def explore():
INDEX_EXPLORING = 10
here = get_best_from_all_gens(1)[0]
best_vec = here["vector"]
orig_res = here["results"]
print(orig_res[0] / 1e11, orig_res[1] / 1e11)
values = []
for i in range(-5, 5):
if i == 0:
continue
copied = [j for j in best_vec]
toadd = i * 1e-15
copied[INDEX_EXPLORING] += toadd
# res = [0, 0]
res = get_errors(TEAM_KEY, copied)
print(i, res[0] / 1e11, res[1] / 1e11,
(fitness(res) - fitness(orig_res)) / 1e11)
values.append({
"index": INDEX_EXPLORING,
"difference": toadd,
"results": res
})
with open("exploring.json") as f:
oldvals = json.load(f)
for val in values:
oldvals["explorations"].append(val)
with open("exploring.json", "w") as f:
json.dump(oldvals, f)
def get_best():
here = get_best_from_all_gens(200)
here = sorted(here, key=lambda i: fitness(i["results"]))
for i in range(200):
if (i == 2):
get_vector_history(here[i]["vector"], here[i]["file"])
break
def select_from_children(children, POPULATION_SIZE, CHILDREN_SIZE):
values = []
for i in range(CHILDREN_SIZE):
values.append(children[i]["child"])
values = sorted(values, key=lambda i: fitness(i["results"]))
ret = []
for i in range(POPULATION_SIZE):
ret.append(values[i])
return ret
def select(vecs, POPULATION_SIZE):
vecs = sorted(vecs, key=lambda i: fitness(i["results"]))
ret = []
# while len(ret) < POPULATION_SIZE:
# x = random.randint(0, POPULATION_SIZE - 1)
# while x not in ret:
# x = random.randint(0, POPULATION_SIZE - 1)
# ret.append(x)
for i in range(len(vecs)):
x = random.random()
# if x <= 0.8:
ret.append(vecs[i])
if len(ret) == POPULATION_SIZE:
break
return ret
def load_inits(POPULATION_SIZE, VECTOR_SIZE=11):
inits = []
with open("./generations.json") as f:
res = json.load(f)
res = res["results"]
vecs = []
for x in res:
y = x["vectors"]
for z in y:
vecs.append(z)
vecs = sorted(vecs, key=lambda i: fitness(i["results"]))
for i in range(POPULATION_SIZE):
inits.append(vecs[i])
# for i in range(len(vecs)):
# x = random.random()
# if x <= 0.9:
# inits.append(np.array(vecs[i]["vector"]))
# if len(inits) == POPULATION_SIZE:
# return inits
return inits
def get_best_from_all_gens(POPULATION_SIZE):
files = [
"new_gen_1.json", "new_gen_2.json", "new_gen_3.json", "new_gen_4.json",
"new_new_gen_5.json", "fixed_6.json", "fixed_7.json", "fixed_8.json",
"fixed_9.json"
]
# files = ["fixed_9.json"]
inits = []
for file in files:
with open(file) as f:
res = json.load(f)
res = res["generations"]
for gen in res:
for vec in gen["vectors"]:
if vec["results"] == [0, 0]:
continue
inits.append({
"vector": vec["vector"]["child"],
"results": vec["results"],
"generation": gen["generation"],
"file": file
})
# with open("./generations.json") as f:
# res = json.load(f)
# res = res["results"]
# for x in res:
# y = x["vectors"]
# for z in y:
# inits.append(z)
inits = sorted(inits, key=lambda i: fitness(i["results"]))
final_inits = []
for i in range(len(inits)):
# if abs(inits[i]["results"][0] - inits[i]["results"][1])/1e11 <= 0.6:
final_inits.append(inits[i])
if len(final_inits) == POPULATION_SIZE:
break
return final_inits
def main():
POPULATION_SIZE = 16
CHILDREN_SIZE = 20
# CREATE MATING POOL ON ITS OWN
mating_pool = hand_picked()
for generation in range(1, 11):
print("Generation", generation)
gen_here = {"crossed_over": [], "mutated": [], "selected": []}
# SELECT PARENTS
parents = get_mating_pool(POPULATION_SIZE, CHILDREN_SIZE)
# DO CROSSOVER OF PARENTS
children = []
for i in range(len(parents)):
child1, child2 = BSC(
np.array(mating_pool[parents[i][0]]["vector"]),
np.array(mating_pool[parents[i][1]]["vector"]),
N=min(6, 3 + generation / 10))
children.append({
"child":
child1,
"parents":
[mating_pool[parents[i][0]], mating_pool[parents[i][1]]]
})
children.append({
"child":
child2,
"parents":
[mating_pool[parents[i][0]], mating_pool[parents[i][1]]]
})
gen_here["crossed_over"].append(child1.tolist())
gen_here["crossed_over"].append(child2.tolist())
# # DO MUTATIONS ON CHILDREN
for i in range(len(children)):
children[i]["child"] = mutate(children[i]["child"], generation)
gen_here["mutated"].append(children[i]["child"].tolist())
# GET ERRORS
errors = []
for child in children:
# res = [0, 0]
res = get_errors(TEAM_KEY, child["child"].tolist())
print(res[0] / 1e11, res[1] / 1e11, fitness(res))
child["child"] = {
"vector": child["child"].tolist(),
"results": res
}
errors.append({"vector": child, "results": res})
# ADD CHILDREN TO LIST
with open("new_new_gen_9.json") as f:
oldres = json.load(f)
oldres = oldres["generations"]
oldres.append({"generation": generation, "vectors": errors})
oldres = {"generations": oldres}
with open("new_new_gen_9.json", "w") as f:
json.dump(oldres, f)
# SELECT BEST CHILDREN
mating_pool = select_from_children(children, POPULATION_SIZE,
CHILDREN_SIZE)
for mat in mating_pool:
gen_here["selected"].append(mat["vector"])
with open("generations/generation_" + str(generation) + ".txt",
"w+") as f:
json.dump(gen_here, f)