def crs3(A_shared, function_number, vec_len):
A = A_shared[:]
rn.seed(1)
iterations = 100000
final_result = list()
for iteration in range(iterations):
i_W = np.argmax(np.array(A).T[-1])
W = A[i_W]
A_exclude_W = A.copy()
A_exclude_W.remove(W)
R_chosen = rn.sample(A_exclude_W, vec_len)
i_S = np.argmax(np.array(A_exclude_W).T[-1])
S = A_exclude_W[i_S]
centroid = get_G(R_chosen)
P = get_P(centroid, W)
Q = get_Q(centroid, W)
R = get_R(centroid, W)
if f.is_point_in_domain(P):
P[-1] = eval('f.function_' + str(function_number) + '(P[:-1])')
if P[-1] < S[-1]:
if not f.is_point_in_domain(R):
W = P
A[i_W] = P
final_result.append(P[-1])
else:
R[-1] = eval('f.function_' + str(function_number) +
'(R[:-1])')
if R[-1] < S[-1]:
W = R
A[i_W] = R
final_result.append(R[-1])
else:
W = P
A[i_W] = P
final_result.append(P[-1])
else:
if not f.is_point_in_domain(Q):
continue
else:
Q[-1] = eval('f.function_' + str(function_number) + '(Q[:-1])')
if Q[-1] < S[-1]:
W = Q
A[i_W] = Q
final_result.append(Q[-1])
else:
continue
return final_result[-1]
def crs2(A_shared, function_number, vec_len):
A = A_shared[:]
rn.seed(1)
iterations = 100000
final_result = list()
for iteration in range(iterations):
i_M = np.argmax(np.array(A).T[-1])
i_L = np.argmin(np.array(A).T[-1])
M = A[i_M]
L = A[i_L]
A_exclude_L = A.copy()
A_exclude_L.remove(L)
R_chosen = rn.sample(A_exclude_L, vec_len)
R_n_plus_1 = R_chosen.pop()
centroid = get_centroid(R_chosen)
P = get_P(centroid, R_n_plus_1)
if f.is_point_in_domain(P):
P[-1] = eval('f.function_' + str(function_number) + '(P[:-1])')
if P[-1] < M[-1]:
M = P
A[i_M] = P
final_result.append(P[-1])
return P[-1]
def crs2(A, return_list, function_number, vec_len):
rn.seed(1)
iterations = 20000
final_result = list()
CLOSE_ENOUGH = 10e-4
WANTED_RESULT = 0
last_P_value = 10e4
for iteration in range(iterations):
# while abs(last_P_value - WANTED_RESULT) > CLOSE_ENOUGH:
i_M = np.argmax(np.array(A).T[-1])
i_L = np.argmin(np.array(A).T[-1])
M = A[i_M]
L = A[i_L]
A_exclude_L = A.copy()
A_exclude_L.remove(L)
R_chosen = rn.sample(A_exclude_L, vec_len)
R_n_plus_1 = R_chosen.pop()
centroid = get_centroid(R_chosen)
P = get_P(centroid, R_n_plus_1)
if f.is_point_in_domain(P):
P[-1] = eval('f.function_' + str(function_number) + '(P[:-1])')
if P[-1] < M[-1]:
M = P
A[i_M] = P
final_result.append(P[-1])
last_P_value = P[-1]
return_list.append(P[-1])
def crs3(A, return_list, function_number, vec_len):
rn.seed(1)
iterations = 20000
final_result = list()
CLOSE_ENOUGH = 10e-4
WANTED_RESULT = 0
last_P_value = 10e4
# while abs(last_P_value - WANTED_RESULT) > CLOSE_ENOUGH:
for iteration in range(iterations):
i_W = np.argmax(np.array(A).T[-1])
W = A[i_W]
A_exclude_W = A.copy()
A_exclude_W.remove(W)
R_chosen = rn.sample(A_exclude_W, vec_len)
i_S = np.argmax(np.array(A_exclude_W).T[-1])
S = A_exclude_W[i_S]
centroid = get_G(R_chosen)
P = get_P(centroid, W)
Q = get_Q(centroid, W)
R = get_R(centroid, W)
if f.is_point_in_domain(P):
P[-1] = eval('f.function_' + str(function_number) + '(P[:-1])')
if P[-1] < S[-1]:
if not f.is_point_in_domain(R):
W = P
A[i_W] = P
final_result.append(P[-1])
last_P_value = P[-1]
else:
R[-1] = eval('f.function_' + str(function_number) +
'(R[:-1])')
if R[-1] < S[-1]:
W = R
A[i_W] = R
final_result.append(R[-1])
last_P_value = P[-1]
else:
W = P
A[i_W] = P
final_result.append(P[-1])
last_P_value = P[-1]
else:
if not f.is_point_in_domain(Q):
continue
else:
Q[-1] = eval('f.function_' + str(function_number) + '(Q[:-1])')
if Q[-1] < S[-1]:
W = Q
A[i_W] = Q
final_result.append(Q[-1])
last_P_value = P[-1]
else:
continue
#
# if iteration % 100 == 0:
# print(str(iteration) + ' Kolejna wartość P' + str(P))
#
# if iteration//100 < 10:
# f_name = 'results/CRS2_00{}'.format(iteration//100)
# elif iteration//100 < 100:
# f_name = 'results/CRS2_0{}'.format(iteration//100)
# else:
# f_name = 'results/CRS2_{}'.format(iteration//100)
#
# hp.plot_3d_scatter(whole_set=A,
# centroid=centroid,
# r_last=W,
# optimum=P,
# f_name=f_name,
# func_number=FUNCTION_NUMBER)
#
# hp.plot_convergence(final_result)
return_list.append(final_result[-1])
def CRS3(FUNCTION_NUMBER, vec_len):
final_result = list()
rn.seed(1)
N = 800
iterations = 20000
start_rand = time.time()
A = eval('f.generate_points_func_' + str(FUNCTION_NUMBER) + '(N, vec_len)')
start_iter = time.time()
for iteration in range(iterations):
i_W = np.argmax(np.array(A).T[-1])
W = A[i_W]
A_exclude_W = A.copy()
A_exclude_W.remove(W)
R_chosen = rn.sample(A_exclude_W, vec_len)
i_S = np.argmax(np.array(A_exclude_W).T[-1])
S = A_exclude_W[i_S]
centroid = get_G(R_chosen)
P = get_P(centroid, W)
Q = get_Q(centroid, W)
R = get_R(centroid, W)
if f.is_point_in_domain(P):
P[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(P[:-1])')
if P[-1] < S[-1]:
if not f.is_point_in_domain(R):
W = P
A[i_W] = P
final_result.append(P[-1])
else:
R[-1] = eval('f.function_' + str(FUNCTION_NUMBER) +
'(R[:-1])')
if R[-1] < S[-1]:
W = R
A[i_W] = R
final_result.append(R[-1])
else:
W = P
A[i_W] = P
final_result.append(P[-1])
else:
if not f.is_point_in_domain(Q):
continue
else:
Q[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(Q[:-1])')
if Q[-1] < S[-1]:
W = Q
A[i_W] = Q
final_result.append(Q[-1])
else:
continue
if iteration % 100 == 0:
print(str(iteration) + ' Kolejna wartość P' + str(P))
if iteration // 100 < 10:
f_name = 'results/CRS3_00{}'.format(iteration // 100)
elif iteration // 100 < 100:
f_name = 'results/CRS3_0{}'.format(iteration // 100)
else:
f_name = 'results/CRS3_{}'.format(iteration // 100)
hp.plot_3d_scatter(whole_set=A,
centroid=centroid,
r_last=W,
optimum=P,
f_name=f_name,
func_number=FUNCTION_NUMBER)
hp.plot_convergence(final_result)
end = time.time()
iter_time = end - start_iter
rand_time = start_iter - start_rand
full_time = end - start_rand
return (iter_time, rand_time, full_time, final_result[-1])