(b *testing.B)
| 18 | ) |
| 19 | |
| 20 | func BenchmarkAlgorithm(b *testing.B) { |
| 21 | rand.Seed(time.Now().UnixNano()) |
| 22 | random.Seed(time.Now().UnixNano()) |
| 23 | |
| 24 | file, err := os.Open("../imgs/clown.jpg") |
| 25 | |
| 26 | if err != nil { |
| 27 | panic(err) |
| 28 | } |
| 29 | |
| 30 | imageFile, _, err := image.Decode(file) |
| 31 | |
| 32 | file.Close() |
| 33 | |
| 34 | if err != nil { |
| 35 | log.Fatal(err) |
| 36 | } |
| 37 | |
| 38 | imgData := imageData.ToData(imageFile) |
| 39 | |
| 40 | if err != nil { |
| 41 | log.Fatal("Arg #2 not an integer") |
| 42 | } |
| 43 | |
| 44 | pointFactory := func() normgeom.NormPointGroup { |
| 45 | |
| 46 | return (generator.RandomGenerator{}).Generate(1000) |
| 47 | } |
| 48 | evaluatorFactory := func(n int) evaluator.Evaluator { |
| 49 | return evaluator.NewParallel(fitness.TrianglesImageFunctions(imgData, 5, n), 22) |
| 50 | } |
| 51 | |
| 52 | mutator := mutation.NewGaussianMethod(2/1000, 0.3) |
| 53 | |
| 54 | algo := NewModifiedGenetic(pointFactory, 400, 5, evaluatorFactory, mutator) |
| 55 | |
| 56 | real := func() { |
| 57 | for i := 0; i < 3000; i++ { |
| 58 | algo.Step() |
| 59 | } |
| 60 | } |
| 61 | real() |
| 62 | } |
nothing calls this directly
no test coverage detected