Refactor random.WeightedChooser, unsing generics

This commit is contained in:
Deluan 2024-05-17 15:45:34 -04:00
parent a7a4fb522c
commit 4d28d534cc
3 changed files with 68 additions and 41 deletions

View File

@ -267,8 +267,8 @@ func (e *externalMetadata) SimilarSongs(ctx context.Context, id string, count in
return nil, ctx.Err()
}
weightedSongs := random.NewWeightedRandomChooser()
addArtist := func(a model.Artist, weightedSongs *random.WeightedChooser, count, artistWeight int) error {
weightedSongs := random.NewWeightedChooser[model.MediaFile]()
addArtist := func(a model.Artist, weightedSongs *random.WeightedChooser[model.MediaFile], count, artistWeight int) error {
if utils.IsCtxDone(ctx) {
log.Warn(ctx, "SimilarSongs call canceled", ctx.Err())
return ctx.Err()
@ -302,12 +302,12 @@ func (e *externalMetadata) SimilarSongs(ctx context.Context, id string, count in
var similarSongs model.MediaFiles
for len(similarSongs) < count && weightedSongs.Size() > 0 {
s, err := weightedSongs.GetAndRemove()
s, err := weightedSongs.Pick()
if err != nil {
log.Warn(ctx, "Error getting weighted song", err)
continue
}
similarSongs = append(similarSongs, s.(model.MediaFile))
similarSongs = append(similarSongs, s)
}
return similarSongs, nil

View File

@ -2,42 +2,46 @@ package random
import (
"errors"
"slices"
)
type WeightedChooser struct {
entries []interface{}
// WeightedChooser allows to randomly choose an entry based on their weights
// (higher weight = higher chance of being chosen). Based on the subtraction method described in
// https://eli.thegreenplace.net/2010/01/22/weighted-random-generation-in-python/
type WeightedChooser[T any] struct {
entries []T
weights []int
totalWeight int
}
func NewWeightedRandomChooser() *WeightedChooser {
return &WeightedChooser{}
func NewWeightedChooser[T any]() *WeightedChooser[T] {
return &WeightedChooser[T]{}
}
func (w *WeightedChooser) Add(value interface{}, weight int) {
func (w *WeightedChooser[T]) Add(value T, weight int) {
w.entries = append(w.entries, value)
w.weights = append(w.weights, weight)
w.totalWeight += weight
}
// GetAndRemove choose a random entry based on their weights, and removes it from the list
func (w *WeightedChooser) GetAndRemove() (interface{}, error) {
// Pick choose a random entry based on their weights, and removes it from the list
func (w *WeightedChooser[T]) Pick() (T, error) {
var empty T
if w.totalWeight == 0 {
return nil, errors.New("cannot choose from zero weight")
return empty, errors.New("cannot choose from zero weight")
}
i, err := w.weightedChoice()
if err != nil {
return nil, err
return empty, err
}
entry := w.entries[i]
w.Remove(i)
_ = w.Remove(i)
return entry, nil
}
// Based on https://eli.thegreenplace.net/2010/01/22/weighted-random-generation-in-python/
func (w *WeightedChooser) weightedChoice() (int, error) {
if w.totalWeight == 0 {
return 0, errors.New("no choices available")
func (w *WeightedChooser[T]) weightedChoice() (int, error) {
if len(w.entries) == 0 {
return 0, errors.New("cannot choose from empty list")
}
rnd := Int64(w.totalWeight)
for i, weight := range w.weights {
@ -49,17 +53,18 @@ func (w *WeightedChooser) weightedChoice() (int, error) {
return 0, errors.New("internal error - code should not reach this point")
}
func (w *WeightedChooser) Remove(i int) {
func (w *WeightedChooser[T]) Remove(i int) error {
if i < 0 || i >= len(w.entries) {
return errors.New("index out of bounds")
}
w.totalWeight -= w.weights[i]
w.weights[i] = w.weights[len(w.weights)-1]
w.weights = w.weights[:len(w.weights)-1]
w.entries[i] = w.entries[len(w.entries)-1]
w.entries[len(w.entries)-1] = nil
w.entries = w.entries[:len(w.entries)-1]
w.weights = slices.Delete(w.weights, i, i+1)
w.entries = slices.Delete(w.entries, i, i+1)
return nil
}
func (w *WeightedChooser) Size() int {
func (w *WeightedChooser[T]) Size() int {
return len(w.entries)
}

View File

@ -5,35 +5,57 @@ import (
. "github.com/onsi/gomega"
)
var _ = Describe("WeightedRandomChooser", func() {
var w *WeightedChooser
var _ = Describe("WeightedChooser", func() {
var w *WeightedChooser[int]
BeforeEach(func() {
w = NewWeightedRandomChooser()
w = NewWeightedChooser[int]()
for i := 0; i < 10; i++ {
w.Add(i, i)
w.Add(i, i+1)
}
})
It("removes a random item", func() {
It("selects and removes a random item", func() {
Expect(w.Size()).To(Equal(10))
_, err := w.GetAndRemove()
_, err := w.Pick()
Expect(err).ToNot(HaveOccurred())
Expect(w.Size()).To(Equal(9))
})
It("removes items", func() {
Expect(w.Size()).To(Equal(10))
for i := 0; i < 10; i++ {
Expect(w.Remove(0)).To(Succeed())
}
Expect(w.Size()).To(Equal(0))
})
It("returns error if trying to remove an invalid index", func() {
Expect(w.Size()).To(Equal(10))
Expect(w.Remove(-1)).ToNot(Succeed())
Expect(w.Remove(10000)).ToNot(Succeed())
Expect(w.Size()).To(Equal(10))
})
It("returns the sole item", func() {
w = NewWeightedRandomChooser()
w.Add("a", 1)
Expect(w.GetAndRemove()).To(Equal("a"))
ws := NewWeightedChooser[string]()
ws.Add("a", 1)
Expect(ws.Pick()).To(Equal("a"))
})
It("returns all items from the list", func() {
for i := 0; i < 10; i++ {
Expect(w.Pick()).To(BeElementOf(0, 1, 2, 3, 4, 5, 6, 7, 8, 9))
}
Expect(w.Size()).To(Equal(0))
})
It("fails when trying to choose from empty set", func() {
w = NewWeightedRandomChooser()
w.Add("a", 1)
w.Add("b", 1)
Expect(w.GetAndRemove()).To(BeElementOf("a", "b"))
Expect(w.GetAndRemove()).To(BeElementOf("a", "b"))
_, err := w.GetAndRemove()
w = NewWeightedChooser[int]()
w.Add(1, 1)
w.Add(2, 1)
Expect(w.Pick()).To(BeElementOf(1, 2))
Expect(w.Pick()).To(BeElementOf(1, 2))
_, err := w.Pick()
Expect(err).To(HaveOccurred())
})