func (f *Flappy) mutateFlock() {
sort.Sort(f.birds)
randNet := func() *neural.Net {
return f.birds[int(neural.RandMax(float64(len(f.birds))))].brain
}
best := f.birds[0].brain
for c := range f.birds {
if f.birds[c].dead {
f.birds[c].dead = false
f.birds[c].bird.pos = *f.lvl.NewBirdPos()
f.birds[c].bird.vel = *util.NewVector(SCROLL_SPEED, 0)
f.birds[c].brain = neural.Cross(best, randNet())
if neural.Chance(0.1) {
// penalize best achievement due to mutation
f.birds[c].bestX *= 0.99
f.birds[c].brain.Mutate(0.33)
}
} else {
f.birds[c].bird.pos = f.birds[c].bird.nextPos
f.birds[c].bestX = math.Max(f.birds[c].bird.pos.X, f.birds[c].bestX)
}
}
}
func NewLevel(w, h int) *Level {
lvl := &Level{
size: *util.NewVector(float64(w), float64(h)),
pylons: make([]util.Vector, 0),
birds: make([]*Bird, 0),
}
// min offset from top && bottom
yOffset := float64(PylonHole)
for off := pylonSpacing; off < w; off += pylonSpacing {
hole := neural.RandMax(float64(h)-yOffset*2.0) + yOffset
lvl.pylons = append(lvl.pylons, *util.NewVector(float64(off), hole))
}
return lvl
}
func (l *Level) makeHole(c *int) {
size := int(3 + neural.RandMax(2))
height := int(l.size.Y/float64(BLOCK_SIZE)) - 1 - 3
skip := OBSTACLE_SPACING * 2
if neural.Chance(0.75) {
size = skip
for iter := 0; iter < skip; iter++ {
if iter+*c >= len(l.blocks) {
break
}
if iter%5 == 0 {
x := float64((iter + *c) * BLOCK_SIZE)
y := float64((height + 3) * BLOCK_SIZE)
l.blocks[iter+*c][height+3] = util.NewVector(x, y)
}
}
}
if neural.Chance(0.3) {
for iter := -2; iter < size+3; iter++ {
xIdx := iter + *c
if xIdx < 0 || xIdx >= len(l.blocks) {
continue
}
x := float64(xIdx * BLOCK_SIZE)
y := float64(height * BLOCK_SIZE)
l.blocks[xIdx][height] = util.NewVector(x, y)
}
}
*c += size
}
