rtreego

an R-Tree library for Go

This project is maintained by dhconnelly

rtreego

A library for efficiently storing and querying spatial data in the Go programming language.

About

The R-tree is a popular data structure for efficiently storing and querying spatial objects; one common use is implementing geospatial indexes in database management systems. The variant implemented here, known as the R*-tree, improves performance and increases storage utilization. Both bounding-box queries and k-nearest-neighbor queries are supported.

R-trees are balanced, so maximum tree height is guaranteed to be logarithmic in the number of entries; however, good worst-case performance is not guaranteed. Instead, a number of rebalancing heuristics are applied that perform well in practice. For more details please refer to the references.

This implementation handles the general N-dimensional case; for a more efficient implementation for the 3-dimensional case, see Patrick Higgins' fork.

Getting Started

Get the source code from GitHub or, with Go 1 installed, run go get github.com/dhconnelly/rtreego.

Make sure you import github.com/dhconnelly/rtreego in your Go source files.

Documentation

Storing, updating, and deleting objects

To create a new tree, specify the number of spatial dimensions and the minimum and maximum branching factor:

rt := rtreego.NewTree(2, 25, 50)

Any type that implements the Spatial interface can be stored in the tree:

type Spatial interface {
    Bounds() *Rect
}

Rects are data structures for representing spatial objects, while Points represent spatial locations. Creating Points is easy--they're just slices of float64s:

p1 := rtreego.Point{0.4, 0.5}
p2 := rtreego.Point{6.2, -3.4}

To create a Rect, specify a location and the lengths of the sides:

r1 := rtreego.NewRect(p1, []float64{1, 2})
r2 := rtreego.NewRect(p2, []float64{1.7, 2.7})

To demonstrate, let's create and store some test data.

type Thing struct {
    where *Rect
    name string
}

func (t *Thing) Bounds() *Rect {
    return t.where
}

rt.Insert(&Thing{r1, "foo"})
rt.Insert(&Thing{r2, "bar"})

size := rt.Size() // returns 2

We can insert and delete objects from the tree in any order.

rt.Delete(thing2)
// do some stuff...
rt.Insert(anotherThing)

If you want to store points instead of rectangles, you can easily convert a point into a rectangle using the ToRect method:

var tol = 0.01

type Somewhere struct {
    location rtreego.Point
    name string
    wormhole chan int
}

func (s *Somewhere) Bounds() *Rect {
    // define the bounds of s to be a rectangle centered at s.location
    // with side lengths 2 * tol:
    return s.location.ToRect(tol)
}

rt.Insert(&Somewhere{rtreego.Point{0, 0}, "Someplace", nil})

If you want to update the location of an object, you must delete it, update it, and re-insert. Just modifying the object so that the *Rect returned by Location() changes, without deleting and re-inserting the object, will corrupt the tree.

Queries

Bounding-box and k-nearest-neighbors queries are supported.

Bounding-box queries require a search *Rect argument and come in two flavors: containment search and intersection search. The former returns all objects that fall strictly inside the search rectangle, while the latter returns all objects that touch the search rectangle.

bb := rtreego.NewRect(rtreego.Point{1.7, -3.4}, []float64{3.2, 1.9})

// Get a slice of the objects in rt that intersect bb:
results, _ := rt.SearchIntersect(bb)

// Get a slice of the objects in rt that are contained inside bb:
results, _ = rt.SearchContained(bb)

Nearest-neighbor queries find the objects in a tree closest to a specified query point.

q := rtreego.Point{6.5, -2.47}
k := 5

// Get a slice of the k objects in rt closest to q:
results, _ = rt.SearchNearestNeighbors(q, k)

More information

See GoPkgDoc for full API documentation.

References

Author

Written by Daniel Connelly (dhconnelly@gmail.com).

License

rtreego is released under a BSD-style license, described here and in the LICENSE file:

Copyright (c) 2012, Daniel Connelly. All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

  2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

  3. Neither the name of Daniel Connelly nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.