def crossover(so1: SoundObject, so2: SoundObject) -> SoundObject:
so1 = copy.deepcopy(so1)
so2 = copy.deepcopy(so2)
env1 = sm.waves.sin(sm.waves.tspan(so1.duration), random.uniform(0.1, 4),
1.0, random.uniform(0, 2 * np.pi))
env2 = sm.waves.sin(sm.waves.tspan(so2.duration), random.uniform(0.1, 4),
1.0, random.uniform(0, 2 * np.pi))
so1.samples *= env1
so2.samples *= env2
so1.t = 0
so2.t = random.uniform(0, so1.duration)
return sm.sound.join(
[so1.get_normalize_to(0.5),
so2.get_normalize_to(0.5)])
def evolve(lso, n_generations, elitism, mut_prob, fitness_weights,
fitness_params):
npop = len(lso)
population = [(so, fitness(so, fitness_weights, fitness_params))
for so in lso]
for _ in range(n_generations):
n_child = round(npop * (1 - elitism))
pot_parents = copy.deepcopy(population)
childs = []
while len(childs) < n_child:
if len(pot_parents) < 2: pot_parents = copy.deepcopy(population)
parent0 = random.choices(pot_parents,
weights=[
score for _, score in pot_parents
],
k=1)[0]
pot_parents.remove(parent0)
parent1 = random.choices(pot_parents,
weights=[
score for _, score in pot_parents
],
k=1)[0]
pot_parents.remove(parent1)
child = crossover(parent0[0], parent1[0])
while random.uniform(0, 1) < mut_prob:
mut = random.choice(mutations)
print(f"Mutating: {mut.__name__}")
new_child = mut(child)
if not np.isnan(new_child.samples).any():
child = new_child
else:
print("Mutation Failed")
try:
child = SoundObject(
lr.effects.trim(child.get_normalize_to(1.0)))
except:
continue
fit = fitness(child, fitness_weights, fitness_params)
if np.isnan(fit) or np.isinf(fit): continue
childs.append((child, fit))
population = sorted(population, key=lambda ind: ind[1],
reverse=True)[:int(elitism * npop)] + childs
print(max([s for _, s in population]))
out = []
for so, _ in population:
ptrack, mtrack = so.track_pitch()
pitch = lr.hz_to_midi(np.mean(ptrack))
velocity = np.clip(np.mean(mtrack) * 127, 0, 127)
out.append((so, pitch, velocity))
return out
