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gsumm.c
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#include "data.table.h"
//#include <time.h>
static int ngrp = 0; // number of groups
static int *grpsize = NULL; // size of each group, used by gmean (and gmedian) not gsum
static int nrow = 0; // length of underlying x; same as length(ghigh) and length(glow)
static int *irows; // GForce support for subsets in 'i' (TODO: joins in 'i')
static int irowslen = -1; // -1 is for irows = NULL
static uint16_t *high=NULL, *low=NULL; // the group of each x item; a.k.a. which-group-am-I
static int *restrict grp; // TODO: eventually this can be made local for gforce as won't be needed globally when all functions here use gather
static size_t highSize;
static int shift, mask;
static char *gx=NULL;
static size_t nBatch, batchSize, lastBatchSize;
static int *counts, *tmpcounts;
// for gmedian
static int maxgrpn = 0;
static int *oo = NULL;
static int *ff = NULL;
static int isunsorted = 0;
// from R's src/cov.c (for variance / sd)
#ifdef HAVE_LONG_DOUBLE
# define SQRTL sqrtl
#else
# define SQRTL sqrt
#endif
static int nbit(int n)
{
// returns position of biggest bit; i.e. floor(log2(n))+1 without using fpa
// not needed to be fast. Just a helper function.
int nb=0;
while (n) { nb++; n>>=1; }
return nb;
}
SEXP gforce(SEXP env, SEXP jsub, SEXP o, SEXP f, SEXP l, SEXP irowsArg) {
double started = wallclock();
const bool verbose = GetVerbose();
if (TYPEOF(env) != ENVSXP) error(_("env is not an environment"));
// The type of jsub is pretty flexbile in R, so leave checking to eval() below.
if (!isInteger(o)) error(_("%s is not an integer vector"), "o");
if (!isInteger(f)) error(_("%s is not an integer vector"), "f");
if (!isInteger(l)) error(_("%s is not an integer vector"), "l");
if (isNull(irowsArg)) {
irows = NULL;
irowslen = -1;
}
else if (isInteger(irowsArg)) {
irows = INTEGER(irowsArg);
irowslen = LENGTH(irowsArg);
}
else error(_("irowsArg is neither an integer vector nor NULL")); // # nocov
ngrp = LENGTH(l);
if (LENGTH(f) != ngrp) error(_("length(f)=%d != length(l)=%d"), LENGTH(f), ngrp);
nrow=0;
grpsize = INTEGER(l);
maxgrpn = 0;
for (int i=0; i<ngrp; i++) {
nrow+=grpsize[i];
if (grpsize[i]>maxgrpn) maxgrpn = grpsize[i]; // old comment to be checked: 'needed for #2046 and #2111 when maxgrpn attribute is not attached to empty o'
}
if (LENGTH(o) && LENGTH(o)!=nrow) error(_("o has length %d but sum(l)=%d"), LENGTH(o), nrow);
{
SEXP tt = getAttrib(o, install("maxgrpn"));
if (length(tt)==1 && INTEGER(tt)[0]!=maxgrpn) error(_("Internal error: o's maxgrpn attribute mismatches recalculated maxgrpn")); // # nocov
}
int nb = nbit(ngrp-1);
shift = nb/2; // /2 so that high and low can be uint16_t, and no limit (even for nb=4) to stress-test.
// shift=MAX(nb-8,0); if (shift>16) shift=nb/2; // TODO: when we have stress-test off mode, do this
mask = (1<<shift)-1;
highSize = ((ngrp-1)>>shift) + 1;
grp = (int *)R_alloc(nrow, sizeof(int)); // TODO: use malloc and made this local as not needed globally when all functions here use gather
// maybe better to malloc to avoid R's heap. This grp isn't global, so it doesn't need to be R_alloc
const int *restrict fp = INTEGER(f);
nBatch = MIN((nrow+1)/2, getDTthreads(nrow, true)*2); // *2 to reduce last-thread-home. TODO: experiment. The higher this is though, the bigger is counts[]
batchSize = MAX(1, (nrow-1)/nBatch);
lastBatchSize = nrow - (nBatch-1)*batchSize;
// We deliberate use, for example, 40 batches of just 14 rows, to stress-test tests. This strategy proved to be a good one as #3204 immediately came to light.
// TODO: enable stress-test mode in tests only (#3205) which can be turned off by default in release to decrease overhead on small data
// if that is established to be biting (it may be fine).
if (nBatch<1 || batchSize<1 || lastBatchSize<1) {
error(_("Internal error: nrow=%d ngrp=%d nbit=%d shift=%d highSize=%d nBatch=%d batchSize=%d lastBatchSize=%d\n"), // # nocov
nrow, ngrp, nb, shift, highSize, nBatch, batchSize, lastBatchSize); // # nocov
}
// initial population of g:
#pragma omp parallel for num_threads(getDTthreads(ngrp, false))
for (int g=0; g<ngrp; g++) {
int *elem = grp + fp[g]-1;
for (int j=0; j<grpsize[g]; j++) elem[j] = g;
}
if (verbose) { Rprintf(_("gforce initial population of grp took %.3f\n"), wallclock()-started); started=wallclock(); }
isunsorted = 0;
if (LENGTH(o)) {
isunsorted = 1; // for gmedian
// What follows is more cache-efficient version of this scattered assign :
// for (int g=0; g<ngrp; g++) {
// const int *elem = op + fp[g]-1;
// for (int j=0; j<grpsize[g]; j++) grp[ elem[j]-1 ] = g;
//}
const int *restrict op = INTEGER(o); // o is a permutation of 1:nrow
int nb = nbit(nrow-1);
int shift = MAX(nb-8, 0); // TODO: experiment nb/2. Here it doesn't have to be /2 currently.
int highSize = ((nrow-1)>>shift) + 1;
//Rprintf(_("When assigning grp[o] = g, highSize=%d nb=%d shift=%d nBatch=%d\n"), highSize, nb, shift, nBatch);
int *counts = calloc(nBatch*highSize, sizeof(int)); // TODO: cache-line align and make highSize a multiple of 64
int *TMP = malloc(nrow*2*sizeof(int));
if (!counts || !TMP ) error(_("Internal error: Failed to allocate counts or TMP when assigning g in gforce"));
#pragma omp parallel for num_threads(getDTthreads(nBatch, false)) // schedule(dynamic,1)
for (int b=0; b<nBatch; b++) {
const int howMany = b==nBatch-1 ? lastBatchSize : batchSize;
const int *my_o = op + b*batchSize;
int *restrict my_counts = counts + b*highSize;
for (int i=0; i<howMany; i++) {
const int w = (my_o[i]-1) >> shift;
my_counts[w]++;
}
for (int i=0, cum=0; i<highSize; i++) {
int tmp = my_counts[i];
my_counts[i] = cum;
cum += tmp;
}
const int *restrict my_g = grp + b*batchSize;
int *restrict my_tmp = TMP + b*2*batchSize;
for (int i=0; i<howMany; i++) {
const int w = (my_o[i]-1) >> shift; // could use my_high but may as well use my_pg since we need my_pg anyway for the lower bits next too
int *p = my_tmp + 2*my_counts[w]++;
*p++ = my_o[i]-1;
*p = my_g[i];
}
}
//Rprintf(_("gforce assign TMP (o,g) pairs took %.3f\n"), wallclock()-started); started=wallclock();
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) { // very important that high is first loop here
for (int b=0; b<nBatch; b++) {
const int start = h==0 ? 0 : counts[ b*highSize + h - 1 ];
const int end = counts[ b*highSize + h ];
const int *restrict p = TMP + b*2*batchSize + start*2;
for (int k=start; k<end; k++, p+=2) {
grp[p[0]] = p[1]; // TODO: could write high here, and initial low. ** If so, same in initial population when o is missing **
}
}
}
free(counts);
free(TMP);
//Rprintf(_("gforce assign TMP [ (o,g) pairs ] back to grp took %.3f\n"), wallclock()-started); started=wallclock();
}
high = (uint16_t *)R_alloc(nrow, sizeof(uint16_t)); // maybe better to malloc to avoid R's heap, but safer to R_alloc since it's done via eval()
low = (uint16_t *)R_alloc(nrow, sizeof(uint16_t));
// global ghigh and glow because the g* functions (inside jsub) share this common memory
gx = (char *)R_alloc(nrow, sizeof(Rcomplex)); // enough for a copy of one column (or length(irows) if supplied)
// TODO: reduce to the largest type present; won't be faster (untouched RAM won't be fetched) but it will increase the largest size that works.
counts = (int *)S_alloc(nBatch*highSize, sizeof(int)); // (S_ zeros) TODO: cache-line align and make highSize a multiple of 64
tmpcounts = (int *)R_alloc(getDTthreads(nBatch, false)*highSize, sizeof(int));
const int *restrict gp = grp;
#pragma omp parallel for num_threads(getDTthreads(nBatch, false)) // schedule(dynamic,1)
for (int b=0; b<nBatch; b++) {
int *restrict my_counts = counts + b*highSize;
uint16_t *restrict my_high = high + b*batchSize;
const int *my_pg = gp + b*batchSize;
const int howMany = b==nBatch-1 ? lastBatchSize : batchSize;
for (int i=0; i<howMany; i++) {
const int w = my_pg[i] >> shift;
my_counts[w]++;
my_high[i] = (uint16_t)w; // reduce 4 bytes to 2
}
for (int i=0, cum=0; i<highSize; i++) {
int tmp = my_counts[i];
my_counts[i] = cum;
cum += tmp;
}
uint16_t *restrict my_low = low + b*batchSize;
int *restrict my_tmpcounts = tmpcounts + omp_get_thread_num()*highSize;
memcpy(my_tmpcounts, my_counts, highSize*sizeof(int));
for (int i=0; i<howMany; i++) {
const int w = my_pg[i] >> shift; // could use my_high but may as well use my_pg since we need my_pg anyway for the lower bits next too
my_low[my_tmpcounts[w]++] = (uint16_t)(my_pg[i] & mask);
}
// counts is now cumulated within batch (with ending values) and we leave it that way
// memcpy(counts + b*256, myCounts, 256*sizeof(int)); // save cumulate for later, first bucket contains position of next. For ease later in the very last batch.
}
if (verbose) { Rprintf(_("gforce assign high and low took %.3f\n"), wallclock()-started); started=wallclock(); }
oo = INTEGER(o);
ff = INTEGER(f);
SEXP ans = PROTECT( eval(jsub, env) );
if (verbose) { Rprintf(_("gforce eval took %.3f\n"), wallclock()-started); started=wallclock(); }
// if this eval() fails with R error, R will release grp for us. Which is why we use R_alloc above.
if (isVectorAtomic(ans)) {
SEXP tt = PROTECT(allocVector(VECSXP, 1));
SET_VECTOR_ELT(tt, 0, ans);
UNPROTECT(2);
return tt;
}
UNPROTECT(1);
return ans;
}
void *gather(SEXP x, bool *anyNA)
{
double started=wallclock();
const bool verbose = GetVerbose();
if (verbose) Rprintf(_("gather took ... "));
switch (TYPEOF(x)) {
case LGLSXP: case INTSXP: {
const int *restrict thisx = INTEGER(x);
#pragma omp parallel for num_threads(getDTthreads(nBatch, false))
for (int b=0; b<nBatch; b++) {
int *restrict my_tmpcounts = tmpcounts + omp_get_thread_num()*highSize;
memcpy(my_tmpcounts, counts + b*highSize, highSize*sizeof(int)); // original cumulated // already cumulated for this batch
int *restrict my_gx = (int *)gx + b*batchSize;
const uint16_t *my_high = high + b*batchSize;
const int howMany = b==nBatch-1 ? lastBatchSize : batchSize;
bool my_anyNA = false;
if (irowslen==-1) {
const int *my_x = thisx + b*batchSize;
for (int i=0; i<howMany; i++) {
const int elem = my_x[i];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
if (elem==NA_INTEGER) my_anyNA = true;
}
} else {
const int *my_x = irows + b*batchSize;
for (int i=0; i<howMany; i++) {
int elem = thisx[ my_x[i]-1 ];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
if (elem==NA_INTEGER) my_anyNA = true;
}
}
if (my_anyNA) *anyNA = true; // naked write ok since just bool and always writing true; and no performance issue as maximum nBatch writes
}
} break;
case REALSXP: {
if (!INHERITS(x, char_integer64)) {
const double *restrict thisx = REAL(x);
#pragma omp parallel for num_threads(getDTthreads(nBatch, false))
for (int b=0; b<nBatch; b++) {
int *restrict my_tmpcounts = tmpcounts + omp_get_thread_num()*highSize;
memcpy(my_tmpcounts, counts + b*highSize, highSize*sizeof(int));
double *restrict my_gx = (double *)gx + b*batchSize;
const uint16_t *my_high = high + b*batchSize;
const int howMany = b==nBatch-1 ? lastBatchSize : batchSize;
bool my_anyNA = false;
if (irowslen==-1) {
const double *my_x = thisx + b*batchSize;
for (int i=0; i<howMany; i++) {
const double elem = my_x[i];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
if (ISNAN(elem)) my_anyNA = true; // R's ISNAN includes NA; i.e. defined as C isnan with some platform specific differences (perhaps historic)
}
} else {
const int *my_x = irows + b*batchSize;
for (int i=0; i<howMany; i++) {
double elem = thisx[ my_x[i]-1 ];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
if (ISNAN(elem)) my_anyNA = true;
}
}
if (my_anyNA) *anyNA = true;
}
} else {
const int64_t *restrict thisx = (int64_t *)REAL(x);
#pragma omp parallel for num_threads(getDTthreads(nBatch, false))
for (int b=0; b<nBatch; b++) {
int *restrict my_tmpcounts = tmpcounts + omp_get_thread_num()*highSize;
memcpy(my_tmpcounts, counts + b*highSize, highSize*sizeof(int));
int64_t *restrict my_gx = (int64_t *)gx + b*batchSize;
const uint16_t *my_high = high + b*batchSize;
const int howMany = b==nBatch-1 ? lastBatchSize : batchSize;
bool my_anyNA = false;
if (irowslen==-1) {
const int64_t *my_x = thisx + b*batchSize;
for (int i=0; i<howMany; i++) {
const int64_t elem = my_x[i];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
if (elem==INT64_MIN) my_anyNA = true;
}
} else {
const int *my_x = irows + b*batchSize;
for (int i=0; i<howMany; i++) {
int64_t elem = thisx[ my_x[i]-1 ];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
if (elem==INT64_MIN) my_anyNA = true;
}
}
if (my_anyNA) *anyNA = true;
}
}
} break;
case CPLXSXP: {
const Rcomplex *restrict thisx = COMPLEX(x);
#pragma omp parallel for num_threads(getDTthreads(nBatch, false))
for (int b=0; b<nBatch; b++) {
int *restrict my_tmpcounts = tmpcounts + omp_get_thread_num()*highSize;
memcpy(my_tmpcounts, counts + b*highSize, highSize*sizeof(int));
Rcomplex *restrict my_gx = (Rcomplex *)gx + b*batchSize;
const uint16_t *my_high = high + b*batchSize;
const int howMany = b==nBatch-1 ? lastBatchSize : batchSize;
bool my_anyNA = false;
if (irowslen==-1) {
const Rcomplex *my_x = thisx + b*batchSize;
for (int i=0; i<howMany; i++) {
const Rcomplex elem = my_x[i];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
// typically just checking one component would be enough,
// but ?complex suggests there may be some edge cases; better to be safe
if (ISNAN(elem.r) && ISNAN(elem.i)) my_anyNA = true;
}
} else {
const int *my_x = irows + b*batchSize;
for (int i=0; i<howMany; i++) {
Rcomplex elem = thisx[ my_x[i]-1 ];
my_gx[ my_tmpcounts[my_high[i]]++ ] = elem;
if (ISNAN(elem.r) && ISNAN(elem.i)) my_anyNA = true;
}
}
if (my_anyNA) *anyNA = true; // naked write ok since just bool and always writing true; and no performance issue as maximum nBatch writes
}
} break;
default :
error(_("gather implemented for INTSXP, REALSXP, and CPLXSXP but not '%s'"), type2char(TYPEOF(x))); // # nocov
}
if (verbose) { Rprintf(_("%.3fs\n"), wallclock()-started); }
return gx;
}
SEXP gsum(SEXP x, SEXP narmArg, SEXP warnOverflowArg)
{
if (!isLogical(narmArg) || LENGTH(narmArg)!=1 || LOGICAL(narmArg)[0]==NA_LOGICAL) error(_("na.rm must be TRUE or FALSE"));
const bool narm = LOGICAL(narmArg)[0];
const bool warnOverflow = LOGICAL(warnOverflowArg)[0];
if (inherits(x, "factor")) error(_("sum is not meaningful for factors."));
const int n = (irowslen == -1) ? length(x) : irowslen;
double started = wallclock();
const bool verbose=GetVerbose();
if (verbose) Rprintf(_("This gsum took (narm=%s) ... "), narm?"TRUE":"FALSE");
if (nrow != n) error(_("nrow [%d] != length(x) [%d] in %s"), nrow, n, "gsum");
bool anyNA=false;
SEXP ans;
switch(TYPEOF(x)) {
case LGLSXP: case INTSXP: {
const int *restrict gx = gather(x, &anyNA);
ans = PROTECT(allocVector(INTSXP, ngrp));
int *restrict ansp = INTEGER(ans);
memset(ansp, 0, ngrp*sizeof(int));
bool overflow=false;
//double started = wallclock();
if (!anyNA) {
#pragma omp parallel for num_threads(getDTthreads(highSize, false)) //schedule(dynamic,1)
for (int h=0; h<highSize; h++) { // very important that high is first loop here
int *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const int a = _ans[my_low[i]];
const int b = my_gx[i];
if ((a>0 && b>INT_MAX-a) || (a<0 && b<NA_INTEGER+1-a)) overflow=true;
else _ans[my_low[i]] += b; // naked by design; each thread does all of each h for all batches
}
}
}
} else {
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
int *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const int a = _ans[my_low[i]];
if (a==NA_INTEGER) continue;
const int b = my_gx[i];
if (b==NA_INTEGER) {
if (!narm) _ans[my_low[i]]=NA_INTEGER;
continue;
}
if ((a>0 && b>INT_MAX-a) || (a<0 && b<NA_INTEGER+1-a)) overflow=true;
else _ans[my_low[i]] += b;
}
}
}
}
//Rprintf(_("gsum int took %.3f\n"), wallclock()-started);
if (overflow) {
UNPROTECT(1); // discard the result with overflow
if (warnOverflow) warning(_("The sum of an integer column for a group was more than type 'integer' can hold so the result has been coerced to 'numeric' automatically for convenience."));
ans = PROTECT(allocVector(REALSXP, ngrp));
double *restrict ansp = REAL(ans);
memset(ansp, 0, ngrp*sizeof(double));
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
double *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
// rare and slower so no need to switch on anyNA
for (int i=0; i<howMany; i++) {
const int elem = my_gx[i];
if (elem==NA_INTEGER) {
if (!narm) _ans[my_low[i]]=NA_REAL;
continue;
}
_ans[my_low[i]] += elem; // let NA_REAL propagate
}
}
}
}
} break;
case REALSXP: {
if (!INHERITS(x, char_integer64)) {
const double *restrict gx = gather(x, &anyNA);
ans = PROTECT(allocVector(REALSXP, ngrp));
double *restrict ansp = REAL(ans);
memset(ansp, 0, ngrp*sizeof(double));
if (!narm || !anyNA) {
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
double *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const double *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
_ans[my_low[i]] += my_gx[i]; // let NA propagate when !narm
}
}
}
} else {
// narm==true and anyNA==true
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
double *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const double *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const double elem = my_gx[i];
if (!ISNAN(elem)) _ans[my_low[i]] += elem;
}
}
}
}
} else { // int64
const int64_t *restrict gx = gather(x, &anyNA);
ans = PROTECT(allocVector(REALSXP, ngrp));
int64_t *restrict ansp = (int64_t *)REAL(ans);
memset(ansp, 0, ngrp*sizeof(int64_t));
if (!anyNA) {
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
int64_t *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int64_t *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
_ans[my_low[i]] += my_gx[i]; // does not propagate INT64 for !narm
}
}
}
} else { // narm==true/false and anyNA==true
if (!narm) {
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
int64_t *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int64_t *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const int64_t elem = my_gx[i];
if (elem!=INT64_MIN) {
_ans[my_low[i]] += elem;
} else {
_ans[my_low[i]] = INT64_MIN;
break;
}
}
}
}
} else {
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
int64_t *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int64_t *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const int64_t elem = my_gx[i];
if (elem!=INT64_MIN) _ans[my_low[i]] += elem;
}
}
}
}
}
}
} break;
case CPLXSXP: {
const Rcomplex *restrict gx = gather(x, &anyNA);
ans = PROTECT(allocVector(CPLXSXP, ngrp));
Rcomplex *restrict ansp = COMPLEX(ans);
memset(ansp, 0, ngrp*sizeof(Rcomplex));
if (!narm || !anyNA) {
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
Rcomplex *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const Rcomplex *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
_ans[my_low[i]].r += my_gx[i].r; // let NA propagate when !narm
_ans[my_low[i]].i += my_gx[i].i;
}
}
}
} else {
// narm==true and anyNA==true
#pragma omp parallel for num_threads(getDTthreads(highSize, false))
for (int h=0; h<highSize; h++) {
Rcomplex *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const Rcomplex *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const Rcomplex elem = my_gx[i];
if (!ISNAN(elem.r)) _ans[my_low[i]].r += elem.r;
if (!ISNAN(elem.i)) _ans[my_low[i]].i += elem.i;
}
}
}
}
} break;
default:
error(_("Type '%s' not supported by GForce sum (gsum). Either add the prefix base::sum(.) or turn off GForce optimization using options(datatable.optimize=1)"), type2char(TYPEOF(x)));
}
copyMostAttrib(x, ans);
if (verbose) { Rprintf(_("%.3fs\n"), wallclock()-started); }
UNPROTECT(1);
return(ans);
}
SEXP gmean(SEXP x, SEXP narm)
{
SEXP ans=R_NilValue;
//clock_t start = clock();
if (!isLogical(narm) || LENGTH(narm)!=1 || LOGICAL(narm)[0]==NA_LOGICAL) error(_("na.rm must be TRUE or FALSE"));
if (!isVectorAtomic(x)) error(_("GForce mean can only be applied to columns, not .SD or similar. Likely you're looking for 'DT[,lapply(.SD,mean),by=,.SDcols=]'. See ?data.table."));
if (inherits(x, "factor")) error(_("mean is not meaningful for factors."));
if (!LOGICAL(narm)[0]) {
int protecti=0;
ans = PROTECT(gsum(x, narm, /*#986, warnOverflow=*/ScalarLogical(FALSE))); protecti++;
switch(TYPEOF(ans)) {
case LGLSXP: case INTSXP:
ans = PROTECT(coerceVector(ans, REALSXP)); protecti++;
case REALSXP: {
double *xd = REAL(ans);
for (int i=0; i<ngrp; i++) *xd++ /= grpsize[i]; // let NA propogate
} break;
case CPLXSXP: {
Rcomplex *xd = COMPLEX(ans);
for (int i=0; i<ngrp; i++) {
xd->i /= grpsize[i];
xd->r /= grpsize[i];
xd++;
}
} break;
default :
error(_("Internal error: gsum returned type '%s'. typeof(x) is '%s'"), type2char(TYPEOF(ans)), type2char(TYPEOF(x))); // # nocov
}
UNPROTECT(protecti);
return(ans);
}
// na.rm=TRUE. Similar to gsum, but we need to count the non-NA as well for the divisor
const int n = (irowslen == -1) ? length(x) : irowslen;
if (nrow != n) error(_("nrow [%d] != length(x) [%d] in %s"), nrow, n, "gsum");
long double *s = calloc(ngrp, sizeof(long double)), *si=NULL; // s = sum; si = sum imaginary just for complex
if (!s) error(_("Unable to allocate %d * %d bytes for sum in gmean na.rm=TRUE"), ngrp, sizeof(long double));
int *c = calloc(ngrp, sizeof(int));
if (!c) error(_("Unable to allocate %d * %d bytes for counts in gmean na.rm=TRUE"), ngrp, sizeof(int));
switch(TYPEOF(x)) {
case LGLSXP: case INTSXP: {
const int *xd = INTEGER(x);
for (int i=0; i<n; i++) {
int thisgrp = grp[i];
int ix = (irowslen == -1) ? i : irows[i]-1;
if (xd[ix] == NA_INTEGER) continue;
s[thisgrp] += xd[ix]; // no under/overflow here, s is long double
c[thisgrp]++;
}
} break;
case REALSXP: {
const double *xd = REAL(x);
for (int i=0; i<n; i++) {
int thisgrp = grp[i];
int ix = (irowslen == -1) ? i : irows[i]-1;
if (ISNAN(xd[ix])) continue;
s[thisgrp] += xd[ix];
c[thisgrp]++;
}
} break;
case CPLXSXP: {
const Rcomplex *xd = COMPLEX(x);
si = calloc(ngrp, sizeof(long double));
if (!si) error(_("Unable to allocate %d * %d bytes for si in gmean na.rm=TRUE"), ngrp, sizeof(long double));
for (int i=0; i<n; i++) {
int thisgrp = grp[i];
int ix = (irowslen == -1) ? i : irows[i]-1;
if (ISNAN(xd[ix].r) || ISNAN(xd[ix].i)) continue; // || otherwise we'll need two counts in two c's too?
s[thisgrp] += xd[ix].r;
si[thisgrp] += xd[ix].i;
c[thisgrp]++;
}
} break;
default:
free(s); free(c); // # nocov because it already stops at gsum, remove nocov if gmean will support a type that gsum wont
error(_("Type '%s' not supported by GForce mean (gmean) na.rm=TRUE. Either add the prefix base::mean(.) or turn off GForce optimization using options(datatable.optimize=1)"), type2char(TYPEOF(x))); // # nocov
}
switch(TYPEOF(x)) {
case LGLSXP: case INTSXP: case REALSXP: {
ans = PROTECT(allocVector(REALSXP, ngrp));
double *ansd = REAL(ans);
for (int i=0; i<ngrp; i++) {
if (c[i]==0) { ansd[i] = R_NaN; continue; } // NaN to follow base::mean
s[i] /= c[i];
ansd[i] = s[i]>DBL_MAX ? R_PosInf : (s[i] < -DBL_MAX ? R_NegInf : (double)s[i]);
}
} break;
case CPLXSXP: {
ans = PROTECT(allocVector(CPLXSXP, ngrp));
Rcomplex *ansd = COMPLEX(ans);
for (int i=0; i<ngrp; i++) {
if (c[i]==0) { ansd[i].r = R_NaN; ansd[i].i = R_NaN; continue; }
s[i] /= c[i];
si[i] /= c[i];
ansd[i].r = s[i] >DBL_MAX ? R_PosInf : (s[i] < -DBL_MAX ? R_NegInf : (double)s[i]);
ansd[i].i = si[i]>DBL_MAX ? R_PosInf : (si[i]< -DBL_MAX ? R_NegInf : (double)si[i]);
}
} break;
default:
error(_("Internal error: unsupported type at the end of gmean")); // # nocov
}
free(s); free(si); free(c);
copyMostAttrib(x, ans);
// Rprintf(_("this gmean na.rm=TRUE took %8.3f\n"), 1.0*(clock()-start)/CLOCKS_PER_SEC);
UNPROTECT(1);
return(ans);
}
// gmin
SEXP gmin(SEXP x, SEXP narm)
{
if (!isLogical(narm) || LENGTH(narm)!=1 || LOGICAL(narm)[0]==NA_LOGICAL) error(_("na.rm must be TRUE or FALSE"));
if (!isVectorAtomic(x)) error(_("GForce min can only be applied to columns, not .SD or similar. To find min of all items in a list such as .SD, either add the prefix base::min(.SD) or turn off GForce optimization using options(datatable.optimize=1). More likely, you may be looking for 'DT[,lapply(.SD,min),by=,.SDcols=]'"));
if (inherits(x, "factor") && !inherits(x, "ordered")) error(_("min is not meaningful for factors."));
R_len_t i, ix, thisgrp=0;
int n = (irowslen == -1) ? length(x) : irowslen;
//clock_t start = clock();
SEXP ans;
if (nrow != n) error(_("nrow [%d] != length(x) [%d] in %s"), nrow, n, "gmin");
int protecti=0;
switch(TYPEOF(x)) {
case LGLSXP: case INTSXP:
ans = PROTECT(allocVector(INTSXP, ngrp)); protecti++;
if (!LOGICAL(narm)[0]) {
for (i=0; i<ngrp; i++) INTEGER(ans)[i] = INT_MAX;
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (INTEGER(x)[ix] < INTEGER(ans)[thisgrp]) // NA_INTEGER==INT_MIN checked in init.c
INTEGER(ans)[thisgrp] = INTEGER(x)[ix];
}
} else {
for (i=0; i<ngrp; i++) INTEGER(ans)[i] = NA_INTEGER;
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (INTEGER(x)[ix] == NA_INTEGER) continue;
if (INTEGER(ans)[thisgrp] == NA_INTEGER || INTEGER(x)[ix] < INTEGER(ans)[thisgrp])
INTEGER(ans)[thisgrp] = INTEGER(x)[ix];
}
for (i=0; i<ngrp; i++) {
if (INTEGER(ans)[i] == NA_INTEGER) {
warning(_("No non-missing values found in at least one group. Coercing to numeric type and returning 'Inf' for such groups to be consistent with base"));
ans = PROTECT(coerceVector(ans, REALSXP)); protecti++;
for (i=0; i<ngrp; i++) {
if (ISNA(REAL(ans)[i])) REAL(ans)[i] = R_PosInf;
}
break;
}
}
}
break;
case STRSXP:
ans = PROTECT(allocVector(STRSXP, ngrp)); protecti++;
if (!LOGICAL(narm)[0]) {
for (i=0; i<ngrp; i++) SET_STRING_ELT(ans, i, R_BlankString);
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (STRING_ELT(x, ix) == NA_STRING) {
SET_STRING_ELT(ans, thisgrp, NA_STRING);
} else {
if (STRING_ELT(ans, thisgrp) == R_BlankString ||
(STRING_ELT(ans, thisgrp) != NA_STRING && strcmp(CHAR(STRING_ELT(x, ix)), CHAR(STRING_ELT(ans, thisgrp))) < 0 )) {
SET_STRING_ELT(ans, thisgrp, STRING_ELT(x, ix));
}
}
}
} else {
for (i=0; i<ngrp; i++) SET_STRING_ELT(ans, i, NA_STRING);
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (STRING_ELT(x, ix) == NA_STRING) continue;
if (STRING_ELT(ans, thisgrp) == NA_STRING ||
strcmp(CHAR(STRING_ELT(x, ix)), CHAR(STRING_ELT(ans, thisgrp))) < 0) {
SET_STRING_ELT(ans, thisgrp, STRING_ELT(x, ix));
}
}
for (i=0; i<ngrp; i++) {
if (STRING_ELT(ans, i)==NA_STRING) {
warning(_("No non-missing values found in at least one group. Returning 'NA' for such groups to be consistent with base"));
break;
}
}
}
break;
case REALSXP:
ans = PROTECT(allocVector(REALSXP, ngrp)); protecti++;
if (!LOGICAL(narm)[0]) {
for (i=0; i<ngrp; i++) REAL(ans)[i] = R_PosInf;
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (ISNAN(REAL(x)[ix]) || REAL(x)[ix] < REAL(ans)[thisgrp])
REAL(ans)[thisgrp] = REAL(x)[ix];
}
} else {
for (i=0; i<ngrp; i++) REAL(ans)[i] = NA_REAL;
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (ISNAN(REAL(x)[ix])) continue;
if (ISNAN(REAL(ans)[thisgrp]) || REAL(x)[ix] < REAL(ans)[thisgrp])
REAL(ans)[thisgrp] = REAL(x)[ix];
}
for (i=0; i<ngrp; i++) {
if (ISNAN(REAL(ans)[i])) {
warning(_("No non-missing values found in at least one group. Returning 'Inf' for such groups to be consistent with base"));
for (; i<ngrp; i++) if (ISNAN(REAL(ans)[i])) REAL(ans)[i] = R_PosInf;
break;
}
}
}
break;
case CPLXSXP:
error(_("Type 'complex' has no well-defined min"));
break;
default:
error(_("Type '%s' not supported by GForce min (gmin). Either add the prefix base::min(.) or turn off GForce optimization using options(datatable.optimize=1)"), type2char(TYPEOF(x)));
}
copyMostAttrib(x, ans); // all but names,dim and dimnames. And if so, we want a copy here, not keepattr's SET_ATTRIB.
UNPROTECT(protecti); // ans + maybe 1 coerced ans
// Rprintf(_("this gmin took %8.3f\n"), 1.0*(clock()-start)/CLOCKS_PER_SEC);
return(ans);
}
// gmax
SEXP gmax(SEXP x, SEXP narm)
{
if (!isLogical(narm) || LENGTH(narm)!=1 || LOGICAL(narm)[0]==NA_LOGICAL) error(_("na.rm must be TRUE or FALSE"));
if (!isVectorAtomic(x)) error(_("GForce max can only be applied to columns, not .SD or similar. To find max of all items in a list such as .SD, either add the prefix base::max(.SD) or turn off GForce optimization using options(datatable.optimize=1). More likely, you may be looking for 'DT[,lapply(.SD,max),by=,.SDcols=]'"));
if (inherits(x, "factor") && !inherits(x, "ordered")) error(_("max is not meaningful for factors."));
R_len_t i, ix, thisgrp=0;
int n = (irowslen == -1) ? length(x) : irowslen;
//clock_t start = clock();
SEXP ans;
if (nrow != n) error(_("nrow [%d] != length(x) [%d] in %s"), nrow, n, "gmax");
// TODO rework gmax in the same way as gmin and remove this *update
char *update = (char *)R_alloc(ngrp, sizeof(char));
for (int i=0; i<ngrp; i++) update[i] = 0;
int protecti=0;
switch(TYPEOF(x)) {
case LGLSXP: case INTSXP:
ans = PROTECT(allocVector(INTSXP, ngrp)); protecti++;
for (i=0; i<ngrp; i++) INTEGER(ans)[i] = 0;
if (!LOGICAL(narm)[0]) { // simple case - deal in a straightforward manner first
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (INTEGER(x)[ix] != NA_INTEGER && INTEGER(ans)[thisgrp] != NA_INTEGER) {
if ( update[thisgrp] != 1 || INTEGER(ans)[thisgrp] < INTEGER(x)[ix] ) {
INTEGER(ans)[thisgrp] = INTEGER(x)[ix];
if (update[thisgrp] != 1) update[thisgrp] = 1;
}
} else INTEGER(ans)[thisgrp] = NA_INTEGER;
}
} else {
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (INTEGER(x)[ix] != NA_INTEGER) {
if ( update[thisgrp] != 1 || INTEGER(ans)[thisgrp] < INTEGER(x)[ix] ) {
INTEGER(ans)[thisgrp] = INTEGER(x)[ix];
if (update[thisgrp] != 1) update[thisgrp] = 1;
}
} else {
if (update[thisgrp] != 1) {
INTEGER(ans)[thisgrp] = NA_INTEGER;
}
}
}
for (i=0; i<ngrp; i++) {
if (update[i] != 1) {// equivalent of INTEGER(ans)[thisgrp] == NA_INTEGER
warning(_("No non-missing values found in at least one group. Coercing to numeric type and returning 'Inf' for such groups to be consistent with base"));
ans = PROTECT(coerceVector(ans, REALSXP)); protecti++;
for (i=0; i<ngrp; i++) {
if (update[i] != 1) REAL(ans)[i] = -R_PosInf;
}
break;
}
}
}
break;
case STRSXP:
ans = PROTECT(allocVector(STRSXP, ngrp)); protecti++;
for (i=0; i<ngrp; i++) SET_STRING_ELT(ans, i, mkChar(""));
if (!LOGICAL(narm)[0]) { // simple case - deal in a straightforward manner first
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (STRING_ELT(x,ix) != NA_STRING && STRING_ELT(ans, thisgrp) != NA_STRING) {
if ( update[thisgrp] != 1 || strcmp(CHAR(STRING_ELT(ans, thisgrp)), CHAR(STRING_ELT(x,ix))) < 0 ) {
SET_STRING_ELT(ans, thisgrp, STRING_ELT(x, ix));
if (update[thisgrp] != 1) update[thisgrp] = 1;
}
} else SET_STRING_ELT(ans, thisgrp, NA_STRING);
}
} else {
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if (STRING_ELT(x, ix) != NA_STRING) {
if ( update[thisgrp] != 1 || strcmp(CHAR(STRING_ELT(ans, thisgrp)), CHAR(STRING_ELT(x, ix))) < 0 ) {
SET_STRING_ELT(ans, thisgrp, STRING_ELT(x, ix));
if (update[thisgrp] != 1) update[thisgrp] = 1;
}
} else {
if (update[thisgrp] != 1) {
SET_STRING_ELT(ans, thisgrp, NA_STRING);
}
}
}
for (i=0; i<ngrp; i++) {
if (update[i] != 1) {// equivalent of INTEGER(ans)[thisgrp] == NA_INTEGER
warning(_("No non-missing values found in at least one group. Returning 'NA' for such groups to be consistent with base"));
break;
}
}
}
break;
case REALSXP:
ans = PROTECT(allocVector(REALSXP, ngrp)); protecti++;
for (i=0; i<ngrp; i++) REAL(ans)[i] = 0;
if (!LOGICAL(narm)[0]) {
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if ( !ISNA(REAL(x)[ix]) && !ISNA(REAL(ans)[thisgrp]) ) {
if ( update[thisgrp] != 1 || REAL(ans)[thisgrp] < REAL(x)[ix] ||
(ISNAN(REAL(x)[ix]) && !ISNAN(REAL(ans)[thisgrp])) ) { // #1461
REAL(ans)[thisgrp] = REAL(x)[ix];
if (update[thisgrp] != 1) update[thisgrp] = 1;
}
} else REAL(ans)[thisgrp] = NA_REAL;
}
} else {
for (i=0; i<n; i++) {
thisgrp = grp[i];
ix = (irowslen == -1) ? i : irows[i]-1;
if ( !ISNAN(REAL(x)[ix]) ) { // #1461
if ( update[thisgrp] != 1 || REAL(ans)[thisgrp] < REAL(x)[ix] ) {
REAL(ans)[thisgrp] = REAL(x)[ix];
if (update[thisgrp] != 1) update[thisgrp] = 1;
}
} else {
if (update[thisgrp] != 1) {
REAL(ans)[thisgrp] = -R_PosInf;
}
}
}
// everything taken care of already. Just warn if all NA groups have occurred at least once
for (i=0; i<ngrp; i++) {
if (update[i] != 1) { // equivalent of REAL(ans)[thisgrp] == -R_PosInf
warning(_("No non-missing values found in at least one group. Returning '-Inf' for such groups to be consistent with base"));
break;
}
}
}
break;
case CPLXSXP:
error(_("Type 'complex' has no well-defined max"));
break;
default:
error(_("Type '%s' not supported by GForce max (gmax). Either add the prefix base::max(.) or turn off GForce optimization using options(datatable.optimize=1)"), type2char(TYPEOF(x)));
}
copyMostAttrib(x, ans); // all but names,dim and dimnames. And if so, we want a copy here, not keepattr's SET_ATTRIB.
UNPROTECT(protecti);
// Rprintf(_("this gmax took %8.3f\n"), 1.0*(clock()-start)/CLOCKS_PER_SEC);
return(ans);
}
// gmedian, always returns numeric type (to avoid as.numeric() wrap..)
SEXP gmedian(SEXP x, SEXP narmArg) {
if (!isLogical(narmArg) || LENGTH(narmArg)!=1 || LOGICAL(narmArg)[0]==NA_LOGICAL) error(_("na.rm must be TRUE or FALSE"));
if (!isVectorAtomic(x)) error(_("GForce median can only be applied to columns, not .SD or similar. To find median of all items in a list such as .SD, either add the prefix stats::median(.SD) or turn off GForce optimization using options(datatable.optimize=1). More likely, you may be looking for 'DT[,lapply(.SD,median),by=,.SDcols=]'"));
if (inherits(x, "factor")) error(_("median is not meaningful for factors."));
const bool isInt64 = INHERITS(x, char_integer64), narm = LOGICAL(narmArg)[0];
int n = (irowslen == -1) ? length(x) : irowslen;
if (nrow != n) error(_("nrow [%d] != length(x) [%d] in %s"), nrow, n, "gmedian");
SEXP ans = PROTECT(allocVector(REALSXP, ngrp));
double *ansd = REAL(ans);
switch(TYPEOF(x)) {
case REALSXP: {
double *subd = REAL(PROTECT(allocVector(REALSXP, maxgrpn))); // allocate once upfront and reuse
int64_t *xi64 = (int64_t *)REAL(x);
double *xd = REAL(x);
for (int i=0; i<ngrp; ++i) {
int thisgrpsize = grpsize[i], nacount=0;
for (int j=0; j<thisgrpsize; ++j) {
int k = ff[i]+j-1;
if (isunsorted) k = oo[k]-1;
k = (irowslen == -1) ? k : irows[k]-1;
if (isInt64 ? xi64[k]==NA_INTEGER64 : ISNAN(xd[k])) nacount++;
else subd[j-nacount] = xd[k];
}
thisgrpsize -= nacount; // all-NA is returned as NA_REAL via n==0 case inside *quickselect
ansd[i] = (nacount && !narm) ? NA_REAL : (isInt64 ? i64quickselect((void *)subd, thisgrpsize) : dquickselect(subd, thisgrpsize));
}}
break;
case LGLSXP: case INTSXP: {
int *subi = INTEGER(PROTECT(allocVector(INTSXP, maxgrpn)));
int *xi = INTEGER(x);
for (int i=0; i<ngrp; i++) {
int thisgrpsize = grpsize[i], nacount=0;
for (int j=0; j<thisgrpsize; ++j) {
int k = ff[i]+j-1;
if (isunsorted) k = oo[k]-1;
k = (irowslen == -1) ? k : irows[k]-1;
if (xi[k]==NA_INTEGER) nacount++;
else subi[j-nacount] = xi[k];
}
ansd[i] = (nacount && !narm) ? NA_REAL : iquickselect(subi, thisgrpsize-nacount);
}}
break;
default:
error(_("Type '%s' not supported by GForce median (gmedian). Either add the prefix stats::median(.) or turn off GForce optimization using options(datatable.optimize=1)"), type2char(TYPEOF(x)));
}
if (!isInt64) copyMostAttrib(x, ans);
// else the integer64 class needs to be dropped since double is always returned by gmedian
UNPROTECT(2); // ans, subd|subi
return ans;
}
SEXP glast(SEXP x) {