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This Quick Start section shows simple way to creating a typical R-tree and perform spatial query.
The code below assumes that following files are included and namespaces used.
#include <boost/geometry.hpp> #include <boost/geometry/geometries/point.hpp> #include <boost/geometry/geometries/box.hpp> #include <boost/geometry/index/rtree.hpp> // to store queries results #include <vector> // just for output #include <iostream> #include <boost/foreach.hpp> namespace bg = boost::geometry; namespace bgi = boost::geometry::index;
Typically you'll store e.g. std::pair<Box, MyGeometryId>
in the R-tree. MyGeometryId
will be some identifier of a complex Geometry
stored in other container, e.g. index type of a Polygon
stored in the vector or an iterator of list of Ring
s.
To keep it simple to define Value
we will use predefined Box and unsigned int.
typedef bg::model::point<float, 2, bg::cs::cartesian> point; typedef bg::model::box<point> box; typedef std::pair<box, unsigned> value;
R-tree may be created using various algorithm and parameters. You should choose the algorithm you'll find the best for your purpose. In this example we will use quadratic algorithm. Parameters are passed as template parameters. Maximum number of elements in nodes is set to 16.
// create the rtree using default constructor bgi::rtree< value, bgi::quadratic<16> > rtree;
Typically Value
s will be
generated in a loop from e.g. Polygon
s
stored in some other container. In this case Box
objects will probably be created with geometry::envelope()
function. But to keep it simple lets just
generate some boxes manually and insert them into the R-tree by using insert()
method.
// create some values for ( unsigned i = 0 ; i < 10 ; ++i ) { // create a box box b(point(i + 0.0f, i + 0.0f), point(i + 0.5f, i + 0.5f)); // insert new value rtree.insert(std::make_pair(b, i)); }
There are various types of spatial queries that may be performed, they can
be even combined together in one call. For simplicity, we use the default
one. The following query return values intersecting a box. The sequence of
Values
in the result is not
specified.
// find values intersecting some area defined by a box box query_box(point(0, 0), point(5, 5)); std::vector<value> result_s; rtree.query(bgi::intersects(query_box), std::back_inserter(result_s));
Other type of query is k-nearest neighbor search. It returns some number
of values nearest to some point in space. The default knn query may be performed
as follows. The sequence of Values
in the result is not specified.
// find 5 nearest values to a point std::vector<value> result_n; rtree.query(bgi::nearest(point(0, 0), 5), std::back_inserter(result_n));
At the end we'll print results.
// display results std::cout << "spatial query box:" << std::endl; std::cout << bg::wkt<box>(query_box) << std::endl; std::cout << "spatial query result:" << std::endl; BOOST_FOREACH(value const& v, result_s) std::cout << bg::wkt<box>(v.first) << " - " << v.second << std::endl; std::cout << "knn query point:" << std::endl; std::cout << bg::wkt<point>(point(0, 0)) << std::endl; std::cout << "knn query result:" << std::endl; BOOST_FOREACH(value const& v, result_n) std::cout << bg::wkt<box>(v.first) << " - " << v.second << std::endl;
More information about the R-tree implementation, other algorithms and queries may be found in other parts of this documentation.