Hi, I was wanting to get the diagonal of an openmx output matrix and tried "diag()" as shown below with the matrix.

Question: should (can?) we overload "standard" R functions, or is there to be an mxDiag() equivalent?

If the latter, it would be nice if where possible it worked (to parameters) as the {base} library functions do.

I guess that it would be VERY helpful if code like

a = mxRun(factorModel) round(diag(a$S), 2) # worked, i.e, output a matrix rounded to 2 decimal places

<

pre>

> diag(a$S)

Error in y[1L + 0L:(m - 1L) * (n + 1L)] <- x :

incompatible types (from S4 to double) in subassignment type fix

> a$S

SymmMatrix 'S'

Labels matrix: No labels assigned.

Values matrix:

[,1] [,2] [,3] [,4] [,5] [,6]

[1,] 0.04081422 0.00000000 0.0000000 0.00000000 0.00000000 0

[2,] 0.00000000 0.03802001 0.0000000 0.00000000 0.00000000 0

[3,] 0.00000000 0.00000000 0.0408272 0.00000000 0.00000000 0

[4,] 0.00000000 0.00000000 0.0000000 0.03938708 0.00000000 0

[5,] 0.00000000 0.00000000 0.0000000 0.00000000 0.03628711 0

[6,] 0.00000000 0.00000000 0.0000000 0.00000000 0.00000000 1

Hi Tim,

The recommended way to do this is to use the mxEvaluate() function. In this fashion, we do not have to rewrite our own version of all the matrix operations.

factorModelOut <- mxRun(factorModel)

mxEvaluate(diag(S), factorModelOut)

Ha, in r705 I just committed the overload of diag. I guess that's a good point though. But how many functions would we really need to overload?

EDIT: removed it in 707.

Thanks for removing the diag() overloading. IMO the greater argument against overloading the matrix operations is that it is restrictive to assume that matrix functions on MxObjects always occur on the values sub-matrix. I've overloaded a few functions that return the same value across all the submatrices, such as nrow() and ncol(). But if we want to operate on the value submatrix, mxEvaluate() is the way to go.

I understand your point, although I'm not sure I fully agree. We can talk about this tomorrow though. :) 10 AM.

I agree with Michael on this. mxEvaluate() the recommended way to do this.

This is a small point, but one to get right early on, I think.

It didn't occurred to me to use mxEvaluate() to do this, mostly because, unlike matrix, there is nothing in R called "evaluate", so mxEvaluate is not analogous to an existing function with that name.

What it seems to be analogous, to is with()

So I'd like to suggest:

It easier to read and easier to stumble across and remember

Actually, eval() is there.

We could rename to mxEval(). I am not sure why the longer name was chosen.

Ahh: then I vote the mx function be called mxEval() by analogy