This repository used to live at mariusae/ocaml-rtree where most of the core implementation was done.
This implements a simple rtree library according to Guttman's original paper. Currently node splitting is done through the quadratic algorithm in that paper.
Some benchmarks are available too.
There are two key elements to an rtree. The type of envelopes used and the type of the values being store in the tree. These values must come with a function to calculate an envelope.
The core library comes with an implementation of envelopes as two-dimensional rectangles.
# #show_module Rtree.Rectangle;;
module Rectangle :
sig
type t
val dimensions : int
val compare_dim : int -> t -> t -> int
val t : t Repr__Type.t
val empty : t
val intersects : t -> t -> bool
val merge : t -> t -> t
val merge_many : t list -> t
val area : t -> float
val contains : t -> t -> bool
val coords : t -> float * float * float * float
val v : x0:float -> y0:float -> x1:float -> y1:float -> t
end
If you wanted to store lines in your rtree, one possible implementation might be the following.
module Line = struct
type t = { p0 : float * float; p1 : float * float }
let t =
let open Repr in
record "line" (fun p0 p1 -> { p0; p1 })
|+ field "p0" (pair float float) (fun t -> t.p0)
|+ field "p1" (pair float float) (fun t -> t.p1)
|> sealr
type envelope = Rtree.Rectangle.t
let envelope { p0 = (x1, y1); p1 = (x2, y2) } =
let x0 = Float.min x1 x2 in
let x1 = Float.max x1 x2 in
let y0 = Float.min y1 y2 in
let y1 = Float.max y1 y2 in
Rtree.Rectangle.v ~x0 ~y0 ~x1 ~y1
end
module R = Rtree.Make(Rtree.Rectangle)(Line)
To insert into an rtree, you simply pass a value into a pre-existing rtree. You can create an empty rtree where you control the maximum node load size. This is essentially the branching factor in the tree. The correct value is hard to guess.
# let index = R.empty 8;;
val index : R.t = <abstr>
# let index = R.insert index Line.{ p0 = (1., 2.); p1 = (3., 3.) };;
val index : R.t = <abstr>
# let index = R.insert index Line.{ p0 = (4., 4.); p1 = (5., 5.) };;
val index : R.t = <abstr>
If you have a list of values to put into an rtree, then you are better off using the load
function instead
of folding and inserting. This uses the OMT algorithm and should give you a more optimised rtree layout.
# let lines =
Line.[
{ p0 = (0., 0.); p1 = (1., 1.) };
{ p0 = (1., 1.); p1 = (2., 2.) };
{ p0 = (2., 2.); p1 = (3., 3.) };
{ p0 = (3., 3.); p1 = (4., 4.) };
]
in
let idx = R.load ~max_node_load:2 lines in
print_endline (Repr.to_string R.t idx)
{"max_node_load":2,"tree":{"Node":[[[0,2,0,2],{"Leaf":[[[0,1,0,1],{"p0":[0,0],"p1":[1,1]}],[[1,2,1,2],{"p0":[1,1],"p1":[2,2]}]]}],[[2,4,2,4],{"Leaf":[[[2,3,2,3],{"p0":[2,2],"p1":[3,3]}],[[3,4,3,4],{"p0":[3,3],"p1":[4,4]}]]}]]}}
- : unit = ()
Also see image.ml for rendering an rtree with vg.
Finding values requires you to pass in a search envelope. A list of result, perhaps empty, will be returned.
# R.find index (Rtree.Rectangle.v ~x0:0. ~y0:0. ~x1:3. ~y1:3.);;
- : Line.t list = [{Line.p0 = (1., 2.); p1 = (3., 3.)}]
# R.find index (Rtree.Rectangle.v ~x0:0. ~y0:0. ~x1:5. ~y1:5.);;
- : Line.t list =
[{Line.p0 = (4., 4.); p1 = (5., 5.)}; {Line.p0 = (1., 2.); p1 = (3., 3.)}]
Rtree asks you to provide a runtime representation of your stored values, which allows you to persist your index easily.
# Fmt.pr "%a" (Repr.pp R.t) index;;
{"max_node_load":8,"tree":{"Leaf":[[[4,5,4,5],{"p0":[4,4],"p1":[5,5]}],[[1,3,2,3],{"p0":[1,2],"p1":[3,3]}]]}}
- : unit = ()