The Art of R Programming

There are several possibilities here. But since ultimatelyimin()is called,

we can check them all from within that function. So, let’s set the debug sta-

tus ofimin(), quit the debugger, and rerun the code.

Browse[1]> Q

> debug(imin)

> mind(m)

debugging in: FUN(newX[, i], ...)

debug at cities.R#17: {

n <- length(x)

i <- x[n]

j <- which.min(x[(i + 1):(n - 1)])

return(c(j, x[j]))

}

...

So, we’re inimin(). Let’s see if it properly received the first row ofdd,

which should be (0,12,5,1).

Browse[4]> x

[1] 0 12 5 1

It’s confirmed. This seems to indicate that the first two arguments to

apply()were correct and that the problem is instead withinimin(), though

that remains to be seen.

Let’s single-step through, occasionally typing confirmational queries:

Browse[2]> n

debug at cities.r#17: n <- length(x)

Browse[2]> n

debug at cities.r#18: i <- x[n]

Browse[2]> n

debug at cities.r#19: j <- which.min(x[(i + 1):(n - 1)])

Browse[2]> n

debug at cities.r#20: return(c(j, x[j]))

Browse[2]> print(n)

[1] 4

Browse[2]> i

[1] 1

Browse[2]> j

[1] 2

Recall that we designed our callwhich.min(x[(i + 1):(n - 1)]to look only

at the above-diagonal portion of this row. This is because the matrix is sym-

metric and because we don’t want to consider the distance between a city

and itself.

298 Chapter 13