This function alters the way operations are performed on mcnode objects for a better consistancy of the theory.
1 2  ## S3 method for class 'mcnode'
Ops(e1, e2)

e1 
An mcnode object, a vector or an array. 
e2 
An optionnal mcnode object, a vector or a matrix with at least one of both objects as an mcnode. 
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.
The results as a mcnode object.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53  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

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