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// Copyright ©2019 The Gonum Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package vptree
import (
"flag"
"fmt"
"math"
"os"
"reflect"
"sort"
"strings"
"testing"
"unsafe"
"golang.org/x/exp/rand"
)
var (
genDot = flag.Bool("dot", false, "generate dot code for failing trees")
dotLimit = flag.Int("dotmax", 100, "specify maximum size for tree output for dot format")
)
var (
// Using example from WP article: https://en.wikipedia.org/w/index.php?title=K-d_tree&oldid=887573572.
wpData = []Comparable{
Point{2, 3},
Point{5, 4},
Point{9, 6},
Point{4, 7},
Point{8, 1},
Point{7, 2},
}
)
var newTests = []struct {
data []Comparable
effort int
}{
{data: wpData, effort: 0},
{data: wpData, effort: 1},
{data: wpData, effort: 2},
{data: wpData, effort: 4},
{data: wpData, effort: 8},
}
func TestNew(t *testing.T) {
for i, test := range newTests {
var tree *Tree
var err error
var panicked bool
func() {
defer func() {
if r := recover(); r != nil {
panicked = true
}
}()
tree, err = New(test.data, test.effort, rand.NewSource(1))
}()
if panicked {
t.Errorf("unexpected panic for test %d", i)
continue
}
if err != nil {
t.Errorf("unexpected error for test %d: %v", i, err)
continue
}
if !tree.Root.isVPTree() {
t.Errorf("tree %d is not vp-tree", i)
}
if t.Failed() && *genDot && tree.Len() <= *dotLimit {
err := dotFile(tree, fmt.Sprintf("TestNew%d", i), "")
if err != nil {
t.Fatalf("failed to write DOT file: %v", err)
}
}
}
}
type compFn func(v, radius float64) bool
func closer(v, radius float64) bool { return v <= radius }
func further(v, radius float64) bool { return v >= radius }
func (n *Node) isVPTree() bool {
if n == nil {
return true
}
if !n.Closer.isPartitioned(n.Point, closer, n.Radius) {
return false
}
if !n.Further.isPartitioned(n.Point, further, n.Radius) {
return false
}
return n.Closer.isVPTree() && n.Further.isVPTree()
}
func (n *Node) isPartitioned(vp Comparable, fn compFn, radius float64) bool {
if n == nil {
return true
}
if n.Closer != nil && !fn(vp.Distance(n.Closer.Point), radius) {
return false
}
if n.Further != nil && !fn(vp.Distance(n.Further.Point), radius) {
return false
}
return n.Closer.isPartitioned(vp, fn, radius) && n.Further.isPartitioned(vp, fn, radius)
}
func nearest(q Comparable, p []Comparable) (Comparable, float64) {
min := q.Distance(p[0])
var r int
for i := 1; i < len(p); i++ {
d := q.Distance(p[i])
if d < min {
min = d
r = i
}
}
return p[r], min
}
func TestNearestRandom(t *testing.T) {
rnd := rand.New(rand.NewSource(1))
const (
min = 0.0
max = 1000.0
dims = 4
setSize = 10000
)
var randData []Comparable
for i := 0; i < setSize; i++ {
p := make(Point, dims)
for j := 0; j < dims; j++ {
p[j] = (max-min)*rnd.Float64() + min
}
randData = append(randData, p)
}
tree, err := New(randData, 10, rand.NewSource(1))
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
for i := 0; i < setSize; i++ {
q := make(Point, dims)
for j := 0; j < dims; j++ {
q[j] = (max-min)*rnd.Float64() + min
}
got, _ := tree.Nearest(q)
want, _ := nearest(q, randData)
if !reflect.DeepEqual(got, want) {
t.Fatalf("unexpected result from query %d %.3f: got:%.3f want:%.3f", i, q, got, want)
}
}
}
func TestNearest(t *testing.T) {
tree, err := New(wpData, 3, rand.NewSource(1))
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
for _, q := range append([]Comparable{
Point{4, 6},
// Point{7, 5}, // Omitted because it is ambiguously finds [9 6] or [5 4].
Point{8, 7},
Point{6, -5},
Point{1e5, 1e5},
Point{1e5, -1e5},
Point{-1e5, 1e5},
Point{-1e5, -1e5},
Point{1e5, 0},
Point{0, -1e5},
Point{0, 1e5},
Point{-1e5, 0},
}, wpData...) {
gotP, gotD := tree.Nearest(q)
wantP, wantD := nearest(q, wpData)
if !reflect.DeepEqual(gotP, wantP) {
t.Errorf("unexpected result for query %.3f: got:%.3f want:%.3f", q, gotP, wantP)
}
if gotD != wantD {
t.Errorf("unexpected distance for query %.3f : got:%v want:%v", q, gotD, wantD)
}
}
}
func nearestN(n int, q Comparable, p []Comparable) []ComparableDist {
nk := NewNKeeper(n)
for i := 0; i < len(p); i++ {
nk.Keep(ComparableDist{Comparable: p[i], Dist: q.Distance(p[i])})
}
if len(nk.Heap) == 1 {
return nk.Heap
}
sort.Sort(nk)
for i, j := 0, len(nk.Heap)-1; i < j; i, j = i+1, j-1 {
nk.Heap[i], nk.Heap[j] = nk.Heap[j], nk.Heap[i]
}
return nk.Heap
}
func TestNearestSetN(t *testing.T) {
data := append([]Comparable{
Point{4, 6},
Point{7, 5}, // OK here because we collect N.
Point{8, 7},
Point{6, -5},
Point{1e5, 1e5},
Point{1e5, -1e5},
Point{-1e5, 1e5},
Point{-1e5, -1e5},
Point{1e5, 0},
Point{0, -1e5},
Point{0, 1e5},
Point{-1e5, 0}},
wpData[:len(wpData)-1]...)
tree, err := New(wpData, 3, rand.NewSource(1))
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
for k := 1; k <= len(wpData); k++ {
for _, q := range data {
wantP := nearestN(k, q, wpData)
nk := NewNKeeper(k)
tree.NearestSet(nk, q)
var max float64
wantD := make(map[float64]map[string]struct{})
for _, p := range wantP {
if p.Dist > max {
max = p.Dist
}
d, ok := wantD[p.Dist]
if !ok {
d = make(map[string]struct{})
}
d[fmt.Sprint(p.Comparable)] = struct{}{}
wantD[p.Dist] = d
}
gotD := make(map[float64]map[string]struct{})
for _, p := range nk.Heap {
if p.Dist > max {
t.Errorf("unexpected distance for point %.3f: got:%v want:<=%v", p.Comparable, p.Dist, max)
}
d, ok := gotD[p.Dist]
if !ok {
d = make(map[string]struct{})
}
d[fmt.Sprint(p.Comparable)] = struct{}{}
gotD[p.Dist] = d
}
// If the available number of slots does not fit all the coequal furthest points
// we will fail the check. So remove, but check them minimally here.
if !reflect.DeepEqual(wantD[max], gotD[max]) {
// The best we can do at this stage is confirm that there are an equal number of matches at this distance.
if len(gotD[max]) != len(wantD[max]) {
t.Errorf("unexpected number of maximal distance points: got:%d want:%d", len(gotD[max]), len(wantD[max]))
}
delete(wantD, max)
delete(gotD, max)
}
if !reflect.DeepEqual(gotD, wantD) {
t.Errorf("unexpected result for k=%d query %.3f: got:%v want:%v", k, q, gotD, wantD)
}
}
}
}
var nearestSetDistTests = []Point{
{4, 6},
{7, 5},
{8, 7},
{6, -5},
}
func TestNearestSetDist(t *testing.T) {
tree, err := New(wpData, 3, rand.NewSource(1))
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
for i, q := range nearestSetDistTests {
for d := 1.0; d < 100; d += 0.1 {
dk := NewDistKeeper(d)
tree.NearestSet(dk, q)
hits := make(map[string]float64)
for _, p := range wpData {
hits[fmt.Sprint(p)] = p.Distance(q)
}
for _, p := range dk.Heap {
var done bool
if p.Comparable == nil {
done = true
continue
}
delete(hits, fmt.Sprint(p.Comparable))
if done {
t.Error("expectedly finished heap iteration")
break
}
dist := p.Comparable.Distance(q)
if dist > d {
t.Errorf("Test %d: query %v found %v expect %.3f <= %.3f", i, q, p, dist, d)
}
}
for p, dist := range hits {
if dist <= d {
t.Errorf("Test %d: query %v missed %v expect %.3f > %.3f", i, q, p, dist, d)
}
}
}
}
}
func TestDo(t *testing.T) {
tree, err := New(wpData, 3, rand.NewSource(1))
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
var got []Point
fn := func(c Comparable, _ int) (done bool) {
got = append(got, c.(Point))
return
}
killed := tree.Do(fn)
want := make([]Point, len(wpData))
for i, p := range wpData {
want[i] = p.(Point)
}
sort.Sort(lexical(got))
sort.Sort(lexical(want))
if !reflect.DeepEqual(got, want) {
t.Errorf("unexpected result from tree iteration: got:%v want:%v", got, want)
}
if killed {
t.Error("tree iteration unexpectedly killed")
}
}
type lexical []Point
func (c lexical) Len() int { return len(c) }
func (c lexical) Less(i, j int) bool {
a, b := c[i], c[j]
l := len(a)
if len(b) < l {
l = len(b)
}
for k, v := range a[:l] {
if v < b[k] {
return true
}
if v > b[k] {
return false
}
}
return len(a) < len(b)
}
func (c lexical) Swap(i, j int) { c[i], c[j] = c[j], c[i] }
func BenchmarkNew(b *testing.B) {
for _, effort := range []int{0, 10, 100} {
b.Run(fmt.Sprintf("New:%d", effort), func(b *testing.B) {
rnd := rand.New(rand.NewSource(1))
p := make([]Comparable, 1e5)
for i := range p {
p[i] = Point{rnd.Float64(), rnd.Float64(), rnd.Float64()}
}
b.ResetTimer()
for i := 0; i < b.N; i++ {
_, err := New(p, effort, rand.NewSource(1))
if err != nil {
b.Fatalf("unexpected error: %v", err)
}
}
})
}
}
func Benchmark(b *testing.B) {
var r Comparable
var d float64
queryBenchmarks := []struct {
name string
fn func(data []Comparable, tree *Tree, rnd *rand.Rand) func(*testing.B)
}{
{
name: "NearestBrute", fn: func(data []Comparable, _ *Tree, rnd *rand.Rand) func(b *testing.B) {
return func(b *testing.B) {
for i := 0; i < b.N; i++ {
r, d = nearest(Point{rnd.Float64(), rnd.Float64(), rnd.Float64()}, data)
}
if r == nil {
b.Error("unexpected nil result")
}
if math.IsNaN(d) {
b.Error("unexpected NaN result")
}
}
},
},
{
name: "NearestBruteN10", fn: func(data []Comparable, _ *Tree, rnd *rand.Rand) func(b *testing.B) {
return func(b *testing.B) {
var r []ComparableDist
for i := 0; i < b.N; i++ {
r = nearestN(10, Point{rnd.Float64(), rnd.Float64(), rnd.Float64()}, data)
}
if len(r) != 10 {
b.Error("unexpected result length", len(r))
}
}
},
},
{
name: "Nearest", fn: func(_ []Comparable, tree *Tree, rnd *rand.Rand) func(b *testing.B) {
return func(b *testing.B) {
for i := 0; i < b.N; i++ {
r, d = tree.Nearest(Point{rnd.Float64(), rnd.Float64(), rnd.Float64()})
}
if r == nil {
b.Error("unexpected nil result")
}
if math.IsNaN(d) {
b.Error("unexpected NaN result")
}
}
},
},
{
name: "NearestSetN10", fn: func(_ []Comparable, tree *Tree, rnd *rand.Rand) func(b *testing.B) {
return func(b *testing.B) {
nk := NewNKeeper(10)
for i := 0; i < b.N; i++ {
tree.NearestSet(nk, Point{rnd.Float64(), rnd.Float64(), rnd.Float64()})
if nk.Len() != 10 {
b.Error("unexpected result length")
}
nk.Heap = nk.Heap[:1]
nk.Heap[0] = ComparableDist{Dist: inf}
}
}
},
},
}
for _, effort := range []int{0, 3, 10, 30, 100, 300} {
rnd := rand.New(rand.NewSource(1))
data := make([]Comparable, 1e5)
for i := range data {
data[i] = Point{rnd.Float64(), rnd.Float64(), rnd.Float64()}
}
tree, err := New(data, effort, rand.NewSource(1))
if err != nil {
b.Errorf("unexpected error for effort=%d: %v", effort, err)
continue
}
if !tree.Root.isVPTree() {
b.Fatal("tree is not vantage point tree")
}
for i := 0; i < 1e3; i++ {
q := Point{rnd.Float64(), rnd.Float64(), rnd.Float64()}
gotP, gotD := tree.Nearest(q)
wantP, wantD := nearest(q, data)
if !reflect.DeepEqual(gotP, wantP) {
b.Errorf("unexpected result for query %.3f: got:%.3f want:%.3f", q, gotP, wantP)
}
if gotD != wantD {
b.Errorf("unexpected distance for query %.3f: got:%v want:%v", q, gotD, wantD)
}
}
if b.Failed() && *genDot && tree.Len() <= *dotLimit {
err := dotFile(tree, "TestBenches", "")
if err != nil {
b.Fatalf("failed to write DOT file: %v", err)
}
return
}
for _, bench := range queryBenchmarks {
if strings.Contains(bench.name, "Brute") && effort != 0 {
continue
}
b.Run(fmt.Sprintf("%s:%d", bench.name, effort), bench.fn(data, tree, rnd))
}
}
}
func dot(t *Tree, label string) string {
if t == nil {
return ""
}
var (
s []string
follow func(*Node)
)
follow = func(n *Node) {
id := uintptr(unsafe.Pointer(n))
c := fmt.Sprintf("%d[label = \"<Closer> |<Elem> %.3f/%.3f|<Further>\"];",
id, n.Point, n.Radius)
if n.Closer != nil {
c += fmt.Sprintf("\n\t\tedge [arrowhead=normal]; \"%d\":Closer -> \"%d\":Elem [label=%.3f];",
id, uintptr(unsafe.Pointer(n.Closer)), n.Point.Distance(n.Closer.Point))
follow(n.Closer)
}
if n.Further != nil {
c += fmt.Sprintf("\n\t\tedge [arrowhead=normal]; \"%d\":Further -> \"%d\":Elem [label=%.3f];",
id, uintptr(unsafe.Pointer(n.Further)), n.Point.Distance(n.Further.Point))
follow(n.Further)
}
s = append(s, c)
}
if t.Root != nil {
follow(t.Root)
}
return fmt.Sprintf("digraph %s {\n\tnode [shape=record,height=0.1];\n\t%s\n}\n",
label,
strings.Join(s, "\n\t"),
)
}
func dotFile(t *Tree, label, dotString string) (err error) {
if t == nil && dotString == "" {
return
}
f, err := os.Create(label + ".dot")
if err != nil {
return
}
defer f.Close()
if dotString == "" {
fmt.Fprint(f, dot(t, label))
} else {
fmt.Fprint(f, dotString)
}
return
}