[Rd] ALTREP ALTINTEGER_SUM/MIN/MAX Return Value and Behavior

[Bill Dunlap]

Adding the dimensions attribute takes away the altrep-ness.  Removing
dimensions
does not make it altrep.  E.g.,

> a <- 1:10
> am <- a ; dim(am) <- c(2L,5L)
> amn <- am ; dim(amn) <- NULL
> .Call("is_altrep", a)
[1] TRUE
> .Call("is_altrep", am)
[1] FALSE
> .Call("is_altrep", amn)
[1] FALSE

where is_altrep() is defined by the following C code:

#include <R.h>
#include <Rinternals.h>

SEXP is_altrep(SEXP x)
{
    return Rf_ScalarLogical(ALTREP(x));
}

-Bill

On Tue, Jun 29, 2021 at 8:03 AM Sebastian Martin Krantz <
sebastian.krantz using graduateinstitute.ch> wrote:

> Hello together, I'm working on some custom (grouped, weighted) sum, min and
> max functions and I want them to support the special case of plain integer
> sequences using ALTREP. I thereby encountered some behavior I cannot
> explain to myself. The head of my fsum C function looks like this (g is
> optional grouping vector, w is optional weights vector):
>
> SEXP fsumC(SEXP x, SEXP Rng, SEXP g, SEXP w, SEXP Rnarm) {
>   int l = length(x), tx = TYPEOF(x), ng = asInteger(Rng),
>     narm = asLogical(Rnarm), nprotect = 1, nwl = isNull(w);
>   if(ALTREP(x) && ng == 0 && nwl) {
>     switch(tx) {
>     case INTSXP: return ALTINTEGER_SUM(x, (Rboolean)narm);
>     case LGLSXP: return ALTLOGICAL_SUM(x, (Rboolean)narm);
>     case REALSXP: return ALTLOGICAL_SUM(x, (Rboolean)narm);
>     default: error("ALTREP object must be integer or real typed");
>     }
>   }
> // ...
> }
>
> when I let x <- 1:1e8, fsum(x) works fine and returns the correct value. If
> I now make this a matrix dim(x) <- c(1e2, 1e6) and subsequently turn this
> into a vector again, dim(x) <- NULL, fsum(x) gives  NULL and a warning
> message 'converting NULL pointer to R NULL'. For functions fmin and fmax
> (similarly defined using ALTINTEGER_MIN/MAX), I get this error right away
> e.g. fmin(1:1e8) gives NULL and warning 'converting NULL pointer to R
> NULL'. So what is going on here? What do these functions return? And how do
> I make this a robust implementation?
>
> Best regards,
>
> Sebastian Krantz
>
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>
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