdata(c(5, 10), type="0", nvariates=2)
xVM <- mcdata(1:(2*ndvar()), type="V", nvariates=2)
xUM <- mcdata(1:(2*ndunc()), type="U", nvariates=2)
xVUM <- mcdata(1:(2*(ndunc()*ndvar())), type="VU", nvariates=2)

## All possible combinations
## "0"
-x0
x0 + 3

## "V"
-xV
3 + xV
xV * (1:ndvar())
xV * x0
xV - xV

## "U"
-xU
xU + 3
(1:ndunc()) * xU
xU * x0
xU - xU

## Watch out the resulting type
xV + xU
xU + xV

## "VU"
-xVU
3 + xVU
(1:(ndunc()*ndvar())) * xVU
xVU + xV
x0 + xVU
xU + xVU
xVU - xVU

## Some Multivariates
x0M+3
xVM * (1:ndvar())
xVM - xV
xUM - xU
xVUM - xU