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import pickle
from deap import tools
from stats import record
logbook = tools.Logbook()
logbook.record(gen=0, evals=30, **record)
print(logbook)
gen, avg = logbook.select("gen", "avg")
with open("logbook.pkl", "w") as lb_file:
pickle.dump(logbook, lb_file)
# Cleaning the pickle file ...
import os
os.remove("logbook.pkl")
logbook.header = "gen", "avg", "spam"
print(logbook)
print(logbook.stream)
logbook.record(gen=1, evals=15, **record)
print(logbook.stream)
from multistats import record
logbook = tools.Logbook()
logbook.record(gen=0, evals=30, **record)
logbook.header = "gen", "evals", "fitness", "size"
logbook.chapters["fitness"].header = "min", "avg", "max"
logbook.chapters["size"].header = "min", "avg", "max"
print(logbook)
gen = logbook.select("gen")
fit_mins = logbook.chapters["fitness"].select("min")
size_avgs = logbook.chapters["size"].select("avg")
import matplotlib.pyplot as plt
fig, ax1 = plt.subplots()
line1 = ax1.plot(gen, fit_mins, "b-", label="Minimum Fitness")
ax1.set_xlabel("Generation")
ax1.set_ylabel("Fitness", color="b")
for tl in ax1.get_yticklabels():
tl.set_color("b")
ax2 = ax1.twinx()
line2 = ax2.plot(gen, size_avgs, "r-", label="Average Size")
ax2.set_ylabel("Size", color="r")
for tl in ax2.get_yticklabels():
tl.set_color("r")
lns = line1 + line2
labs = [l.get_label() for l in lns]
ax1.legend(lns, labs, loc="center right")
plt.show()
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