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SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp
#pragma omp parallel for num_threads(nthreads)
100
IntegerVector gsv = gs; if(ng != gsv.size()) stop("ng must match length(gs)"); <LOOP-START>for(int i = 0; i < ng; ++i) { // if(gsv[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them."); if(gsv[i] > 0) gmap[i+1] = std::vector<double> (gsv[i]); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp
#pragma omp parallel for num_threads(nthreads)
100
r(int i = 0; i != lx1; ++i) if(nisnan(column[i])) gmap[g[i]][gcount[g[i]]++] = column[i]; <LOOP-START>for(int i = 1; i < ngp; ++i) { if(gcount[i] != 0) { int n = gcount[i], nth = lower ? (n-1)*Q : n*Q; auto begin = gmap[i].begin(), mid = begin + nth, end = begin + n; std::nth_element(begin, mid, end); nthj[i-1] = (tiesmean && n%2 == 0) ? (*(mid) + *(std::min_element(mid+1, end)))*0.5 : *(mid); } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp
#pragma omp parallel for num_threads(nthreads)
100
} else { gmap[g[i]][gcount[g[i]]++] = column[i]; } } <LOOP-START>for(int i = 0; i < ng; ++i) { if(isnan2(nthj[i]) || gcount[i+1] == 0) continue; int n = gcount[i+1], nth = lower ? (n-1)*Q : n*Q; auto begin = gmap[i+1].begin(), mid = begin + nth, end = begin + n; std::nth_element(begin, mid, end); nthj[i] = (tiesmean && n%2 == 0) ? (*(mid) + *(std::min_element(mid+1, end)))*0.5 : *(mid); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
} for(int i = 0; i != l; ++i) gmap[pg[i]][n[pg[i]]++] = x[i]; if(narm) { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { // const std::vector<storage_t>& temp = gmap[gr]; // wrap() // good ? // const Vector<RTYPE>& // better for character strings sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); // wrap(temp) int i = 0, s = hash.n, end = s-1, max = 1, index; // n[s+1] // fastest ? use n ? while(isnanT(hash.src[i]) && i!=end) ++i; out[gr] = hash.src[i]; // good if(i!=end) { std::vector<int> n(s+1); // = no_init_vector // better for valgrind for( ; i != s; ++i) { storage_t val = hash.src[i]; if(isnanT(val)) continue; addr = hash.get_addr(val); index = hash.data[addr]; while(index && hash.not_equal(hash.src[index - 1], val)) { ++addr; if(addr == static_cast<unsigned int>(hash.m)) addr = 0; index = hash.data[addr]; } if(!index) { hash.data[addr] = i+1; ++hash.size_; n[i+1] = 1; if(nfirstm && max == 1) { // Could also do this at the end in a separate loop. What is faster ? -> This seems better ! if(lastm) out[gr] = val; else if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } else { // if(++n[hash.data[addr]] > max) { // good, or create int index // max = n[hash.data[addr]]; // out[gr] = val; // } // index = hash.data[addr]; if(++n[index] >= max) { if(lastm || n[index] > max) { max = n[index]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } } // if(nfirstm && max == 1) { // Above seems better ! // if(minm) { // for(int i = 1; i != s; ++i) if(out[gr] > hash.src[i]) out[gr] = hash.src[i]; // } else { // for(int i = 1; i != s; ++i) if(out[gr] < hash.src[i]) out[gr] = hash.src[i]; // } // } } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
gr] = hash.src[i]; // } // } } } } else { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { // const std::vector<storage_t>& temp = gmap[gr]; // good ? // const Vector<RTYPE>& // wrap() sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); // wrap(temp) out[gr] = hash.src[0]; int s = hash.n, max = 1, index; // n[s+1] // fastest ? use n ? and reset partially ? std::vector<int> n(s+1); // = no_init_vector // better for valgrind for(int i = 0; i != s; ++i) { storage_t val = hash.src[i]; addr = hash.get_addr(val); index = hash.data[addr]; while(index && hash.not_equal(hash.src[index - 1], val)) { ++addr; if(addr == static_cast<unsigned int>(hash.m)) addr = 0; index = hash.data[addr]; } if(!index) { hash.data[addr] = i+1; ++hash.size_; n[i+1] = 1; if(nfirstm && max == 1) { // Could also do this at the end in a separate loop. What is faster ? -> This seems better ! if(lastm) out[gr] = val; else if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } else { // if(++n[hash.data[addr]] > max) { // good, or create int index // max = n[hash.data[addr]]; // out[gr] = val; // } if(++n[index] >= max) { if(lastm || n[index] > max) { max = n[index]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } } // if(nfirstm && max == 1) { // Above seems better ! // if(minm) { // for(int i = 1; i != s; ++i) if(out[gr] > hash.src[i]) out[gr] = hash.src[i]; // } else { // for(int i = 1; i != s; ++i) if(out[gr] < hash.src[i]) out[gr] = hash.src[i]; // } // } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
gmap[gi][n[gi]] = x[i]; wmap[gi][n[gi]++] = pwg[i]; } if(narm) { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { // const std::vector<storage_t>& temp = gmap[gr]; // good ? // const Vector<RTYPE>& // wrap() const std::vector<double>& wtemp = wmap[gr+1]; sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); // wrap(temp) int i = 0, s = hash.n, end = s-1, index; double max = DBL_MIN; // n[s+1] while((isnanT(hash.src[i]) || std::isnan(wtemp[i])) && i!=end) ++i; out[gr] = hash.src[i]; // good ! if(i!=end) { std::vector<double> n(s+1); // = no_init_vector // better for valgrind for( ; i != s; ++i) { storage_t val = hash.src[i]; if(isnanT(val) || std::isnan(wtemp[i])) continue; addr = hash.get_addr(val); index = hash.data[addr]; while(index && hash.not_equal(hash.src[index - 1], val)) { ++addr; if(addr == static_cast<unsigned int>(hash.m)) addr = 0; index = hash.data[addr]; } if(!index) { hash.data[addr] = i+1; ++hash.size_; n[i+1] = wtemp[i]; if(wtemp[i] >= max) { // necessary, because second loop only entered for more than one occurrence of the same value if(lastm || wtemp[i] > max) { max = wtemp[i]; out[gr] = val; } else if(nfirstm) { // Could also do this at the end in a separate loop. What is faster ?? if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } else { n[index] += wtemp[i]; // if(n[index] > max) { // max = n[index]; // out[gr] = val; // } if(n[index] >= max) { if(lastm || n[index] > max) { max = n[index]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } } } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
} } } } } } } else { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { // const std::vector<storage_t>& temp = gmap[gr]; // good ? // const Vector<RTYPE>& // wrap() const std::vector<double>& wtemp = wmap[gr+1]; sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); // wrap(temp) out[gr] = hash.src[0]; int s = hash.n, index; // fastest ? use n ? and reset partially ? double max = DBL_MIN; // n[s+1]; std::vector<double> n(s+1); // = no_init_vector // better for valgrind for(int i = 0; i != s; ++i) { if(std::isnan(wtemp[i])) continue; storage_t val = hash.src[i]; addr = hash.get_addr(val); index = hash.data[addr]; while(index && hash.not_equal(hash.src[index - 1], val)) { ++addr; if(addr == static_cast<unsigned int>(hash.m)) addr = 0; index = hash.data[addr]; } if(!index) { hash.data[addr] = i+1; ++hash.size_; n[i+1] = wtemp[i]; if(wtemp[i] >= max) { // necessary, because second loop only entered for more than one occurrence of the same value if(lastm || wtemp[i] > max) { max = wtemp[i]; out[gr] = val; } else if(nfirstm) { // Could also do this at the end in a separate loop. What is faster ?? if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } else { n[index] += wtemp[i]; // if(n[index] > max) { // max = n[index]; // out[gr] = val; // } if(n[index] >= max) { if(lastm || n[index] > max) { max = n[index]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
} for(int i = 0; i != l; ++i) gmap[pg[i]][n[pg[i]]++] = x[i]; if(narm) { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { const std::vector<int>& temp = gmap[gr+1]; int i = 0, s = temp.size(), end = s-1, max = 1; while(temp[i] == NA_INTEGER && i!=end) ++i; out[gr] = temp[i]; if(i!=end) { std::vector<int> n(nlevp); for( ; i != s; ++i) { val = temp[i]; if(val == NA_INTEGER) continue; if(++n[val] >= max) { if(lastm || n[val] > max) { max = n[val]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
} } } } } } } else { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { const std::vector<int>& temp = gmap[gr+1]; int tl = temp.size(), max = 1; std::vector<int> n(nlevp); out[gr] = temp[0]; for(int i = 0; i != tl; ++i) { val = temp[i]; if(val == NA_INTEGER) val = 0; if(++n[val] >= max) { if(lastm || n[val] > max) { max = n[val]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } if(out[gr] == 0) out[gr] = NA_INTEGER; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
gmap[gi][n[gi]] = x[i]; wmap[gi][n[gi]++] = pwg[i]; } if(narm) { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { const std::vector<int>& temp = gmap[gr+1]; const std::vector<double>& wtemp = wmap[gr+1]; int i = 0, s = temp.size(), end = s-1; double max = DBL_MIN; while((temp[i] == NA_INTEGER || std::isnan(wtemp[i])) && i!=end) ++i; out[gr] = temp[i]; if(i!=end) { std::vector<double> n(nlevp); for( ; i != s; ++i) { val = temp[i]; if(val == NA_INTEGER || std::isnan(wtemp[i])) continue; n[val] += wtemp[i]; if(n[val] >= max) { if(lastm || n[val] > max) { max = n[val]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
} } } } } } } else { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { const std::vector<int>& temp = gmap[gr+1]; const std::vector<double>& wtemp = wmap[gr+1]; int tl = temp.size(); double max = DBL_MIN; std::vector<double> n(nlevp); out[gr] = temp[0]; for(int i = 0; i != tl; ++i) { if(std::isnan(wtemp[i])) continue; val = temp[i]; if(val == NA_INTEGER) val = 0; n[val] += wtemp[i]; if(n[val] >= max) { if(lastm || n[val] > max) { max = n[val]; out[gr] = val; } else if(nfirstm) { if(minm) { if(out[gr] > val) out[gr] = val; } else { if(out[gr] < val) out[gr] = val; } } } } if(out[gr] == 0) out[gr] = NA_INTEGER; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
= x.size(); List out(l); if(ng == 0 && nthreads > 1) { if(nthreads > l) nthreads = l; <LOOP-START>for(int j = 0; j < l; ++j) out[j] = fmodeCpp(x[j], ng, g, gs, w, narm, ret, 1); } else { for(int j = l; j--; ) out[j] = fmodeCpp(x[j], ng, g, gs, w, narm, ret, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fmode.cpp
#pragma omp parallel for num_threads(nthreads)
100
o_init_matrix(ng, col); if(ng == 0 && nthreads > 1) { if(nthreads > col) nthreads = col; <LOOP-START>for(int j = 0; j < col; ++j) out(_, j) = fmodeImpl<RTYPE>(x(_, j), ng, g, gs, w, narm, ret, 1); } else { for(int j = col; j--; ) out(_, j) = fmodeImpl<RTYPE>(x(_, j), ng, g, gs, w, narm, ret, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
tm1 = out.begin()-1; if(Rf_isNull(gs)) { for(int i = 0; i != l; ++i) ++outm1[g[i]]; <LOOP-START>for(int i = 0; i < ng; ++i) { // if(out[i] == 0) stop("Group size of 0 encountered. This is probably due to unused factor levels. Use fdroplevels(f) to drop them."); if(out[i] > 0) { gmap[i+1] = std::vector<storage_t> (out[i]); out[i] = 0; } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
{ IntegerVector gsv = gs; if(ng != gsv.size()) stop("ng must match length(gs)"); <LOOP-START>for(int i = 0; i < ng; ++i) { // if(gsv[i] == 0) stop("Group size of 0 encountered. This is probably due to unused factor levels. Use fdroplevels(f) to drop them."); if(gsv[i] > 0) gmap[i+1] = std::vector<storage_t> (gsv[i]); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
} } for(int i = 0; i != l; ++i) gmap[g[i]][outm1[g[i]]++] = x[i]; if(narm) { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { if(out[gr] == 0) continue; // const std::vector<storage_t>& temp = gmap[gr+1]; // good ? // const Vector<RTYPE>& // wrap() sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); // temp for(int i = hash.n; i--; ) { storage_t val = hash.src[i]; if(isnanT(val)) continue; addr = hash.get_addr(val); while(hash.data[addr] && hash.not_equal(hash.src[hash.data[addr] - 1], val)) { ++addr; if(addr == static_cast<unsigned int>(hash.m)) addr = 0; } if(!hash.data[addr]) { hash.data[addr] = i+1; ++hash.size_; } } out[gr] = hash.size_; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
++hash.size_; } } out[gr] = hash.size_; } } else { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { if(out[gr] == 0) continue; sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); hash.fill(); out[gr] = hash.size_; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
out.begin()-1; if(Rf_isNull(gs)) { for(int i = 0; i != l; ++i) ++outm1[g[i]]; <LOOP-START>for(int i = 0; i < ng; ++i) { // if(out[i] == 0) stop("Group size of 0 encountered. This is probably due to unused factor levels. Use fdroplevels(f) to drop them."); if(out[i] > 0) { gmap[i+1] = std::vector<int> (out[i]); out[i] = 0; } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
IntegerVector gsv = gs; if(ng != gsv.size()) stop("ng must match length(gs)"); <LOOP-START>for(int i = 0; i < ng; ++i) { // if(gsv[i] == 0) stop("Group size of 0 encountered. This is probably due to unused factor levels. Use fdroplevels(f) to drop them."); if(gsv[i] > 0) gmap[i+1] = std::vector<int> (gsv[i]); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
} for(int i = 0; i != l; ++i) gmap[g[i]][outm1[g[i]]++] = x[i]; if(narm) { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { if(out[gr] == 0) continue; const std::vector<int>& temp = gmap[gr+1]; n = 1; std::vector<bool> uxp(nlevp, true); for(int i = temp.size(); i--; ) { if(temp[i] != NA_INTEGER && uxp[temp[i]]) { // save xi = x[i] ? Faster ? uxp[temp[i]] = false; if(++n == nlevp) break; } } out[gr] = n - 1; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
nlevp) break; } } out[gr] = n - 1; } } else { <LOOP-START>for(int gr = 0; gr < ng; ++gr) { if(out[gr] == 0) continue; const std::vector<int>& temp = gmap[gr+1]; bool anyNA = false; n = 1; std::vector<bool> uxp(nlevp, true); for(int i = temp.size(); i--; ) { if(temp[i] == NA_INTEGER) { anyNA = true; continue; } if(uxp[temp[i]]) { // save xi = x[i] ? Faster ? uxp[temp[i]] = false; if(++n == nlevp && anyNA) break; } } out[gr] = n + anyNA - 1; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
> 1 && ((ng == 0 && l > 1) || (ng != 0 && nthreads < l))) { if(nthreads > l) nthreads = l; <LOOP-START>for(int j = 0; j < l; ++j) out[j] = fndistinctCpp(x[j], ng, g, gs, narm, 1); } else { for(int j = l; j--; ) out[j] = fndistinctCpp(x[j], ng, g, gs, narm, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
ntegerVector out = no_init_vector(col); if(nthreads > col) nthreads = col; if(narm) { <LOOP-START>for(int j = 0; j < col; ++j) { // ConstMatrixColumn<RTYPE> column = x(_ , j); sugar::IndexHash<RTYPE> hash(wrap(x(_ , j))); // wrap(column) // why wrap needed ? for(int i = 0; i != l; ++i) { storage_t val = hash.src[i]; if(isnanT(val)) continue; addr = hash.get_addr(val); while(hash.data[addr] && hash.not_equal(hash.src[hash.data[addr] - 1], val)) { ++addr; if(addr == static_cast<unsigned int>(hash.m)) addr = 0; } if(!hash.data[addr]) { hash.data[addr] = i+1; ++hash.size_; } } out[j] = hash.size_; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
++hash.size_; } } out[j] = hash.size_; } } else { <LOOP-START>for(int j = 0; j < col; ++j) { // ConstMatrixColumn<RTYPE> column = x(_ , j); sugar::IndexHash<RTYPE> hash(wrap(x(_ , j))); // wrap(column) // why wrap needed ? hash.fill(); out[j] = hash.size_; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
ll(gs)) { // memset(n, 0, sizeof(int)*ng); for(int i = 0; i != l; ++i) ++n[g[i]]; <LOOP-START>for(int i = 1; i < ngp; ++i) { // if(n[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them."); if(n[i] > 0) gmap[i] = std::vector<storage_t> (n[i]); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
{ IntegerVector gsv = gs; if(ng != gsv.size()) stop("ng must match length(gs)"); <LOOP-START>for(int i = 0; i < ng; ++i) { // if(gsv[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them."); if(gsv[i] > 0) gmap[i+1] = std::vector<storage_t> (gsv[i]); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
i != l; ++i) gmap[g[i]][n[g[i]]++] = column[i]; // reading in all the values. Better way ? <LOOP-START>for(int gr = 0; gr < ng; ++gr) { if(n[gr+1] == 0) continue; // const std::vector<storage_t>& temp = gmap[gr+1]; // good ? // const Vector<RTYPE>& // wrap() sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); // wrap(temp) for(int i = hash.n; i--; ) { storage_t val = hash.src[i]; if(isnanT(val)) continue; addr = hash.get_addr(val); while(hash.data[addr] && hash.not_equal(hash.src[hash.data[addr] - 1], val)) { ++addr; if(addr == static_cast<unsigned int>(hash.m)) addr = 0; } if(!hash.data[addr]) { hash.data[addr] = i+1; ++hash.size_; } } outj[gr] = hash.size_; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.7.6 - 1.8.0/fndistinct.cpp
#pragma omp parallel for num_threads(nthreads)
100
i != l; ++i) gmap[g[i]][n[g[i]]++] = column[i]; // reading in all the values. Better way ? <LOOP-START>for(int gr = 0; gr < ng; ++gr) { if(n[gr+1] == 0) continue; sugar::IndexHash<RTYPE> hash(wrap(gmap[gr+1])); hash.fill(); outj[gr] = hash.size_; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
ing range_str"); // # nocov // savetl_init() has already been called at the start of forder // <LOOP-START>for(int i=0; i<n; i++) { SEXP s = x[i]; if (s==NA_STRING) { // #pragma omp atomic update na_count++; continue; } if (TRUELENGTH(s)<0) continue; // seen this group before // #pragma omp critical if (TRUELENGTH(s)>=0) { // another thread may have set it while I was waiting, so check it again if (TRUELENGTH(s)>0) // save any of R's own usage of tl (assumed positive, so we can both count and save in one scan), to restore savetl(s); // afterwards. From R 2.14.0, tl is initialized to 0, prior to that it was random so this step saved too much. // now save unique SEXP in ustr so i) we can loop through them afterwards and reset TRUELENGTH to 0 and ii) sort uniques when sorting too if (ustr_alloc<=ustr_n) { ustr_alloc = (ustr_alloc==0) ? 16384 : ustr_alloc*2; // small initial guess, negligible time to alloc 128KB (32 pages) if (ustr_alloc>n) ustr_alloc = n; // clamp at n. Reaches n when fully unique (no dups) ustr = realloc(ustr, ustr_alloc * sizeof(SEXP)); if (ustr==NULL) STOP("Unable to realloc %d * %d bytes in range_str", ustr_alloc, (int)sizeof(SEXP)); // # nocov } ustr[ustr_n++] = s; SET_TRUELENGTH(s, -ustr_n); // unique in any order is fine. first-appearance order is achieved later in count_group if (LENGTH(s)>ustr_maxlen) ustr_maxlen=LENGTH(s); if (!anyneedutf8 && NEED2UTF8(s)) anyneedutf8=true; } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
SEXP ans = PROTECT(allocVector(INTSXP, nrow)); n_protect++; anso = INTEGER(ans); TEND(0) // <LOOP-START>for (int i=0; i<nrow; i++) anso[i]=i+1; // gdb 8.1.0.20180409-git very slow here, oddly TEND(1) savetl_init(); // from now on use Error not error int ncol=length(by); int keyAlloc = (ncol+n_cplx)*8 + 1; // +1 for NULL to mark end; calloc to initialize with NULLs key = calloc(keyAlloc, sizeof(uint8_t *)); // needs to be before loop because part II relies on part I, column-by-column. if (!key) STOP("Unable to allocate %llu bytes of working memory", (unsigned long long)(keyAlloc*sizeof(uint8_t *))); // # nocov nradix=0; // the current byte we're writing this column to; might be squashing into it (spare>0) int spare=0; // the amount of bits remaining on the right of the current nradix byte bool isReal=false; bool complexRerun = false; // see comments below in CPLXSXP case SEXP CplxPart = R_NilValue; if (n_cplx) { CplxPart=PROTECT(allocVector(REALSXP, nrow)); n_protect++; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
switch(TYPEOF(x)) { case INTSXP : case LGLSXP : { int32_t *xd = INTEGER(x); // <LOOP-START>for (int i=0; i<nrow; i++) { uint64_t elem=0; if (xd[i]==NA_INTEGER) { // TODO: go branchless if na_count==0 if (nalast==-1) anso[i]=0; elem = naval; } else { elem = xd[i] ^ 0x80000000u; } WRITE_KEY }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
EALSXP : if (inherits(x, "integer64")) { int64_t *xd = (int64_t *)REAL(x); // <LOOP-START>for (int i=0; i<nrow; i++) { uint64_t elem=0; if (xd[i]==INT64_MIN) { if (nalast==-1) anso[i]=0; elem = naval; } else { elem = xd[i] ^ 0x8000000000000000u; } WRITE_KEY }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
ion (skip bytes/mult by 10,100 etc) as currently it's often 6-8 bytes even for 3.14,3.15 // <LOOP-START>for (int i=0; i<nrow; i++) { uint64_t elem=0; if (!R_FINITE(xd[i])) { if (isinf(xd[i])) elem = signbit(xd[i]) ? min-1 : max+1; else { if (nalast==-1) anso[i]=0; // for both NA and NaN elem = ISNA(xd[i]) ? naval : nanval; } } else { elem = dtwiddle(xd, i); // TODO: could avoid twiddle() if all positive finite which could be known from range_d. // also R_FINITE is repeated within dtwiddle() currently, wastefully given the if() above } WRITE_KEY }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
ITE_KEY } } break; case STRSXP : { SEXP *xd = STRING_PTR(x); // <LOOP-START>for (int i=0; i<nrow; i++) { uint64_t elem=0; if (xd[i]==NA_STRING) { if (nalast==-1) anso[i]=0; elem = naval; } else { elem = -TRUELENGTH(xd[i]); } WRITE_KEY }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
anso will contain 0's for the NAs and will be considered not-sorted. bool stop = false; // <LOOP-START>for (int i=0; i<nrow; i++) { if (stop) continue; if (anso[i]!=i+1) stop=true; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
if (!TMP) STOP("Unable to allocate TMP for my_n=%d items in parallel batch counting", my_n); // <LOOP-START>for (int batch=0; batch<nBatch; batch++) { const int *restrict my_starts = starts + batch*256; const uint16_t *restrict my_counts = counts + batch*256; const int *restrict osub = anso + from + batch*batchSize; // the groups sit here contiguously const uint8_t *restrict byte = ugrps + batch*256; // in appearance order always logged here in ugrps const int my_ngrp = ngrps[batch]; for (int i=0; i<my_ngrp; i++, byte++) { const uint16_t len = my_counts[*byte]; memcpy(TMP+my_starts[*byte], osub, len*sizeof(int)); osub += len; } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for num_threads(getDTthreads())
100
int currently (in future 8). To save team startup cost (but unlikely significant anyway) // <LOOP-START>for (int batch=0; batch<nBatch; batch++) { const int *restrict my_starts = starts + batch*256; const uint16_t *restrict my_counts = counts + batch*256; const uint8_t *restrict ksub = key[radix+1+r] + from + batch*batchSize; // the groups sit here contiguosly const uint8_t *restrict byte = ugrps + batch*256; // in appearance order always logged here in ugrps const int my_ngrp = ngrps[batch]; for (int i=0; i<my_ngrp; i++, byte++) { const uint16_t len = my_counts[*byte]; memcpy((uint8_t *)TMP + my_starts[*byte], ksub, len); ksub += len; } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for ordered schedule(dynamic) num_threads(getDTthreads())
100
o start a parallel team and there will be no nestedness here either. if (retgrp) { // <LOOP-START>for (int i=0; i<ngrp; i++) { int start = from + starts[ugrp[i]]; radix_r(start, start+my_gs[i]-1, radix+1); // #pragma omp ordered flush(); }<LOOP-END> <OMP-START>#pragma omp parallel for ordered schedule(dynamic) num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/misc/legacy/sorted out 1.1.0 - 1.2.0/data.table_forder.c
#pragma omp parallel for schedule(dynamic) num_threads(getDTthreads())
100
// flush() is only relevant when retgrp==true so save the redundant ordered clause // <LOOP-START>for (int i=0; i<ngrp; i++) { int start = from + starts[ugrp[i]]; radix_r(start, start+my_gs[i]-1, radix+1); }<LOOP-END> <OMP-START>#pragma omp parallel for schedule(dynamic) num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
tithreaded... switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_double(px + pst[gr], po, pgs[gr], 1, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_int(px + pst[gr], po, pgs[gr], 1, narm, ret, Q); break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_int(px + pst[gr], po, pgs[gr], 1, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } else { // Not sorted. Perhaps reordering x is faster? switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_double(px, po + pst[gr], pgs[gr], 0, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_int(px, po + pst[gr], pgs[gr], 0, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
ng x is faster? switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x); <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_double(px, po + pst[gr], pgs[gr], 0, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_int(px, po + pst[gr], pgs[gr], 0, narm, ret, Q); break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_int(px, po + pst[gr], pgs[gr], 0, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } if(ATTRIB(x) != R_NilValue && !(isObject(x) && inherits(x, "ts"))) copyMostAttrib(x, res); UNPROTECT(1); return res; } // Expects pointer po to be decremented by 1 SEXP nth_g_impl_noalloc(SEXP x, int ng, int *pgs, int *po, int *pst, int sorted, int narm, int ret, double Q, void* x_cc) { SEXP res = PROTECT(allocVector(REALSXP, ng)); double *pres = REAL(res); if(sorted) { switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x)-1; for(int gr = 0; gr != ng; ++gr) pres[gr] = nth_double_noalloc(px + pst[gr], po, x_cc, pgs[gr], 1, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; for(int gr = 0; gr != ng; ++gr) pres[gr] = nth_int_noalloc(px + pst[gr], po, x_cc, pgs[gr], 1, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } else { switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x); for(int gr = 0; gr != ng; ++gr) pres[gr] = nth_double_noalloc(px, po + pst[gr], x_cc, pgs[gr], 0, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); for(int gr = 0; gr != ng; ++gr) pres[gr] = nth_int_noalloc(px, po + pst[gr], x_cc, pgs[gr], 0, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } if(ATTRIB(x) != R_NilValue && !(isObject(x) && inherits(x, "ts"))) copyMostAttrib(x, res); UNPROTECT(1); return res; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
e *pres = REAL(res); switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_double_ord(px, po + pst[gr], pgs[gr], narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_int_ord(px, po + pst[gr], pgs[gr], narm, ret, Q); break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = nth_int_ord(px, po + pst[gr], pgs[gr], narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } if(ATTRIB(x) != R_NilValue && !(isObject(x) && inherits(x, "ts"))) copyMostAttrib(x, res); UNPROTECT(1); return res; } // Expects pointers pw and po to be decremented by 1 SEXP w_nth_g_ord_impl(SEXP x, double *pw, int ng, int *pgs, int *po, int *pst, int narm, int ret, double Q, int nthreads) { if(nthreads > ng) nthreads = ng; SEXP res = PROTECT(allocVector(REALSXP, ng)); double *pres = REAL(res); switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_double_ord(px, pw, po + pst[gr], DBL_MIN, pgs[gr], narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_ord(px, pw, po + pst[gr], DBL_MIN, pgs[gr], narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } if(ATTRIB(x) != R_NilValue && !(isObject(x) && inherits(x, "ts"))) copyMostAttrib(x, res); UNPROTECT(1); return res; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
e *pres = REAL(res); switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_double_ord(px, pw, po + pst[gr], DBL_MIN, pgs[gr], narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_ord(px, pw, po + pst[gr], DBL_MIN, pgs[gr], narm, ret, Q); break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_ord(px, pw, po + pst[gr], DBL_MIN, pgs[gr], narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } if(ATTRIB(x) != R_NilValue && !(isObject(x) && inherits(x, "ts"))) copyMostAttrib(x, res); UNPROTECT(1); return res; } // Expects pointers pw and po to be decremented by 1 SEXP w_nth_g_qsort_impl(SEXP x, double *pw, int ng, int *pgs, int *po, int *pst, int sorted, int narm, int ret, double Q, int nthreads) { if(nthreads > ng) nthreads = ng; SEXP res = PROTECT(allocVector(REALSXP, ng)); double *pres = REAL(res); if(sorted) { // sorted by groups: need to offset both px and pw switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_double_qsort(px + pst[gr], pw + pst[gr], po, DBL_MIN, pgs[gr], 1, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_qsort(px + pst[gr], pw + pst[gr], po, DBL_MIN, pgs[gr], 1, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } else { switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_double_qsort(px, pw, po + pst[gr], DBL_MIN, pgs[gr], 0, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_qsort(px, pw, po + pst[gr], DBL_MIN, pgs[gr], 0, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } if(ATTRIB(x) != R_NilValue && !(isObject(x) && inherits(x, "ts"))) copyMostAttrib(x, res); UNPROTECT(1); return res; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
oth px and pw switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_double_qsort(px + pst[gr], pw + pst[gr], po, DBL_MIN, pgs[gr], 1, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_qsort(px + pst[gr], pw + pst[gr], po, DBL_MIN, pgs[gr], 1, narm, ret, Q); break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x)-1; <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_qsort(px + pst[gr], pw + pst[gr], po, DBL_MIN, pgs[gr], 1, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } else { switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_double_qsort(px, pw, po + pst[gr], DBL_MIN, pgs[gr], 0, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_qsort(px, pw, po + pst[gr], DBL_MIN, pgs[gr], 0, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
} } else { switch(TYPEOF(x)) { case REALSXP: { double *px = REAL(x); <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_double_qsort(px, pw, po + pst[gr], DBL_MIN, pgs[gr], 0, narm, ret, Q); break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_qsort(px, pw, po + pst[gr], DBL_MIN, pgs[gr], 0, narm, ret, Q); break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
break; } case INTSXP: case LGLSXP: { int *px = INTEGER(x); <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = w_nth_int_qsort(px, pw, po + pst[gr], DBL_MIN, pgs[gr], 0, narm, ret, Q); break; } default: error("Not Supported SEXP Type: '%s'", type2char(TYPEOF(x))); } } if(ATTRIB(x) != R_NilValue && !(isObject(x) && inherits(x, "ts"))) copyMostAttrib(x, res); UNPROTECT(1); return res; } // Functions for Export -------------------------------------------------------- int Rties2int(SEXP x) { int tx = TYPEOF(x); if(tx == INTSXP || tx == REALSXP || tx == LGLSXP) { int ret = asInteger(x); if(ret < 1 || ret > 9 || ret == 4) error("ties must be 1, 2, 3 or 5-9, you supplied: %d", ret); return ret; } if(tx != STRSXP) error("ties must be integer or character"); const char * r = CHAR(STRING_ELT(x, 0)); // translateCharUTF8() if(strcmp(r, "mean") == 0) return 1; if(strcmp(r, "min") == 0) return 2; if(strcmp(r, "max") == 0) return 3; if(strcmp(r, "q5") == 0) return 5; if(strcmp(r, "q6") == 0) return 6; if(strcmp(r, "q7") == 0) return 7; if(strcmp(r, "q8") == 0) return 8; if(strcmp(r, "q9") == 0) return 9; error("Unknown ties option: %s", r); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fnth_fmedian_fquantile.c
#pragma omp parallel for num_threads(nthreads)
100
\ } /* Multithreading: does not work with radixorder * } else { <LOOP-START>for(int j = 0; j < l; ++j) { int *pxo = (int *) Calloc(nrx, int); // num1radixsort(pxo, TRUE, FALSE, px[j]); // Probably cannot be parallelized, can try R_orderVector1() // R_orderVector1(pxo, nrx, px[j], TRUE, FALSE); // Also not thread safe, and also 0-indexed. // for(int i = 0; i < nrx; ++i) pxo[i] += 1; pout[j] = w_nth_ord_impl_dbl(px[j], pxo, pw, narm, ret, Q, h); Free(pxo); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)
100
int j = 1; sum = px[0]; while(ISNAN(sum) && j != l) sum = px[j++]; if(j != l) { <LOOP-START>for(int i = j; i < l; ++i) sum += NISNAN(px[i]) ? px[i] : 0.0; } else if(narm == 2) sum = 0.0; } else { sum = 0; #pragma omp parallel for simd num_threads(nthreads) reduction(+:sum) for(int i = 0; i < l; ++i) sum += px[i]; // Cannot have break statements in OpenMP for loop }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)
100
sum += NISNAN(px[i]) ? px[i] : 0.0; } else if(narm == 2) sum = 0.0; } else { sum = 0; <LOOP-START>for(int i = 0; i < l; ++i) sum += px[i]; // Cannot have break statements in OpenMP for loop } return sum; } // This is unsafe... // void fsum_double_g_omp_impl(double *restrict pout, double *restrict px, int ng, int *restrict pg, int narm, int l, int nthreads) { // if(narm) { // for(int i = ng; i--; ) pout[i] = NA_REAL; // #pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng]) // for(int i = 0; i < l; ++i) { // if(!ISNAN(px[i])) { // if(ISNAN(pout[pg[i]-1])) pout[pg[i]-1] = px[i]; // else pout[pg[i]-1] += px[i]; // } // } // } else { // memset(pout, 0, sizeof(double) * ng); // #pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng]) // shared(pout) // for(int i = 0; i < l; ++i) { // // #pragma omp atomic // pout[pg[i]-1] += px[i]; // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. // } // } // }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])
100
arm, int l, int nthreads) { // if(narm) { // for(int i = ng; i--; ) pout[i] = NA_REAL; // <LOOP-START>// for(int i = 0; i < l; ++i) { // if(!ISNAN(px[i])) { // if(ISNAN(pout[pg[i]-1])) pout[pg[i]-1] = px[i]; // else pout[pg[i]-1] += px[i]; // } // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])
100
-1] += px[i]; // } // } // } else { // memset(pout, 0, sizeof(double) * ng); // <LOOP-START>// for(int i = 0; i < l; ++i) { // // #pragma omp atomic // pout[pg[i]-1] += px[i]; // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng]) <OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)
100
hile(j!=l && (ISNAN(px[j]) || ISNAN(pw[j]))) ++j; if(j != l) { sum = px[j] * pw[j]; <LOOP-START>for(int i = j+1; i < l; ++i) sum += (NISNAN(px[i]) && NISNAN(pw[i])) ? px[i] * pw[i] : 0.0; } else sum = narm == 1 ? NA_REAL : 0.0; } else { sum = 0; #pragma omp parallel for simd num_threads(nthreads) reduction(+:sum) for(int i = 0; i < l; ++i) sum += px[i] * pw[i]; }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)
100
i])) ? px[i] * pw[i] : 0.0; } else sum = narm == 1 ? NA_REAL : 0.0; } else { sum = 0; <LOOP-START>for(int i = 0; i < l; ++i) sum += px[i] * pw[i]; } return sum; } // This is unsafe... // void fsum_weights_g_omp_impl(double *restrict pout, double *restrict px, int ng, int *restrict pg, double *restrict pw, int narm, int l, int nthreads) { // if(narm) { // for(int i = ng; i--; ) pout[i] = NA_REAL; // #pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng]) // for(int i = 0; i < l; ++i) { // if(ISNAN(px[i]) || ISNAN(pw[i])) continue; // if(ISNAN(pout[pg[i]-1])) pout[pg[i]-1] = px[i] * pw[i]; // else pout[pg[i]-1] += px[i] * pw[i]; // } // } else { // memset(pout, 0, sizeof(double) * ng); // #pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng]) // for(int i = 0; i < l; ++i) pout[pg[i]-1] += px[i] * pw[i]; // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. // } // }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])
100
arm, int l, int nthreads) { // if(narm) { // for(int i = ng; i--; ) pout[i] = NA_REAL; // <LOOP-START>// for(int i = 0; i < l; ++i) { // if(ISNAN(px[i]) || ISNAN(pw[i])) continue; // if(ISNAN(pout[pg[i]-1])) pout[pg[i]-1] = px[i] * pw[i]; // else pout[pg[i]-1] += px[i] * pw[i]; // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])
100
[i]-1] += px[i] * pw[i]; // } // } else { // memset(pout, 0, sizeof(double) * ng); // <LOOP-START>// for(int i = 0; i < l; ++i) pout[pg[i]-1] += px[i] * pw[i]; // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. // } // } // using long long internally is substantially faster than using doubles !! double fsum_int_impl(const int *restrict px, const int narm, const int l) { long long sum; if(narm) { int j = l-1; while(px[j] == NA_INTEGER && j!=0) --j; sum = (long long)px[j]; if(j == 0 && px[j] == NA_INTEGER) return narm == 1 ? NA_REAL : 0; for(int i = j; i--; ) if(px[i] != NA_INTEGER) sum += (long long)px[i]; } else { sum = 0; for(int i = 0; i != l; ++i) { if(px[i] == NA_INTEGER) return NA_REAL; // Need this, otherwise result is incorrect !! sum += (long long)px[i]; } } return (double)sum; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)
100
if(j == l && px[j-1] == NA_INTEGER) return narm == 1 ? NA_REAL : 0; sum = (long long)px[j]; <LOOP-START>for(int i = j+1; i < l; ++i) sum += px[i] != NA_INTEGER ? (long long)px[i] : 0; } else { if(px[0] == NA_INTEGER || px[l-1] == NA_INTEGER) return NA_REAL; sum = 0; #pragma omp parallel for simd num_threads(nthreads) reduction(+:sum) for(int i = 0; i < l; ++i) sum += (long long)px[i]; // Need this, else wrong result }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)
100
0; } else { if(px[0] == NA_INTEGER || px[l-1] == NA_INTEGER) return NA_REAL; sum = 0; <LOOP-START>for(int i = 0; i < l; ++i) sum += (long long)px[i]; // Need this, else wrong result } return (double)sum; } // This is unsafe... // void fsum_int_g_omp_impl(int *restrict pout, int *restrict px, int ng, int *restrict pg, int narm, int l, int nthreads) { // long long ckof; // if(narm) { // for(int i = ng; i--; ) pout[i] = NA_INTEGER; // int lsi; // #pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng]) // for(int i = 0; i < l; ++i) { // if(px[i] != NA_INTEGER) { // lsi = pout[pg[i]-1]; // if(lsi == NA_INTEGER) pout[pg[i]-1] = px[i]; // else { // ckof = (long long)lsi + px[i]; // if(ckof > INT_MAX || ckof <= INT_MIN) error("Integer overflow in one or more groups. Integers in R are bounded between 2,147,483,647 and -2,147,483,647. The sum within each group should be in that range."); // pout[pg[i]-1] = (int)ckof; // } // } // } // } else { // memset(pout, 0, sizeof(int) * ng); // int lsi; // #pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng]) // for(int i = 0; i < l; ++i) { // if(px[i] == NA_INTEGER) { // pout[pg[i]-1] = NA_INTEGER; // continue; // } // lsi = pout[pg[i]-1]; // if(lsi != NA_INTEGER) { // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. // ckof = (long long)lsi + px[i]; // if(ckof > INT_MAX || ckof <= INT_MIN) error("Integer overflow in one or more groups. Integers in R are bounded between 2,147,483,647 and -2,147,483,647. The sum within each group should be in that range."); // pout[pg[i]-1] = (int)ckof; // } // } // } // }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:sum)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])
100
ng ckof; // if(narm) { // for(int i = ng; i--; ) pout[i] = NA_INTEGER; // int lsi; // <LOOP-START>// for(int i = 0; i < l; ++i) { // if(px[i] != NA_INTEGER) { // lsi = pout[pg[i]-1]; // if(lsi == NA_INTEGER) pout[pg[i]-1] = px[i]; // else { // ckof = (long long)lsi + px[i]; // if(ckof > INT_MAX || ckof <= INT_MIN) error("Integer overflow in one or more groups. Integers in R are bounded between 2,147,483,647 and -2,147,483,647. The sum within each group should be in that range."); // pout[pg[i]-1] = (int)ckof; // } // } // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])
100
// } // } // } else { // memset(pout, 0, sizeof(int) * ng); // int lsi; // <LOOP-START>// for(int i = 0; i < l; ++i) { // if(px[i] == NA_INTEGER) { // pout[pg[i]-1] = NA_INTEGER; // continue; // } // lsi = pout[pg[i]-1]; // if(lsi != NA_INTEGER) { // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. // ckof = (long long)lsi + px[i]; // if(ckof > INT_MAX || ckof <= INT_MIN) error("Integer overflow in one or more groups. Integers in R are bounded between 2,147,483,647 and -2,147,483,647. The sum within each group should be in that range."); // pout[pg[i]-1] = (int)ckof; // } // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads) reduction(+:pout[:ng])<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
) pout[j] = fsum_double_impl(px + j*l, narm, l); } else if(col >= nthreads) { <LOOP-START>for(int j = 0; j < col; ++j) pout[j] = fsum_double_impl(px + j*l, narm, l); } else { for(int j = 0; j != col; ++j) pout[j] = fsum_double_omp_impl(px + j*l, narm, l, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
*l, ng, pg, narm, l); } else { if(nthreads > col) nthreads = col; <LOOP-START>for(int j = 0; j < col; ++j) fsum_double_g_impl(pout + j*ng, px + j*l, ng, pg, narm, l); } } break; } case INTSXP: { int *px = INTEGER(x); if(ng > 0) { int *pout = INTEGER(out); if(nthreads <= 1 || col == 1) { for(int j = 0; j != col; ++j) fsum_int_g_impl(pout + j*ng, px + j*l, ng, pg, narm, l); } else { if(nthreads > col) nthreads = col; #pragma omp parallel for num_threads(nthreads) for(int j = 0; j < col; ++j) fsum_int_g_impl(pout + j*ng, px + j*l, ng, pg, narm, l); } } else { double *restrict pout = REAL(out); int anyoutl = 0; if(nthreads <= 1) { for(int j = 0; j != col; ++j) { double sumj = fsum_int_impl(px + j*l, narm, l); if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; pout[j] = sumj; } } else if(col >= nthreads) { // If high-dimensional: column-level parallelism #pragma omp parallel for num_threads(nthreads) for(int j = 0; j < col; ++j) { double sumj = fsum_int_impl(px + j*l, narm, l); if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; pout[j] = sumj; } } else { for(int j = 0; j != col; ++j) { double sumj = fsum_int_omp_impl(px + j*l, narm, l, nthreads); if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; pout[j] = sumj; } } if(anyoutl == 0) { out = PROTECT(coerceVector(out, INTSXP)); matCopyAttr(out, x, Rdrop, ng); UNPROTECT(nprotect + 1); return out; } } break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
*l, ng, pg, narm, l); } else { if(nthreads > col) nthreads = col; <LOOP-START>for(int j = 0; j < col; ++j) fsum_int_g_impl(pout + j*ng, px + j*l, ng, pg, narm, l); } } else { double *restrict pout = REAL(out); int anyoutl = 0; if(nthreads <= 1) { for(int j = 0; j != col; ++j) { double sumj = fsum_int_impl(px + j*l, narm, l); if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; pout[j] = sumj; } } else if(col >= nthreads) { // If high-dimensional: column-level parallelism #pragma omp parallel for num_threads(nthreads) for(int j = 0; j < col; ++j) { double sumj = fsum_int_impl(px + j*l, narm, l); if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; pout[j] = sumj; } } else { for(int j = 0; j != col; ++j) { double sumj = fsum_int_omp_impl(px + j*l, narm, l, nthreads); if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; pout[j] = sumj; } } if(anyoutl == 0) { out = PROTECT(coerceVector(out, INTSXP)); matCopyAttr(out, x, Rdrop, ng); UNPROTECT(nprotect + 1); return out; } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
} else if(col >= nthreads) { // If high-dimensional: column-level parallelism <LOOP-START>for(int j = 0; j < col; ++j) { double sumj = fsum_int_impl(px + j*l, narm, l); if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; pout[j] = sumj; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
++j) pout[j] = fsum_weights_impl(px + j*l, pw, narm, l); } else if(col >= nthreads) { <LOOP-START>for(int j = 0; j < col; ++j) pout[j] = fsum_weights_impl(px + j*l, pw, narm, l); } else { for(int j = 0; j != col; ++j) pout[j] = fsum_weights_omp_impl(px + j*l, pw, narm, l, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
, px + j*l, ng, pg, pw, narm, l); } else { if(nthreads > col) nthreads = col; <LOOP-START>for(int j = 0; j < col; ++j) fsum_weights_g_impl(pout + j*ng, px + j*l, ng, pg, pw, narm, l); } } } matCopyAttr(out, x, Rdrop, ng); UNPROTECT(nprotect); return out; } // For safe multithreading across data frame columns double fsum_impl_dbl(SEXP x, int narm, int nthreads) { int l = length(x); if(l < 1) return NA_REAL; if(nthreads <= 1) switch(TYPEOF(x)) { case REALSXP: return fsum_double_impl(REAL(x), narm, l); case LGLSXP: case INTSXP: return fsum_int_impl(INTEGER(x), narm, l); default: error("Unsupported SEXP type: '%s'", type2char(TYPEOF(x))); } switch(TYPEOF(x)) { case REALSXP: return fsum_double_omp_impl(REAL(x), narm, l, nthreads); case LGLSXP: case INTSXP: return fsum_int_omp_impl(INTEGER(x), narm, l, nthreads); default: error("Unsupported SEXP type: '%s'", type2char(TYPEOF(x))); } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
!= R_NilValue && !(isObject(xj) && inherits(xj, "ts"))) copyMostAttrib(xj, outj); } <LOOP-START>for(int j = 0; j < l; ++j) fsum_g_omp_impl(px[j], DATAPTR(pout[j]), ng, pg, narm); } else { for(int j = 0; j != l; ++j) pout[j] = fsum_g_impl(px[j], ng, pg, narm); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
up = 1;} SET_VECTOR_ELT(x, j, coerceVector(xj, REALSXP)); } } <LOOP-START>for(int j = 0; j < l; ++j) fsum_weights_g_impl(REAL(pout[j]), REAL(px[j]), ng, pg, pw, narm, nrx); } else { for(int j = 0; j != l; ++j) pout[j] = fsum_wg_impl(px[j], ng, pg, pw, narm); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
/ if(ng == 0) { // if(cmth) { // If high-dimensional: column-level parallelism // <LOOP-START>// for(int j = 0; j < col; ++j) fsum_double_impl(pout + j, px + j*l, narm, l); // } else { // for(int j = 0; j != col; ++j) fsum_double_omp_impl(pout + j, px + j*l, narm, l, nthreads); // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
} // } else { // if(cmth) { // If high-dimensional: column-level parallelism // <LOOP-START>// for(int j = 0; j < col; ++j) fsum_double_g_impl(pout + j*ng, px + j*l, ng, pg, narm, l); // } else { // for(int j = 0; j != col; ++j) fsum_double_g_omp_impl(pout + j*ng, px + j*l, ng, pg, narm, l, nthreads); // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
ng, pg, narm, l); // } else if(cmth) { // If high-dimensional: column-level parallelism // <LOOP-START>// for(int j = 0; j < col; ++j) fsum_int_g_impl(pout + j*ng, px + j*l, ng, pg, narm, l); // } else { // for(int j = 0; j != col; ++j) fsum_int_g_omp_impl(pout + j*ng, px + j*l, ng, pg, narm, l, nthreads); // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
mj; // } // } else if(cmth) { // If high-dimensional: column-level parallelism // <LOOP-START>// for(int j = 0; j < col; ++j) { // double sumj = fsum_int_impl(px + j*l, narm, l); // if(sumj > INT_MAX || sumj <= INT_MIN) anyoutl = 1; // pout[j] = sumj; // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
ol; ++j) fsum_weights_impl(pout + j*ng, px + j*l, ng, pg, pw, narm, l); // } else if(cmth) { // <LOOP-START>// for(int j = 0; j < col; ++j) fsum_weights_impl(pout + j*ng, px + j*l, ng, pg, pw, narm, l); // } else { // for(int j = 0; j != col; ++j) fsum_weights_omp_impl(pout + j*ng, px + j*l, ng, pg, pw, narm, l, nthreads); // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
uble *pout = REAL(out); // if(cmth) { // If high-dimensional: column-level parallelism // <LOOP-START>// for(int j = 0; j < l; ++j) pout[j] = asReal(fsumC(px[j], Rng, g, w, Rnarm, Rnthreads1)); // } else { // for(int j = 0; j != l; ++j) pout[j] = asReal(fsumC(px[j], Rng, g, w, Rnarm, Rnthreads)); // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fsum.c
#pragma omp parallel for num_threads(nthreads)
100
t = PROTECT(allocVector(VECSXP, l)), *pout = SEXPPTR(out), *px = SEXPPTR(x); // if(cmth) { // <LOOP-START>// for(int j = 0; j < l; ++j) pout[j] = fsumC(px[j], Rng, g, w, Rnarm, Rnthreads1); // } else { // for(int j = 0; j != l; ++j) pout[j] = fsumC(px[j], Rng, g, w, Rnarm, Rnthreads); // }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,n)
100
nst int narm, const int l, const int nthreads) { double mean = 0; if(narm) { int n = 0; <LOOP-START>for(int i = 0; i < l; ++i) { int tmp = NISNAN(px[i]); mean += tmp ? px[i] : 0.0; n += tmp ? 1 : 0; }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,n)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean)
100
n += tmp ? px[i] : 0.0; n += tmp ? 1 : 0; } return n == 0 ? NA_REAL : mean / n; } <LOOP-START>for(int i = 0; i < l; ++i) mean += px[i]; return mean / l; } void fmean_double_g_impl(double *restrict pout, const double *restrict px, const int ng, const int *restrict pg, const int *restrict pgs, const int narm, const int l) { memset(pout, 0, sizeof(double) * ng); if(narm) { int *restrict n = (int*)Calloc(ng, int); for(int i = 0, gi; i != l; ++i) { if(ISNAN(px[i])) continue; gi = pg[i]-1; pout[gi] += px[i]; ++n[gi]; } for(int i = ng; i--; ) { if(n[i] == 0) pout[i] = NA_REAL; else pout[i] /= n[i]; } Free(n); } else { --pout; for(int i = l; i--; ) pout[pg[i]] += px[i]; // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. ++pout; for(int i = ng; i--; ) pout[i] /= pgs[i]; } }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,sumw)
100
w, const int narm, const int l, const int nthreads) { double mean = 0, sumw = 0; if(narm) { <LOOP-START>for(int i = 0; i < l; ++i) { int tmp = NISNAN(px[i]) + NISNAN(pw[i]) == 2; // && doesn't vectorize for some reason mean += tmp ? px[i] * pw[i] : 0.0; sumw += tmp ? pw[i] : 0.0; }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,sumw)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,sumw)
100
sumw += tmp ? pw[i] : 0.0; } if(mean == 0 && sumw == 0) sumw = NA_REAL; } else { <LOOP-START>for(int i = 0; i < l; ++i) { mean += px[i] * pw[i]; sumw += pw[i]; }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,sumw)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,n)
100
int l, const int nthreads) { long long mean = 0; double dmean; if(narm) { int n = 0; <LOOP-START>for(int i = 0; i < l; ++i) { int tmp = px[i] != NA_INTEGER; mean += tmp ? px[i] : 0; n += tmp ? 1 : 0; }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean,n)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean)
100
ouble)mean / n; } else { if(px[0] == NA_INTEGER || px[l-1] == NA_INTEGER) return NA_REAL; <LOOP-START>for(int i = 0; i < l; ++i) mean += px[i]; dmean = (double)mean / l; } return dmean; } void fmean_int_g_impl(double *restrict pout, const int *restrict px, const int ng, const int *restrict pg, const int *restrict pgs, const int narm, const int l) { memset(pout, 0, sizeof(double) * ng); if(narm) { int *restrict n = (int*)Calloc(ng, int); for(int i = 0, gi; i != l; ++i) { if(px[i] == NA_INTEGER) continue; gi = pg[i]-1; pout[gi] += px[i]; ++n[gi]; } for(int i = ng; i--; ) { if(n[i] == 0) pout[i] = NA_REAL; else pout[i] /= n[i]; } Free(n); } else { --pout; for(int i = l; i--; ) pout[pg[i]] += px[i]; // Used to stop loop when all groups passed with NA, but probably no speed gain since groups are mostly ordered. ++pout; for(int i = ng; i--; ) pout[i] /= pgs[i]; } }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads) reduction(+:mean)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
pout[j] = fmean_double_impl(px + j*l, narm, l); } else if(col >= nthreads) { <LOOP-START>for(int j = 0; j < col; ++j) pout[j] = fmean_double_impl(px + j*l, narm, l); } else { for(int j = 0; j != col; ++j) pout[j] = fmean_double_omp_impl(px + j*l, narm, l, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
g, pg, pgs, narm, l); } else { if(nthreads > col) nthreads = col; <LOOP-START>for(int j = 0; j < col; ++j) fmean_double_g_impl(pout + j*ng, px + j*l, ng, pg, pgs, narm, l); } } break; } case INTSXP: { const int *px = INTEGER(x); if(ng > 0) { if(nthreads <= 1 || col == 1) { for(int j = 0; j != col; ++j) fmean_int_g_impl(pout + j*ng, px + j*l, ng, pg, pgs, narm, l); } else { if(nthreads > col) nthreads = col; #pragma omp parallel for num_threads(nthreads) for(int j = 0; j < col; ++j) fmean_int_g_impl(pout + j*ng, px + j*l, ng, pg, pgs, narm, l); } } else { if(nthreads <= 1) { for(int j = 0; j != col; ++j) pout[j] = fmean_int_impl(px + j*l, narm, l); } else if(col >= nthreads) { #pragma omp parallel for num_threads(nthreads) for(int j = 0; j < col; ++j) pout[j] = fmean_int_impl(px + j*l, narm, l); } else { for(int j = 0; j != col; ++j) pout[j] = fmean_int_omp_impl(px + j*l, narm, l, nthreads); } } break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
g, pg, pgs, narm, l); } else { if(nthreads > col) nthreads = col; <LOOP-START>for(int j = 0; j < col; ++j) fmean_int_g_impl(pout + j*ng, px + j*l, ng, pg, pgs, narm, l); } } else { if(nthreads <= 1) { for(int j = 0; j != col; ++j) pout[j] = fmean_int_impl(px + j*l, narm, l); } else if(col >= nthreads) { #pragma omp parallel for num_threads(nthreads) for(int j = 0; j < col; ++j) pout[j] = fmean_int_impl(px + j*l, narm, l); } else { for(int j = 0; j != col; ++j) pout[j] = fmean_int_omp_impl(px + j*l, narm, l, nthreads); } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
+j) pout[j] = fmean_int_impl(px + j*l, narm, l); } else if(col >= nthreads) { <LOOP-START>for(int j = 0; j < col; ++j) pout[j] = fmean_int_impl(px + j*l, narm, l); } else { for(int j = 0; j != col; ++j) pout[j] = fmean_int_omp_impl(px + j*l, narm, l, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
+j) pout[j] = fmean_weights_impl(px + j*l, pw, narm, l); } else if(col >= nthreads) { <LOOP-START>for(int j = 0; j < col; ++j) pout[j] = fmean_weights_impl(px + j*l, pw, narm, l); } else { for(int j = 0; j != col; ++j) pout[j] = fmean_weights_omp_impl(px + j*l, pw, narm, l, nthreads); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
, px + j*l, ng, pg, pw, narm, l); } else { if(nthreads > col) nthreads = col; <LOOP-START>for(int j = 0; j < col; ++j) fmean_weights_g_impl(pout + j*ng, px + j*l, ng, pg, pw, narm, l); } } } matCopyAttr(out, x, Rdrop, ng); UNPROTECT(nprotect); return out; } // For safe multithreading across data frame columns double fmean_impl_dbl(SEXP x, int narm, int nthreads) { int l = length(x); if(l < 1) return NA_REAL; if(nthreads <= 1) switch(TYPEOF(x)) { case REALSXP: return fmean_double_impl(REAL(x), narm, l); case LGLSXP: case INTSXP: return fmean_int_impl(INTEGER(x), narm, l); default: error("Unsupported SEXP type: '%s'", type2char(TYPEOF(x))); } switch(TYPEOF(x)) { case REALSXP: return fmean_double_omp_impl(REAL(x), narm, l, nthreads); case LGLSXP: case INTSXP: return fmean_int_omp_impl(INTEGER(x), narm, l, nthreads); default: error("Unsupported SEXP type: '%s'", type2char(TYPEOF(x))); } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
!= R_NilValue && !(isObject(xj) && inherits(xj, "ts"))) copyMostAttrib(xj, outj); } <LOOP-START>for(int j = 0; j < l; ++j) fmean_g_omp_impl(px[j], DATAPTR(pout[j]), ng, pg, pgs, narm); } else { for(int j = 0; j != l; ++j) pout[j] = fmean_g_impl(px[j], ng, pg, pgs, narm); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fmean.c
#pragma omp parallel for num_threads(nthreads)
100
up = 1;} SET_VECTOR_ELT(x, j, coerceVector(xj, REALSXP)); } } <LOOP-START>for(int j = 0; j < l; ++j) fmean_weights_g_impl(REAL(pout[j]), REAL(px[j]), ng, pg, pw, narm, nrx); } else { for(int j = 0; j != l; ++j) pout[j] = fmean_wg_impl(px[j], ng, pg, pw, narm); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/data.table_subset.c
#pragma omp parallel for num_threads(getDTthreads())
100
int *idxp = INTEGER(idx); bool stop = false; // <LOOP-START>#pragma omp simd reduction(|:stop) for (int i = 0; i < n; ++i) { int elem = idxp[i]; stop |= (elem<1 && elem!=NA_INTEGER) || elem>max; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(getDTthreads())<OMP-END>
SebKrantz/collapse/src/programming.c
#pragma omp parallel for num_threads(nthreads)
100
// Full distance matrix if(nthreads > 1) { if(nthreads > nrow-1) nthreads = nrow-1; <LOOP-START>for(int k = 1; k < nrow; ++k) { // Row vectors to compute distances with int nmk = nrow - k; double *presk = pres + l - nmk*(nmk+1)/2, // https://en.wikipedia.org/wiki/1_%2B_2_%2B_3_%2B_4_%2B_%E2%8B%AF *pxj = px + k, v; for(int j = 0; j != ncol; ++j) { // Elements of the row vector at hand v = pxj[-1]; #pragma omp simd for(int i = 0; i < nmk; ++i) { // All remaining rows to compute the distance to double tmp = pxj[i] - v; presk[i] += tmp * tmp; } pxj += nrow; } }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/programming.c
#pragma omp parallel for simd num_threads(nthreads)
100
for (int j = 0; j < ncol; ++j) { double *pxj = px + j * nrow, v = pv[j]; <LOOP-START>for (int i = 0; i < nrow; ++i) { double tmp = pxj[i] - v; pres[i] += tmp * tmp; }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/programming.c
#pragma omp parallel for num_threads(nthreads) reduction(+:dres)
100
double dres = 0.0; if(nthreads > 1) { if(nthreads > ncol) nthreads = ncol; <LOOP-START>for (int i = 0; i < ncol; ++i) { double tmp = px[i] - pv[i]; dres += tmp * tmp; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads) reduction(+:dres)<OMP-END>
SebKrantz/collapse/src/programming.c
#pragma omp parallel for simd num_threads(nthreads)
100
he square root loop below } } // Square Root if(ret == 1) { if(nthreads > 1) { <LOOP-START>for (size_t i = 0; i < l; ++i) pres[i] = sqrt(pres[i]); } else { #pragma omp simd for (size_t i = 0; i < l; ++i) pres[i] = sqrt(pres[i]); }<LOOP-END> <OMP-START>#pragma omp parallel for simd num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fndistinct.c
#pragma omp parallel for num_threads(nthreads)
100
readed... switch(TYPEOF(x)) { case REALSXP: { const double *px = REAL(x); <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = pgs[gr] == 0 ? 0 : ndistinct_double(px + pst[gr]-1, po, pgs[gr], 1, narm); break; } case INTSXP: { const int *px = INTEGER(x); if(isFactor(x) && nlevels(x) < l / ng * 3) { int M = nlevels(x); #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = pgs[gr] == 0 ? 0 : ndistinct_fct(px + pst[gr]-1, po, pgs[gr], M, 1, narm); } else { #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = pgs[gr] == 0 ? 0 : ndistinct_int(px + pst[gr]-1, po, pgs[gr], 1, narm); } break; }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>
SebKrantz/collapse/src/fndistinct.c
#pragma omp parallel for num_threads(nthreads)
100
ER(x); if(isFactor(x) && nlevels(x) < l / ng * 3) { int M = nlevels(x); <LOOP-START>for(int gr = 0; gr < ng; ++gr) pres[gr] = pgs[gr] == 0 ? 0 : ndistinct_fct(px + pst[gr]-1, po, pgs[gr], M, 1, narm); } else { #pragma omp parallel for num_threads(nthreads) for(int gr = 0; gr < ng; ++gr) pres[gr] = pgs[gr] == 0 ? 0 : ndistinct_int(px + pst[gr]-1, po, pgs[gr], 1, narm); }<LOOP-END> <OMP-START>#pragma omp parallel for num_threads(nthreads)<OMP-END>