def zad4():
import matplotlib.pyplot as plt
import numpy as np
go.reset_params()
ut.reset_params()
results = {}
factory.set_type('floating_point')
ut.n_features = 1
eGA.n_iter = 10000
f = 'f6'
iters = {}
for size in [30, 50, 100, 200]:
go.population_size = size
factory.set_function_to_minimize(f)
for p in [0.1, 0.3, 0.6, 0.9]:
key = f+'-p_size'+str(size) + '-p_mut-'+str(p)
go.p_mutation = p
results[key] = []
iters[key] = []
for i in range(n_tries):
res, iter = eGA.minimize(n_iter_trace=True)
results[key].append(abs(res.fitness))
iters[key].append(iter)
#plotting iters
res = []
iter_ = []
labels = [0.1, 0.3, 0.6, 0.9]
for p in labels:
size = 30
res.append(results[f+'-p_size'+str(size) + '-p_mut-'+str(p)])
iter_.append(iters[f+'-p_size'+str(size) + '-p_mut-'+str(p)])
plt.boxplot(res, labels=labels)
plt.show()
def zad1():
go.reset_params()
ut.reset_params()
results = {'f1': [], 'f2': [], 'f6': [], 'f7': []}
iters = {}
factory.set_type('floating_point')
for curr in results:
factory.set_function_to_minimize(curr)
ut.n_features = 5 if curr == 'f2' else 2
iters[curr] = []
for i in range(n_tries):
res, iter = eGA.minimize(n_iter_trace=True)
results[curr].append(abs(res.fitness))
iters[curr].append(iter)
def zad5():
go.reset_params()
ut.reset_params()
results = {}
iters = {}
factory.set_type('floating_point')
for dim in [3,5,7]:
go.tournament_size = dim
for f in ['f6']:
key = f+'-k'+str(dim)
factory.set_function_to_minimize(f)
results[key] = []
iters[key] = []
for i in range(n_tries):
res, iter = eGA.minimize(n_iter_trace=True)
results[key].append(abs(res.fitness))
iters[key].append(iter)
def zad2():
go.reset_params()
ut.reset_params()
results = {}
factory.set_type('floating_point')
iters = {}
for dim in [1,3,6,10]:
for f in ['f6', 'f7']:
ut.n_features = dim
key = f+'-d'+str(dim)
factory.set_function_to_minimize(f)
results[key] = []
iters[key] = []
for i in range(n_tries):
res, iter = eGA.minimize(n_iter_trace=True)
results[key].append(abs(res.fitness))
iters[key].append(iter)
def zad3():
results = {}
iters = {}
go.reset_params()
ut.reset_params()
ut.binary_n_bits = 32
for method in ['floating_point', 'binary']:
factory.set_type(method)
for dim in [3,6]:
ut.n_features = dim
for f in ['f6', 'f7']:
ut.n_features = dim
key = f+'-'+method+'-d'+str(dim)
factory.set_function_to_minimize(f)
results[key] = []
iters[key] = []
for i in range(n_tries):
res, iter = eGA.minimize(n_iter_trace=True)
results[key].append(abs(res.fitness))
iters[key].append(iter)
