#include "run_sp.h" #include "dgraph.h" #include "heaps/heap_lib.h" // # nocov start template void inst_graph (std::shared_ptr g, size_t nedges, const std::map & vert_map, const std::vector & from, const std::vector & to, const std::vector & dist, const std::vector & wt) { for (size_t i = 0; i < nedges; ++i) { size_t fromi = vert_map.at(from [i]); size_t toi = vert_map.at(to [i]); g->addNewEdge (fromi, toi, dist [i], wt [i], i); } } // # nocov end // RcppParallel jobs can be chunked to a specified "grain size"; see // https://rcppcore.github.io/RcppParallel/#grain_size // This function determines chunk size such that there are at least 100 chunks // for a given `nfrom`. size_t run_sp::get_chunk_size (const size_t nfrom) { size_t chunk_size; if (nfrom > 1000) chunk_size = 100; else if (nfrom > 100) chunk_size = 10; else chunk_size = 1; return chunk_size; } std::shared_ptr run_sp::getHeapImpl(const std::string& heap_type) { if (heap_type == "FHeap") return std::make_shared >(); else if (heap_type == "BHeap" || heap_type == "set") // heap not used for set return std::make_shared >(); else if (heap_type == "Heap23") return std::make_shared >(); else if (heap_type == "TriHeap") return std::make_shared >(); else if (heap_type == "TriHeapExt") return std::make_shared >(); else throw std::runtime_error("invalid heap type: " + heap_type); // # nocov } struct OneDist : public RcppParallel::Worker { RcppParallel::RVector dp_fromi; const std::vector toi; const size_t nverts; const std::vector vx; const std::vector vy; const std::shared_ptr g; const std::string heap_type; bool is_spatial; RcppParallel::RMatrix dout; // constructor OneDist ( const RcppParallel::RVector fromi, const std::vector toi_in, const size_t nverts_in, const std::vector vx_in, const std::vector vy_in, const std::shared_ptr g_in, const std::string & heap_type_in, const bool & is_spatial_in, RcppParallel::RMatrix dout_in) : dp_fromi (fromi), toi (toi_in), nverts (nverts_in), vx (vx_in), vy (vy_in), g (g_in), heap_type (heap_type_in), is_spatial (is_spatial_in), dout (dout_in) { } // Parallel function operator void operator() (std::size_t begin, std::size_t end) { // Allocate once per chunk; PathFinder::init_arrays resets state each call. // Reuse requires BHeap (clear() is a no-op for other heap types). std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl (heap_type), g); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); for (std::size_t i = begin; i < end; i++) { std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl (heap_type), g); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); size_t from_i = static_cast (dp_fromi [i]); if (is_spatial) { pathfinder->AStar (d, w, prev, from_i, toi, vx[toi[0]], vy[toi[0]], vx, vy, is_spatial); } else if (heap_type.find ("set") == std::string::npos) pathfinder->Dijkstra (d, w, prev, from_i, toi); else pathfinder->Dijkstra_set (d, w, prev, from_i); for (size_t j = 0; j < toi.size (); j++) { if (w [toi [j]] < INFINITE_DOUBLE) { dout (i, j) = d [toi [j]]; } } } } }; struct OneDistNearest : public RcppParallel::Worker { RcppParallel::RVector dp_fromi; const std::vector toi; const size_t nverts; const size_t nfrom; const std::shared_ptr g; const std::string heap_type; RcppParallel::RVector dout; // constructor OneDistNearest ( const RcppParallel::RVector fromi, const std::vector toi_in, const size_t nverts_in, const size_t nfrom_in, const std::shared_ptr g_in, const std::string & heap_type_in, RcppParallel::RVector dout_in) : dp_fromi (fromi), toi (toi_in), nverts (nverts_in), nfrom (nfrom_in), g (g_in), heap_type (heap_type_in), dout (dout_in) { } // Parallel function operator void operator() (std::size_t begin, std::size_t end) { std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl (heap_type), g); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); for (std::size_t i = begin; i < end; i++) { size_t from_i = static_cast (dp_fromi [i]); pathfinder->DijkstraNearest (d, w, prev, from_i, toi); for (size_t j = 0; j < toi.size (); j++) { if (w [toi [j]] < INFINITE_DOUBLE) { dout [i] = d [toi [j]]; dout [i + nfrom] = static_cast (toi [j]); } } } } }; struct OneDistPaired : public RcppParallel::Worker { RcppParallel::RVector dp_fromtoi; const size_t nverts; const size_t nfrom; const std::vector vx; const std::vector vy; const std::shared_ptr g; const std::string heap_type; bool is_spatial; bool do_bidirectional; RcppParallel::RMatrix dout; // constructor OneDistPaired ( const RcppParallel::RVector fromtoi, const size_t nverts_in, const size_t nfrom_in, const std::vector vx_in, const std::vector vy_in, const std::shared_ptr g_in, const std::string & heap_type_in, const bool & is_spatial_in, const bool & do_bidirectional_in, RcppParallel::RMatrix dout_in) : dp_fromtoi (fromtoi), nverts (nverts_in), nfrom (nfrom_in), vx (vx_in), vy (vy_in), g (g_in), heap_type (heap_type_in), is_spatial (is_spatial_in), do_bidirectional(do_bidirectional_in), dout (dout_in) { } // Parallel function operator void operator() (std::size_t begin, std::size_t end) { std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl (heap_type), g); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); for (std::size_t i = begin; i < end; i++) { std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl (heap_type), g, do_bidirectional); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); const size_t from_i = static_cast (dp_fromtoi [i]); const std::vector to_i = {static_cast (dp_fromtoi [nfrom + i])}; if (do_bidirectional) { std::vector w_rev (nverts); std::vector d_rev (nverts); std::vector prev_rev (nverts); pathfinder->AStar2 (d, w, prev, from_i, to_i[0], d_rev, w_rev, prev_rev, vx[to_i[0]], vy[to_i[0]], vx, vy, is_spatial); } else if (is_spatial) { long int max_h_index = -1; double max_h_value = -1.0; // This selection needs the heuristic value of every vertex, // so gains nothing from lazy evaluation, unlike the AStar // search itself below. std::vector heuristic (nverts); const double x0 = vx [from_i]; const double y0 = vy [from_i]; for (size_t j = 0; j < nverts; j++) { const double dx = vx [j] - x0; const double dy = vy [j] - y0; heuristic [j] = sqrt (dx * dx + dy * dy); } for (size_t j = 0; j < nverts; j++) { const double h = heuristic [j]; if (h > max_h_value) { max_h_value = h; max_h_index = static_cast (j); } } const double htemp = heuristic [static_cast (dp_fromtoi [nfrom + i])]; double min_h_value = max_h_value; long int min_h_index = max_h_index; const double thr = 0.1; for (size_t j = 0; j < nverts; j++) { const double h = heuristic [j]; if ((h < (thr * htemp)) && (h > min_h_value)) { min_h_value = h; min_h_index = static_cast (j); } } const std::vector to_i2 = {to_i [0], static_cast (min_h_index)}; pathfinder->AStar (d, w, prev, from_i, to_i2, vx[to_i2[0]], vy[to_i2[0]], vx, vy, is_spatial); } else if (heap_type.find ("set") == std::string::npos) pathfinder->Dijkstra (d, w, prev, from_i, to_i); else pathfinder->Dijkstra_set (d, w, prev, from_i); if (w [to_i [0]] < INFINITE_DOUBLE) dout (i, 0) = d [to_i [0]]; } } }; struct OneIso : public RcppParallel::Worker { RcppParallel::RVector dp_fromi; const size_t nverts; const std::shared_ptr g; const RcppParallel::RVector dlimit; const std::string heap_type; RcppParallel::RMatrix dout; // constructor OneIso ( const RcppParallel::RVector fromi, const size_t nverts_in, const std::shared_ptr g_in, const RcppParallel::RVector dlimit_in, const std::string & heap_type_in, RcppParallel::RMatrix dout_in) : dp_fromi (fromi), nverts (nverts_in), g (g_in), dlimit (dlimit_in), heap_type (heap_type_in), dout (dout_in) { } // Parallel function operator void operator() (std::size_t begin, std::size_t end) { const double dlimit_max = *std::max_element (dlimit.begin (), dlimit.end ()); std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl (heap_type), g); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); for (std::size_t i = begin; i < end; i++) { size_t from_i = static_cast (dp_fromi [i]); pathfinder->DijkstraLimit (d, w, prev, from_i, dlimit_max); // Get the set of terminal vertices: those with w < dlimit_max but // with no previous (outward-going) nodes std::unordered_set terminal_verts; for (size_t j = 0; j < nverts; j++) { if (prev [j] == INFINITE_INT && d [j] < dlimit_max) { terminal_verts.emplace (static_cast (j)); } } for (size_t j = 0; j < nverts; j++) { if (terminal_verts.find (static_cast (j)) != terminal_verts.end ()) { // Flag terminal verts with -d dout (i, j) = -d [j]; // # nocov } else if (prev [j] < INFINITE_INT && d [j] < dlimit_max) { size_t st_prev = static_cast (prev [j]); dout (i, j) = d [j]; } } } } }; size_t run_sp::make_vert_map (const Rcpp::DataFrame &vert_map_in, const std::vector &vert_map_id, const std::vector &vert_map_n, std::map &vert_map) { for (size_t i = 0; i < static_cast (vert_map_in.nrow ()); ++i) { vert_map.emplace (vert_map_id [i], vert_map_n [i]); } size_t nverts = static_cast (vert_map.size ()); return (nverts); } // Flows from the pathfinder output are reallocated based on matching vertex // pairs to edge indices. Note, however, that contracted graphs frequently // have duplicate vertex pairs with different distances. The following // therefore uses two maps, one to hold the ultimate index from vertex // pairs, and the other to hold minimal distances. This is used in flow routines // only. void run_sp::make_vert_to_edge_maps (const std::vector &from, const std::vector &to, const std::vector &wt, std::unordered_map &verts_to_edge_map, std::unordered_map &verts_to_dist_map) { for (size_t i = 0; i < from.size (); i++) { std::string two_verts = "f" + from [i] + "t" + to [i]; verts_to_edge_map.emplace (two_verts, i); if (verts_to_dist_map.find (two_verts) == verts_to_dist_map.end ()) verts_to_dist_map.emplace (two_verts, wt [i]); else if (wt [i] < verts_to_dist_map.at (two_verts)) { verts_to_dist_map [two_verts] = wt [i]; verts_to_edge_map [two_verts] = i; } } } //' rcpp_get_sp_dists_par //' //' @noRd // [[Rcpp::export]] Rcpp::NumericMatrix rcpp_get_sp_dists_par (const Rcpp::DataFrame graph, const Rcpp::DataFrame vert_map_in, Rcpp::IntegerVector fromi, Rcpp::IntegerVector toi_in, const std::string& heap_type, const bool is_spatial) { std::vector toi = Rcpp::as > ( toi_in); size_t nfrom = static_cast (fromi.size ()); size_t nto = static_cast (toi.size ()); const std::vector from = graph ["from"]; const std::vector to = graph ["to"]; const std::vector dist = graph ["d"]; const std::vector wt = graph ["d_weighted"]; const size_t nedges = static_cast (graph.nrow ()); std::map vert_map; std::vector vert_map_id = vert_map_in ["vert"]; std::vector vert_map_n = vert_map_in ["id"]; const size_t nverts = run_sp::make_vert_map (vert_map_in, vert_map_id, vert_map_n, vert_map); std::vector vx (nverts), vy (nverts); if (is_spatial) { vx = Rcpp::as > (vert_map_in ["x"]); vy = Rcpp::as > (vert_map_in ["y"]); } std::shared_ptr g = std::make_shared (nverts); inst_graph (g, nedges, vert_map, from, to, dist, wt); Rcpp::NumericVector na_vec = Rcpp::NumericVector (nfrom * nto, Rcpp::NumericVector::get_na ()); Rcpp::NumericMatrix dout (static_cast (nfrom), static_cast (nto), na_vec.begin ()); // Create parallel worker OneDist one_dist (RcppParallel::RVector (fromi), toi, nverts, vx, vy, g, heap_type, is_spatial, RcppParallel::RMatrix (dout)); size_t chunk_size = run_sp::get_chunk_size (nfrom); RcppParallel::parallelFor (0, nfrom, one_dist, chunk_size); return (dout); } //' rcpp_get_sp_dists_nearest //' //' @noRd // [[Rcpp::export]] Rcpp::NumericVector rcpp_get_sp_dists_nearest (const Rcpp::DataFrame graph, const Rcpp::DataFrame vert_map_in, Rcpp::IntegerVector fromi, Rcpp::IntegerVector toi_in, const std::string& heap_type) { std::vector toi = Rcpp::as > (toi_in); size_t nfrom = static_cast (fromi.size ()); const std::vector from = graph ["from"]; const std::vector to = graph ["to"]; const std::vector dist = graph ["d"]; const std::vector wt = graph ["d_weighted"]; const size_t nedges = static_cast (graph.nrow ()); std::map vert_map; std::vector vert_map_id = vert_map_in ["vert"]; std::vector vert_map_n = vert_map_in ["id"]; const size_t nverts = run_sp::make_vert_map (vert_map_in, vert_map_id, vert_map_n, vert_map); std::shared_ptr g = std::make_shared (nverts); inst_graph (g, nedges, vert_map, from, to, dist, wt); Rcpp::NumericVector dout = Rcpp::NumericVector (2 * nfrom, Rcpp::NumericVector::get_na ()); // Create parallel worker OneDistNearest one_dist (RcppParallel::RVector (fromi), toi, nverts, nfrom, g, heap_type, RcppParallel::RVector (dout)); size_t chunk_size = run_sp::get_chunk_size (nfrom); RcppParallel::parallelFor (0, nfrom, one_dist, chunk_size); return (dout); } //' rcpp_get_sp_dists_paired_par //' //' @noRd // [[Rcpp::export]] Rcpp::NumericMatrix rcpp_get_sp_dists_paired_par (const Rcpp::DataFrame graph, const Rcpp::DataFrame vert_map_in, Rcpp::IntegerVector fromi, Rcpp::IntegerVector toi, const std::string& heap_type, const bool is_spatial, const bool do_bidirectional) { if (fromi.size () != toi.size ()) Rcpp::stop ("pairwise dists must have from.size == to.size"); long int n = fromi.size (); size_t n_st = static_cast (n); const std::vector from = graph ["from"]; const std::vector to = graph ["to"]; const std::vector dist = graph ["d"]; const std::vector wt = graph ["d_weighted"]; const size_t nedges = static_cast (graph.nrow ()); std::map vert_map; std::vector vert_map_id = vert_map_in ["vert"]; std::vector vert_map_n = vert_map_in ["id"]; const size_t nverts = run_sp::make_vert_map (vert_map_in, vert_map_id, vert_map_n, vert_map); std::vector vx (nverts), vy (nverts); if (is_spatial) { vx = Rcpp::as > (vert_map_in ["x"]); vy = Rcpp::as > (vert_map_in ["y"]); } std::shared_ptr g = std::make_shared (nverts); inst_graph (g, nedges, vert_map, from, to, dist, wt); Rcpp::NumericVector na_vec = Rcpp::NumericVector (n_st, Rcpp::NumericVector::get_na ()); Rcpp::NumericMatrix dout (static_cast (n), 1, na_vec.begin ()); // Paired (fromi, toi) in a single vector Rcpp::IntegerVector fromto (2 * n_st); for (int i = 0; i < n; i++) { size_t i_t = static_cast (i); fromto [i] = fromi (i_t); fromto [i + n] = toi (i_t); } // Create parallel worker OneDistPaired one_dist_paired (RcppParallel::RVector (fromto), nverts, n_st, vx, vy, g, heap_type, is_spatial, do_bidirectional, RcppParallel::RMatrix (dout)); size_t chunk_size = run_sp::get_chunk_size (n_st); RcppParallel::parallelFor (0, n_st, one_dist_paired, chunk_size); return (dout); } //' rcpp_get_iso //' //' @noRd // [[Rcpp::export]] Rcpp::NumericMatrix rcpp_get_iso (const Rcpp::DataFrame graph, const Rcpp::DataFrame vert_map_in, Rcpp::IntegerVector fromi, Rcpp::NumericVector dlim, const std::string& heap_type) { const size_t nfrom = static_cast (fromi.size ()); std::vector from = graph ["from"]; std::vector to = graph ["to"]; std::vector dist = graph ["d"]; std::vector wt = graph ["d_weighted"]; size_t nedges = static_cast (graph.nrow ()); std::map vert_map; std::vector vert_map_id = vert_map_in ["vert"]; std::vector vert_map_n = vert_map_in ["id"]; size_t nverts = run_sp::make_vert_map (vert_map_in, vert_map_id, vert_map_n, vert_map); std::vector vx (nverts), vy (nverts); std::shared_ptr g = std::make_shared (nverts); inst_graph (g, nedges, vert_map, from, to, dist, wt); Rcpp::NumericVector na_vec = Rcpp::NumericVector (nfrom * nverts, Rcpp::NumericVector::get_na ()); Rcpp::NumericMatrix dout (static_cast (nfrom), static_cast (nverts), na_vec.begin ()); // Create parallel worker OneIso one_iso (RcppParallel::RVector (fromi), nverts, g, RcppParallel::RVector (dlim), heap_type, RcppParallel::RMatrix (dout)); RcppParallel::parallelFor (0, static_cast (fromi.length ()), one_iso); return (dout); } //' rcpp_get_sp_dists //' //' @noRd // [[Rcpp::export]] Rcpp::NumericMatrix rcpp_get_sp_dists (const Rcpp::DataFrame graph, const Rcpp::DataFrame vert_map_in, Rcpp::IntegerVector fromi, Rcpp::IntegerVector toi_in, const std::string& heap_type) { std::vector toi = Rcpp::as > ( toi_in); size_t nfrom = static_cast (fromi.size ()); size_t nto = static_cast (toi.size ()); std::vector from = graph ["from"]; std::vector to = graph ["to"]; std::vector dist = graph ["d"]; std::vector wt = graph ["d_weighted"]; size_t nedges = static_cast (graph.nrow ()); std::map vert_map; std::vector vert_map_id = vert_map_in ["vert"]; std::vector vert_map_n = vert_map_in ["id"]; size_t nverts = run_sp::make_vert_map (vert_map_in, vert_map_id, vert_map_n, vert_map); std::shared_ptr g = std::make_shared(nverts); inst_graph (g, nedges, vert_map, from, to, dist, wt); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); // initialise dout matrix to NA Rcpp::NumericVector na_vec = Rcpp::NumericVector (nfrom * nto, Rcpp::NumericVector::get_na ()); Rcpp::NumericMatrix dout (static_cast (nfrom), static_cast (nto), na_vec.begin ()); std::shared_ptr pathfinder = std::make_shared ( nverts, *run_sp::getHeapImpl(heap_type), g); for (size_t i = 0; i < nfrom; i++) { Rcpp::checkUserInterrupt (); size_t fromi_i = static_cast (fromi [static_cast (i)]); pathfinder->Dijkstra (d, w, prev, fromi_i, toi); for (size_t j = 0; j < nto; j++) { if (w [static_cast (toi [j])] < INFINITE_DOUBLE) { dout (i, j) = d [static_cast (toi [j])]; } } } return (dout); } //' rcpp_get_paths //' //' @param graph The data.frame holding the graph edges //' @param vert_map_in map from vertex ID to (0-indexed) integer //' index of vertices //' @param fromi Index into vert_map_in of vertex numbers //' @param toi Index into vert_map_in of vertex numbers //' //' @note The graph is constructed with 0-indexed vertex numbers contained in //' code{vert_map_in}. Both \code{fromi} and \code{toi} already map directly //' onto these. The graph has to be constructed by first constructing a //' \code{std::map} object (\code{vertmap}) for \code{vert_map_in}, then //' translating all \code{graph["from"/"to"]} values into these indices. This //' construction is done in \code{inst_graph}. //' //' @note Returns 1-indexed values indexing directly into the R input //' //' @noRd // [[Rcpp::export]] Rcpp::List rcpp_get_paths (const Rcpp::DataFrame graph, const Rcpp::DataFrame vert_map_in, Rcpp::IntegerVector fromi, Rcpp::IntegerVector toi_in, const std::string& heap_type) { std::vector toi = Rcpp::as > ( toi_in); size_t nfrom = static_cast (fromi.size ()); size_t nto = static_cast (toi.size ()); std::vector from = graph ["from"]; std::vector to = graph ["to"]; std::vector dist = graph ["d"]; std::vector wt = graph ["d_weighted"]; size_t nedges = static_cast (graph.nrow ()); std::map vert_map; std::vector vert_map_id = vert_map_in ["vert"]; std::vector vert_map_n = vert_map_in ["id"]; size_t nverts = run_sp::make_vert_map (vert_map_in, vert_map_id, vert_map_n, vert_map); std::shared_ptr g = std::make_shared(nverts); inst_graph (g, nedges, vert_map, from, to, dist, wt); Rcpp::List res (nfrom); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl(heap_type), g); for (size_t i = 0; i < nfrom; i++) { const R_xlen_t i_R = static_cast (i); // These lines (re-)initialise the heap, so have to be called for each i std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl(heap_type), g); pathfinder->init (g); // specify the graph Rcpp::checkUserInterrupt (); pathfinder->Dijkstra (d, w, prev, static_cast (fromi [i_R]), toi); Rcpp::List res1 (nto); for (size_t j = 0; j < nto; j++) { std::vector onePath; if (w [toi [j]] < INFINITE_DOUBLE) { long int target = toi_in [static_cast (j)]; // target can be -1! while (target < INFINITE_INT) { // Note that targets are all C++ 0-indexed and are converted // directly here to R-style 1-indexes. onePath.push_back (target + 1L); target = prev [static_cast (target)]; if (target < 0L || target == fromi [i_R]) break; } } if (onePath.size () >= 1) { onePath.push_back (static_cast (fromi [i_R] + 1L)); std::reverse (onePath.begin (), onePath.end ()); res1 [static_cast (j)] = onePath; } } res [static_cast (i)] = res1; } return (res); } // [[Rcpp::export]] Rcpp::List rcpp_get_paths_pairwise (const Rcpp::DataFrame graph, const Rcpp::DataFrame vert_map_in, Rcpp::IntegerVector fromi, Rcpp::IntegerVector toi_in, const std::string& heap_type, const bool is_spatial, const bool do_bidirectional) { std::vector toi = Rcpp::as > ( toi_in); size_t nfrom = static_cast (fromi.size ()); std::vector from = graph ["from"]; std::vector to = graph ["to"]; std::vector dist = graph ["d"]; std::vector wt = graph ["d_weighted"]; size_t nedges = static_cast (graph.nrow ()); std::map vert_map; std::vector vert_map_id = vert_map_in ["vert"]; std::vector vert_map_n = vert_map_in ["id"]; size_t nverts = run_sp::make_vert_map (vert_map_in, vert_map_id, vert_map_n, vert_map); std::vector vx (nverts), vy (nverts); if (is_spatial) { vx = Rcpp::as > (vert_map_in ["x"]); vy = Rcpp::as > (vert_map_in ["y"]); } std::shared_ptr g = std::make_shared(nverts); inst_graph (g, nedges, vert_map, from, to, dist, wt); Rcpp::List res (nfrom); std::vector w (nverts); std::vector d (nverts); std::vector prev (nverts); for (size_t i = 0; i < nfrom; i++) { const R_xlen_t i_R = static_cast (i); // These lines (re-)initialise the heap, so have to be called for each i std::shared_ptr pathfinder = std::make_shared (nverts, *run_sp::getHeapImpl(heap_type), g, do_bidirectional); pathfinder->init (g); // specify the graph Rcpp::checkUserInterrupt (); if (do_bidirectional) { std::vector w_rev (nverts); std::vector d_rev (nverts); std::vector prev_rev (nverts); size_t target_idx = toi [static_cast (i_R)]; pathfinder->AStar2 (d, w, prev, static_cast (fromi [i_R]), target_idx, d_rev, w_rev, prev_rev, vx[target_idx], vy[target_idx], vx, vy, is_spatial); } else { pathfinder->Dijkstra (d, w, prev, static_cast (fromi [i_R]), toi); } Rcpp::List res1( 1L ); std::vector onePath; if (w [toi [i]] < INFINITE_DOUBLE) { long int target = toi_in [i_R]; // target can be -1! while (target < INFINITE_INT) { // Note that targets are all C++ 0-indexed and are converted // directly here to R-style 1-indexes. onePath.push_back (target + 1); target = prev [static_cast (target)]; if (target < 0 || target == fromi [i_R]) break; } } if (onePath.size () >= 1) { onePath.push_back (static_cast (fromi [i_R] + 1L)); std::reverse (onePath.begin (), onePath.end ()); res1[0L] = onePath; } res [static_cast (i)] = res1; } return (res); }