rtree_sample.go

package main

import (
	"fmt"
	"math/rand"
	"strconv"

	"github.com/dhconnelly/rtreego"
)

type Thing struct {
	where *rtreego.Rect
	name  string
}

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

func main() {
	rt := rtreego.NewTree(2, 1000, 1000000)

	objSlice := make([]*Thing, 0)

	for i := 0; i < 10000; i++ {
		x := -5 + rand.Float64()*10
		y := -5 + rand.Float64()*10
		p1 := rtreego.Point{x, y}
		r1, _ := rtreego.NewRect(p1, []float64{0, 0})
		str1 := "foo" + strconv.Itoa(i)
		thing1 := &Thing{r1, str1}
		rt.Insert(thing1)
		objSlice = append(objSlice, thing1)
	}

	size := rt.Size() // returns 2
	fmt.Println("tree size = ", size)

	bb, _ := rtreego.NewRect(rtreego.Point{-5, -5}, []float64{.01, .01})
	// Get a slice of the objects in rt that intersect bb:
	results := rt.SearchIntersect(bb)

	for _, obj := range results {
		if thing, ok := obj.(*Thing); ok {
			fmt.Println("results = ", thing.name)
		}
	}

	//delete half of the objects
	fmt.Println("==Deleting thing2==")

	for i, obj := range objSlice {
		if i < len(objSlice)/2 {
			rt.Delete(obj)
		}
	}

	results2 := rt.SearchIntersect(bb)
	for _, obj := range results2 {
		if thing, ok := obj.(*Thing); ok {
			fmt.Println("results = ", thing.name)
		}
	}
}

This code tests out the performance of rtree implementation.