Persistent state in a function?

Use a local environment to as a place to store state. Update with <<- 
and resolve symbol references through lexical scope E.g.,

     persist <- local({
         last <- NULL                # initialize
         function(value) {
             if (!missing(value))
                 last <<- value      # update with <<-
             last                    # use
         }
     })

and in action

 > persist("foo")
[1] "foo"
 > persist()
[1] "foo"
 > persist("bar")
[1] "bar"
 > persist()
[1] "bar"

A variant is to use a 'factory' function

     factory <- function(init) {
         stopifnot(!missing(init))
         last <- init
         function(value) {
             if (!missing(value))
                 last <<- value
             last
         }
     }

and

 > p1 = factory("foo")
 > p2 = factory("bar")
 > c(p1(), p2())
[1] "foo" "bar"
 > c(p1(), p2("foo"))
[1] "foo" "foo"
 > c(p1(), p2())
[1] "foo" "foo"

The 'bank account' exercise in section 10.7 of RShowDoc("R-intro") 
illustrates this.

Martin

Dear all -

I need to have a function maintain a persistent lookup table of results for an expensive calculation, a named vector or hash. I know that I can just keep the table in the global environment. One problem with this approach is that the function should be able to delete/recalculate the table and I don't like side-effects in the global environment. This table really should be private. What I don't know is:
  -A- how can I keep the table in an environment that is private to the function but persistent for the session?
  -B- how can I store and reload such table?
  -C- most importantly: is that the right strategy to initialize and maintain state in a function in the first place?


For illustration ...

-----------------------------------

myDist <- function(a, b) {
     # retrieve or calculate distances
     if (!exists("Vals")) {
         Vals <<- numeric() # the lookup table for distance values
                            # here, created in the global env.
     }
     key <- sprintf("X%d.%d", a, b)
     thisDist <- Vals[key]
     if (is.na(thisDist)) {          # Hasn't been calculated yet ...
         cat("Calculating ... ")
         thisDist <- sqrt(a^2 + b^2) # calculate with some expensive function ...
         Vals[key] <<- thisDist      # store in global table
     }
     return(thisDist)
}


# run this
set.seed(112358)

for (i in 1:10) {
     x <- sample(1:3, 2)
     print(sprintf("d(%d, %d) = %f", x[1], x[2], myDist(x[1], x[2])))
}


Thanks!
Boris

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