list_exec_time = []
list_functions = [(testFunctions.ackley_function, (0.0, 0.0)),
(testFunctions.easom_function, (math.pi, math.pi)),
(testFunctions.sphere_function, (0.0 , 0.0)),
(testFunctions.bohachevsky_function, (0.0 , 0.0)),
(testFunctions.sum_squares_function, (0.0 , 0.0))]
for l in range(len(list_functions)):
# gets the function
function = list_functions[l][0]
#print("Function: " + ", " + str(function))
#print("Run, Mean Error, Execution Time")
avg_error = 0
avg_delta = 0
for i in range(num_runs):
start = datetime.datetime.now()
alh = SwarmPackagePy.fa(num_agents, function, -10, 10, 2, num_iterations)
end = datetime.datetime.now()
delta = end - start
last_list_pos = alh.get_agents()[-1]
# gets the global optima of the function
global_optima = list_functions[l][1]
error = 0
for j in range(num_agents):
last_pos = last_list_pos[j]
ind_error = ((last_pos[0] - global_optima[0]) ** 2 + (last_pos[1] - global_optima[1]) ** 2) ** 0.5
error += ind_error
error /= num_agents
list_error.append(error)
list_exec_time.append(delta.microseconds)
#print("average error for run " + str(i + 1) + ": " + str(error))
#print("exec time for run " + str(i + 1) + ": " + str(delta,microseconds))
import SwarmPackagePy as sw
from SwarmPackagePy import testFunctions as tf
from SwarmPackagePy import animation, animation3D
import numpy as np
sw._version_
swarm_strength = np.random.random_integers(25, 55)
print("Swarm strength =", swarm_strength)
firefly = sw.fa(n=swarm_strength,
function=tf.sum_squares_function,
lb=-10,
ub=10,
dimension=2,
psi=2,
iteration=50)
animation(firefly.get_agents(), tf.sum_squares_function, -10, 10)
animation3D(firefly.get_agents(), tf.sum_squares_function, -10, 10)