import numpy as np
from cpso_swarm import COMB_Swarm
from cpso_particle import COMB_Particle
s = COMB_Swarm(3, 2.1, 2.1, 2.1, 5,
0.8, 0.2,
(-6.0, 6.0), (-4.0, 0.25), (0.4, 0.9), (0, 10),
'data/data.csv', 'data/target.csv')
s.swarm.append(COMB_Particle(2.1, 2.1, 2.1, 5, (-6.0, 6.0), (-4.0, 0.25), (0.4, 0.9)))
s.swarm.append(COMB_Particle(2.1, 2.1, 2.1, 5, (-6.0, 6.0), (-4.0, 0.25), (0.4, 0.9)))
s.swarm.append(COMB_Particle(2.1, 2.1, 2.1, 5, (-6.0, 6.0), (-4.0, 0.25), (0.4, 0.9)))
s.swarm[0].x = np.array([1, 32, 8, 4, 13])
s.swarm[1].x = np.array([24, 3, 28, 3, 21])
s.swarm[2].x = np.array([12, 5, 24, 15, 31])
print('{:35} : {}'.format('Calculated Spread', s.calc_spread()))
print('{:35} : {}'.format('Correct Spread', 59.863405937339586))
args.x_bounds = tuple(args.x_bounds)
args.v_bounds = tuple(args.v_bounds)
args.w_bounds = tuple(args.w_bounds)
args.t_bounds = (0, args.t)
# Downstream file saving code expects directories to end with a '/'
if args.output_path[-1] != '/':
args.output_path.append('/')
if args.copyscript:
import shutil
shutil.copy(__file__, args.output_path + 'cpso_script.py')
# Initialize swarm and execute algorithm
s = COMB_Swarm(args.npart, args.c[0], args.c[1], args.c[2], args.ndim,
args.alpha, args.test_size, args.x_bounds, args.v_bounds,
args.w_bounds, args.t_bounds, args.data_path, args.target_path)
s.initialize_particles()
s.execute_search()
s.final_eval()
# Collect and process data from inside the swarm
data = []
columns = []
for k, v in s.var_by_time.items():
columns.append(k)
data.append(v)
var_by_time = pd.DataFrame(data=np.transpose(data), columns=columns)
var_by_time.to_csv(args.output_path + 'var_by_time.csv')
np.savetxt(args.output_path + 'abinary.csv', s.abinary, delimiter=',')
np.savetxt(args.output_path + 'X_train.csv', s.X_train, delimiter=',')
np.savetxt(args.output_path + 'y_train.csv', s.y_train, delimiter=',')
# Creating the fitness function terms dict
terms = {}
for k, v in zip(args.terms, args.weights):
terms[k] = v
# Downstream file saving code expects directories to end with a '/'
if args.output_path[-1] != '/':
args.output_path += '/'
if args.copyscript:
import shutil
shutil.copy(__file__, args.output_path)
# Initialize swarm and execute algorithm
s = COMB_Swarm(args.npart, args.c[0], args.c[1], args.c[2], args.ndim, terms,
args.stagn_limit, args.x_bounds, args.v_bounds, args.w_bounds,
args.t_bounds, args.data_path, args.target_path,
args.init_particles)
if not args.init_particles:
s.initialize_particles()
s.execute_search()
# Collect and process data from inside the swarm
data = []
columns = []
for k, v in s.var_by_time.items():
if k == 'g_score':
columns.append('g_accuracy')
data.append([i[0] for i in v])
columns.append('g_sensitivity')
data.append([i[1] for i in v])
columns.append('g_specificity')
data.append([i[2] for i in v])