Long vectors: Missing values and R_xlen_t?

Is there a missing value constant defined for R_xlen_t, cf. NA_INTEGER
(== R_NaInt == INT_MIN) for int(eger)?  If not, is it correct to
assume that missing values should be taken care/tested for before
coercing from int or double?

On Sep 20, 2015, at 3:06 PM, Henrik Bengtsson <henrik.bengtsson at ucsf.edu> wrote:

Is there a missing value constant defined for R_xlen_t, cf. NA_INTEGER
(== R_NaInt == INT_MIN) for int(eger)?  If not, is it correct to
assume that missing values should be taken care/tested for before
coercing from int or double?

R_xlen_t is type of the vector length (see XLENGTH()) and as such never holds a missing value (since there is no such thing as a missing length). It is *not* a native type for R vectors and therefore there is no official representation of NAs in R_xlen_t.

Although native R vectors can be used as indices, the way it typically works is that the code first checks for NAs in the R vector and only then converts to R_xlen_t, so the NA value is never stored in R_xlen_t even for indexing.

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That said, when converting packages from "legacy" .Call code before long vector support which used asInteger() to convert an index I tend to use this utility for convenience:

static R_INLINE R_xlen_t asLength(SEXP x, R_xlen_t NA) {
    double d;
    if (TYPEOF(x) == INTSXP && LENGTH(x) > 0) {
        int res = INTEGER(x)[0];
        return (res == NA_INTEGER) ? NA : ((R_xlen_t) res);
    }
    d = asReal(x);
    return (R_finite(d)) ? ((R_xlen_t) d) : NA;
}

Note that this explicitly allows the caller to specify NA representation since it depends on the use - often it's simply 0, other times -1 will do since typically anything negative is equally bad. As noted above, this is not what R itself does, so it's more of a convenience to simplify conversion of legacy code.

Cheers,
Simon