Problem with the `pdag2allDags` and `addBgKnowledge` functions on pcalg package

Question

I am starting to use the pcalg package, and I am having some doubts regarding the functions pdag2allDags and addBgKnowledge :

I am using the sample data gmG provided by the package

library(pcalg)
library(Rgraphviz)
data("gmG")
df<-gmG$x
suffStat <- list(C = cor(df), n = nrow(df))
fci.fit<-fci(suffStat, indepTest = gaussCItest, p = ncol(df),alpha = 0.01)
plot(fci.fit)

I would like to get the all equivalent DAGs. From documentation, it should work using the function pdag2allDags (from here ). We should need just to get the amat ( a djacent mat rix) data.

From the specifications on the documentation , I thought the following should work...

plotAllDags <- function(res) {
    require(graph)
    p <- sqrt(ncol(res$dags))
    nDags <- ceiling(sqrt(nrow(res$dags)))
    par(mfrow = c(nDags, nDags))
    for (i in 1:nrow(res$dags)) {
        tmp <- matrix(res$dags[i,],p,p)
        colnames(tmp) <- rownames(tmp) <- res$nodeNms
        plot(as(tmp, "graphNEL"))
    }
}

res1<-pdag2allDags(as(fci.fit,"amat"))
plotAllDags(res1)

But, instead, it returns:

Error in sqrt(ncol(res$dags)): non-numeric argument to mathematical function

We see also the amat in the fci' s object. So, I tried:

res2<-pdag2allDags(fci.fit@amat)
plotAllDags(res2)

It also returns the same:

Error in sqrt(ncol(res$dags)): non-numeric argument to mathematical function

But if I use the pc algorithm, it works:

pc.fit<-pc(suffStat, indepTest = gaussCItest, p = ncol(df),alpha = 0.01)
plot(pc.fit)
res0<-pdag2allDags(as(pc.fit,"amat"))
plotAllDags(res0)

What is going on? Is not pdag2allDags intended to deal with all amat objects (pc, fci, rfci, etc.)? I was not able to find any other ...allDags function in the documentation. How to get the all equivalent DAGs from the output of the fci function?

---

The same happens for the function addBgKnowledge . It works for pc :

pc.amat2<-addBgKnowledge(gInput = pc.fit@graph,x=1,y=2)
plot(pc.amat2)

but not for fci , even the documentation saying it uses an amat

fci.amat2<-addBgKnowledge(gInput = as(fci.fit,"amat"),x=1,y=2)
plot(as(t(fci.amat2),"graphNEL"))

It delivers:

Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': argument is not a matrix

Answer 1

I believe it should not be an ideal answer, it should have a better way to do it, but as I was not getting any answer, I have made some attempts, and I am sharing how I had circumvented the issue for now...

If we assess the structure, both are indeed dealing with adjacency matrix (amat)... but they are different... the pc output comprises a ' cpdag ' type amat , and fci output, a ' pag ' type amat ...

as(pc.fit,"amat")

we get:

Adjacency Matrix 'amat' (8 x 8) of type ‘cpdag’:
  1 2 3 4 5 6 7 8
1 . 1 . . . . . .
2 1 . 1 . 1 . . .
3 . 1 . . . . . .
4 . . . . . . . .
5 . 1 . . . . . .
6 1 . . . 1 . . .
7 . . . . . 1 . .
8 1 . . . 1 . . .

and with

as(fci.fit,"amat")

we get:

Adjacency Matrix 'amat' (8 x 8) of type ‘pag’:
  1 2 3 4 5 6 7 8
1 . 1 . . . 2 . 2
2 1 . 1 . 1 . . .
3 . 1 . . . . . .
4 . . . . . . . .
5 . 1 . . . 2 . 2
6 3 . . . 3 . 2 .
7 . . . . . 3 . .
8 3 . . . 3 . . .

or, with

fci.fit@amat

we get

  1 2 3 4 5 6 7 8
1 0 1 0 0 0 2 0 2
2 1 0 1 0 1 0 0 0
3 0 1 0 0 0 0 0 0
4 0 0 0 0 0 0 0 0
5 0 1 0 0 0 2 0 2
6 3 0 0 0 3 0 2 0
7 0 0 0 0 0 3 0 0
8 3 0 0 0 3 0 0 0

The pcalg documentation on pdag2allDags does not explicitly mention that...

• function definition says 'a Given Partially Directed Acyclic Graph (PDAG)'.
• the example shows an ' amat ' defined as matrix of zeros and ones, without any connection to fci or pc functions

But the solution I found starts with taking the ' pag ' type amat and converting it to ' cpdag '...

Well... the ' pag ' type amat indeed is not comprised just by zeroes and ones... But we now from here :

• 3 means the column is the cause and line the consequence...
• and 2 means the column is the consequence and line is the cause...

so, we replace them creating a new function

pag2cpdag<-function(fciAlgo){
  res<-as(fciAlgo,"amat")#a amat type pag
  res[res==3]<-1
  res[res==2]<-0
  return(res)
}

So we get with

pag2cpdag(fci.fit)

the following output:

Adjacency Matrix 'amat' (8 x 8) of type ‘pag’:
  1 2 3 4 5 6 7 8
1 . 1 . . . . . .
2 1 . 1 . 1 . . .
3 . 1 . . . . . .
4 . . . . . . . .
5 . 1 . . . . . .
6 1 . . . 1 . . .
7 . . . . . 1 . .
8 1 . . . 1 . . .

I was not able to change the type, but it delivers a matrix in the cpdag 's amat format. And can be applied to pdag2allDags ...

res1<-pdag2allDags(pag2cpdag(fci.fit))
plotAllDags(res1)

to return adequatelly the all equivalent DAGs...

---

But it still does not work for addBgKnowledge with objects generated by fci even the documentation saying it uses an amat

fci.amat2<-addBgKnowledge(gInput = pag2cpdag(fci.fit),x=1,y=2)
plot(as(t(fci.amat2),"graphNEL"))

it returns:

Error in h(simpleError(msg, call)) : error in evaluating the argument 'x' in selecting a method for function 'plot': no method or default for coercing “amat” to “graphNEL”

The output of

fci.amat2

appears to be ok...

Adjacency Matrix 'amat' (8 x 8) of type ‘pag’:
  1 2 3 4 5 6 7 8
1 . . . . . . . .
2 1 . . . . . . .
3 . 1 . . . . . .
4 . . . . . . . .
5 . 1 . . . . . .
6 1 . . . 1 . . .
7 . . . . . 1 . .
8 1 . . . 1 . . .

Looking at example, a simple matrix work for plotting it as graphNEL ... so, just converting to a simple matrix solves the issue:

pc.amat2<-addBgKnowledge(pag2cpdag(fci.fit),x=1,y=2)
class(pc.amat2)<-"matrix"
plot(as(t(pc.amat2),"graphNEL"))