def init_trace(n_particles):
"""
Constructs the tracing log which tracks the movement of particles in 2 dimensions only..
--We build these dimensions as ("objective(particle)", "-20")
"""
for i in range(n_particles):
vals_ = particles[i].get_vals()
movement_trace.append({"id": i, "x": objective(vals_), "y": -100, "new_x": objective(vals_), "new_y": -100})
def init_particles(n_particles, min_, max_, dimensions):
"""
Declaring the particles.
"""
for _ in range(n_particles):
new_particle = Particle()
val_ = random.sample(range(min_, max_), dimensions)
p_best = objective(val_)
new_particle.set_vals(val_)
new_particle.set_pbest(p_best)
particles.append(new_particle)
def set_trace(i, old, new):
"""
Updates the location trace for the particle
"""
movement_trace.append({"id": i, "x": objective(old), "y": -100, "new_x": objective(new), "new_y": -100})
def optimize(self):
"""
trains/fits the particles to catch the target
under the given number of pre-fixed iterations
"""
victor = 0
found = False
while not self.done:
if self.epoch < self.max_epochs:
for i in range(self.max_particles):
if self.objective(particles[i].get_vals()) == self.target:
victor = i
self.done = True
found = True
print "FOUND!", self.objective(particles[i].get_vals()), self.target
break
new_best = self.get_nearest()
a_particle = particles[self.g_best]
if math.fabs(self.target - self.objective(particles[new_best].get_vals())) < math.fabs(
self.target - self.objective(a_particle.get_vals())
):
self.g_best = new_best
self.set_velocity(self.g_best)
self.update_particles(self.g_best)
self.epoch += 1
else:
self.done = True
if found:
print "particle %d is the victor: %s" % (victor, str(particles[victor].get_vals()))
else:
print "exact match not found. %d is the nearest: %s" % (victor, str(particles[victor].get_vals()))
print "epochs: %d out of %d completed" % (self.epoch, self.max_epochs)
# --add the achieved
movement_trace.append(
{
"id": -1,
"x": objective(particles[victor].get_vals()),
"y": -100,
"new_x": objective(particles[victor].get_vals()),
"new_y": -100,
}
)
# --add the target
movement_trace.append({"id": -2, "x": self.target, "y": -100, "new_x": self.target, "new_y": -100})
results = {
"victor": particles[victor].get_vals(),
"index": victor,
"value": objective(particles[victor].get_vals()),
"target_value": self.target,
"max_epochs": self.epoch,
"v_max": self.v_max,
"n_particles": self.max_particles,
}
# --visualize if demanded..
if self.visualize:
write_trace(movement_trace, results)
print "visual trace created..please check viz/pso_index.html"
return results