// Boost.Geometry Index // // R-tree linear split algorithm implementation // // Copyright (c) 2008 Federico J. Fernandez. // Copyright (c) 2011-2014 Adam Wulkiewicz, Lodz, Poland. // // Use, modification and distribution is subject to the Boost Software License, // Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at // http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_GEOMETRY_INDEX_DETAIL_RTREE_LINEAR_REDISTRIBUTE_ELEMENTS_HPP #define BOOST_GEOMETRY_INDEX_DETAIL_RTREE_LINEAR_REDISTRIBUTE_ELEMENTS_HPP #include #include #include #include #include #include namespace boost { namespace geometry { namespace index { namespace detail { namespace rtree { namespace linear { template inline R difference_dispatch(T const& from, T const& to, ::boost::mpl::bool_ const& /*is_unsigned*/) { return to - from; } template inline R difference_dispatch(T const& from, T const& to, ::boost::mpl::bool_ const& /*is_unsigned*/) { return from <= to ? R(to - from) : -R(from - to); } template inline R difference(T const& from, T const& to) { BOOST_MPL_ASSERT_MSG(!boost::is_unsigned::value, RESULT_CANT_BE_UNSIGNED, (R)); typedef ::boost::mpl::bool_< boost::is_unsigned::value > is_unsigned; return difference_dispatch(from, to, is_unsigned()); } // TODO: awulkiew // In general, all aerial Indexables in the tree with box-like nodes will be analyzed as boxes // because they must fit into larger box. Therefore the algorithm could be the same for Bounds type. // E.g. if Bounds type is sphere, Indexables probably should be analyzed as spheres. // 1. View could be provided to 'see' all Indexables as Bounds type. // Not ok in the case of big types like Ring, however it's possible that Rings won't be supported, // only simple types. Even then if we consider storing Box inside the Sphere we must calculate // the bounding sphere 2x for each box because there are 2 loops. For each calculation this means // 4-2d or 8-3d expansions or -, / and sqrt(). // 2. Additional container could be used and reused if the Indexable type is other than the Bounds type. // IMPORTANT! // Still probably the best way would be providing specialized algorithms for each Indexable-Bounds pair! // Probably on pick_seeds algorithm level - For Bounds=Sphere seeds would be choosen differently // TODO: awulkiew // there are loops inside find_greatest_normalized_separation::apply() // iteration is done for each DimensionIndex. // Separations and seeds for all DimensionIndex(es) could be calculated at once, stored, then the greatest would be choosen. // The following struct/method was adapted for the preliminary version of the R-tree. Then it was called: // void find_normalized_separations(std::vector const& boxes, T& separation, unsigned int& first, unsigned int& second) const template struct find_greatest_normalized_separation { typedef typename Elements::value_type element_type; typedef typename rtree::element_indexable_type::type indexable_type; typedef typename coordinate_type::type coordinate_type; typedef typename boost::mpl::if_c< boost::is_integral::value, double, coordinate_type >::type separation_type; typedef typename geometry::point_type::type point_type; typedef geometry::model::box bounds_type; typedef index::detail::bounded_view bounded_view_type; static inline void apply(Elements const& elements, Parameters const& parameters, Translator const& translator, separation_type & separation, size_t & seed1, size_t & seed2) { const size_t elements_count = parameters.get_max_elements() + 1; BOOST_GEOMETRY_INDEX_ASSERT(elements.size() == elements_count, "unexpected number of elements"); BOOST_GEOMETRY_INDEX_ASSERT(2 <= elements_count, "unexpected number of elements"); // find the lowest low, highest high bounded_view_type bounded_indexable_0(rtree::element_indexable(elements[0], translator)); coordinate_type lowest_low = geometry::get(bounded_indexable_0); coordinate_type highest_high = geometry::get(bounded_indexable_0); // and the lowest high coordinate_type lowest_high = highest_high; size_t lowest_high_index = 0; for ( size_t i = 1 ; i < elements_count ; ++i ) { bounded_view_type bounded_indexable(rtree::element_indexable(elements[i], translator)); coordinate_type min_coord = geometry::get(bounded_indexable); coordinate_type max_coord = geometry::get(bounded_indexable); if ( max_coord < lowest_high ) { lowest_high = max_coord; lowest_high_index = i; } if ( min_coord < lowest_low ) lowest_low = min_coord; if ( highest_high < max_coord ) highest_high = max_coord; } // find the highest low size_t highest_low_index = lowest_high_index == 0 ? 1 : 0; bounded_view_type bounded_indexable_hl(rtree::element_indexable(elements[highest_low_index], translator)); coordinate_type highest_low = geometry::get(bounded_indexable_hl); for ( size_t i = highest_low_index ; i < elements_count ; ++i ) { bounded_view_type bounded_indexable(rtree::element_indexable(elements[i], translator)); coordinate_type min_coord = geometry::get(bounded_indexable); if ( highest_low < min_coord && i != lowest_high_index ) { highest_low = min_coord; highest_low_index = i; } } coordinate_type const width = highest_high - lowest_low; // highest_low - lowest_high separation = difference(lowest_high, highest_low); // BOOST_GEOMETRY_INDEX_ASSERT(0 <= width); if ( std::numeric_limits::epsilon() < width ) separation /= width; seed1 = highest_low_index; seed2 = lowest_high_index; ::boost::ignore_unused_variable_warning(parameters); } }; // Version for points doesn't calculate normalized separation since it would always be equal to 1 // It returns two seeds most distant to each other, separation is equal to distance template struct find_greatest_normalized_separation { typedef typename Elements::value_type element_type; typedef typename rtree::element_indexable_type::type indexable_type; typedef typename coordinate_type::type coordinate_type; typedef coordinate_type separation_type; static inline void apply(Elements const& elements, Parameters const& parameters, Translator const& translator, separation_type & separation, size_t & seed1, size_t & seed2) { const size_t elements_count = parameters.get_max_elements() + 1; BOOST_GEOMETRY_INDEX_ASSERT(elements.size() == elements_count, "unexpected number of elements"); BOOST_GEOMETRY_INDEX_ASSERT(2 <= elements_count, "unexpected number of elements"); // find the lowest low, highest high coordinate_type lowest = geometry::get(rtree::element_indexable(elements[0], translator)); coordinate_type highest = geometry::get(rtree::element_indexable(elements[0], translator)); size_t lowest_index = 0; size_t highest_index = 0; for ( size_t i = 1 ; i < elements_count ; ++i ) { coordinate_type coord = geometry::get(rtree::element_indexable(elements[i], translator)); if ( coord < lowest ) { lowest = coord; lowest_index = i; } if ( highest < coord ) { highest = coord; highest_index = i; } } separation = highest - lowest; seed1 = lowest_index; seed2 = highest_index; if ( lowest_index == highest_index ) seed2 = (lowest_index + 1) % elements_count; // % is just in case since if this is true lowest_index is 0 ::boost::ignore_unused_variable_warning(parameters); } }; template struct pick_seeds_impl { BOOST_STATIC_ASSERT(0 < Dimension); typedef typename Elements::value_type element_type; typedef typename rtree::element_indexable_type::type indexable_type; typedef find_greatest_normalized_separation< Elements, Parameters, Translator, typename tag::type, Dimension - 1 > find_norm_sep; typedef typename find_norm_sep::separation_type separation_type; static inline void apply(Elements const& elements, Parameters const& parameters, Translator const& tr, separation_type & separation, size_t & seed1, size_t & seed2) { pick_seeds_impl::apply(elements, parameters, tr, separation, seed1, seed2); separation_type current_separation; size_t s1, s2; find_norm_sep::apply(elements, parameters, tr, current_separation, s1, s2); // in the old implementation different operator was used: <= (y axis prefered) if ( separation < current_separation ) { separation = current_separation; seed1 = s1; seed2 = s2; } } }; template struct pick_seeds_impl { typedef typename Elements::value_type element_type; typedef typename rtree::element_indexable_type::type indexable_type; typedef typename coordinate_type::type coordinate_type; typedef find_greatest_normalized_separation< Elements, Parameters, Translator, typename tag::type, 0 > find_norm_sep; typedef typename find_norm_sep::separation_type separation_type; static inline void apply(Elements const& elements, Parameters const& parameters, Translator const& tr, separation_type & separation, size_t & seed1, size_t & seed2) { find_norm_sep::apply(elements, parameters, tr, separation, seed1, seed2); } }; // from void linear_pick_seeds(node_pointer const& n, unsigned int &seed1, unsigned int &seed2) const template inline void pick_seeds(Elements const& elements, Parameters const& parameters, Translator const& tr, size_t & seed1, size_t & seed2) { typedef typename Elements::value_type element_type; typedef typename rtree::element_indexable_type::type indexable_type; typedef pick_seeds_impl < Elements, Parameters, Translator, geometry::dimension::value > impl; typedef typename impl::separation_type separation_type; separation_type separation = 0; impl::apply(elements, parameters, tr, separation, seed1, seed2); } } // namespace linear // from void split_node(node_pointer const& n, node_pointer& n1, node_pointer& n2) const template struct redistribute_elements { typedef typename Options::parameters_type parameters_type; typedef typename rtree::node::type node; typedef typename rtree::internal_node::type internal_node; typedef typename rtree::leaf::type leaf; template static inline void apply(Node & n, Node & second_node, Box & box1, Box & box2, parameters_type const& parameters, Translator const& translator, Allocators & allocators) { typedef typename rtree::elements_type::type elements_type; typedef typename elements_type::value_type element_type; typedef typename rtree::element_indexable_type::type indexable_type; typedef typename index::detail::default_content_result::type content_type; elements_type & elements1 = rtree::elements(n); elements_type & elements2 = rtree::elements(second_node); const size_t elements1_count = parameters.get_max_elements() + 1; BOOST_GEOMETRY_INDEX_ASSERT(elements1.size() == elements1_count, "unexpected number of elements"); // copy original elements - use in-memory storage (std::allocator) // TODO: move if noexcept typedef typename rtree::container_from_elements_type::type container_type; container_type elements_copy(elements1.begin(), elements1.end()); // MAY THROW, STRONG (alloc, copy) // calculate initial seeds size_t seed1 = 0; size_t seed2 = 0; linear::pick_seeds(elements_copy, parameters, translator, seed1, seed2); // prepare nodes' elements containers elements1.clear(); BOOST_GEOMETRY_INDEX_ASSERT(elements2.empty(), "unexpected container state"); BOOST_TRY { // add seeds elements1.push_back(elements_copy[seed1]); // MAY THROW, STRONG (copy) elements2.push_back(elements_copy[seed2]); // MAY THROW, STRONG (alloc, copy) // calculate boxes detail::bounds(rtree::element_indexable(elements_copy[seed1], translator), box1); detail::bounds(rtree::element_indexable(elements_copy[seed2], translator), box2); // initialize areas content_type content1 = index::detail::content(box1); content_type content2 = index::detail::content(box2); BOOST_GEOMETRY_INDEX_ASSERT(2 <= elements1_count, "unexpected elements number"); size_t remaining = elements1_count - 2; // redistribute the rest of the elements for ( size_t i = 0 ; i < elements1_count ; ++i ) { if (i != seed1 && i != seed2) { element_type const& elem = elements_copy[i]; indexable_type const& indexable = rtree::element_indexable(elem, translator); // if there is small number of elements left and the number of elements in node is lesser than min_elems // just insert them to this node if ( elements1.size() + remaining <= parameters.get_min_elements() ) { elements1.push_back(elem); // MAY THROW, STRONG (copy) geometry::expand(box1, indexable); content1 = index::detail::content(box1); } else if ( elements2.size() + remaining <= parameters.get_min_elements() ) { elements2.push_back(elem); // MAY THROW, STRONG (alloc, copy) geometry::expand(box2, indexable); content2 = index::detail::content(box2); } // choose better node and insert element else { // calculate enlarged boxes and areas Box enlarged_box1(box1); Box enlarged_box2(box2); geometry::expand(enlarged_box1, indexable); geometry::expand(enlarged_box2, indexable); content_type enlarged_content1 = index::detail::content(enlarged_box1); content_type enlarged_content2 = index::detail::content(enlarged_box2); content_type content_increase1 = enlarged_content1 - content1; content_type content_increase2 = enlarged_content2 - content2; // choose group which box content have to be enlarged least or has smaller content or has fewer elements if ( content_increase1 < content_increase2 || ( content_increase1 == content_increase2 && ( content1 < content2 || ( content1 == content2 && elements1.size() <= elements2.size() ) ) ) ) { elements1.push_back(elem); // MAY THROW, STRONG (copy) box1 = enlarged_box1; content1 = enlarged_content1; } else { elements2.push_back(elem); // MAY THROW, STRONG (alloc, copy) box2 = enlarged_box2; content2 = enlarged_content2; } } BOOST_GEOMETRY_INDEX_ASSERT(0 < remaining, "unexpected value"); --remaining; } } } BOOST_CATCH(...) { elements1.clear(); elements2.clear(); rtree::destroy_elements::apply(elements_copy, allocators); //elements_copy.clear(); BOOST_RETHROW // RETHROW, BASIC } BOOST_CATCH_END } }; }} // namespace detail::rtree }}} // namespace boost::geometry::index #endif // BOOST_GEOMETRY_INDEX_DETAIL_RTREE_LINEAR_REDISTRIBUTE_ELEMENTS_HPP