def __init__(self, ax, global_map, particle_list, target_particles=300, draw_max=2000, resample_period=10):
self.ax = ax
self.draw_max = draw_max
self.global_map = global_map
self.particle_list = particle_list
mcl.draw_map_state(global_map, particle_list, ax=self.ax, draw_max=self.draw_max)
self.i = 1
self.target_particles = target_particles
self.resample_period = resample_period
def update(self, message):
if self.i % self.resample_period == 0:# Resample and plot state
self.particle_list = mcl.mcl_update(self.particle_list, message, resample=True,
target_particles=self.target_particles) # Update
plt.cla()
mcl.draw_map_state(self.global_map, self.particle_list, self.ax, draw_max=self.draw_max)
#print(pd.Series([p.weight for p in self.particle_list]).describe())
else: # Just update particle weights / locations - do not resample
self.particle_list = mcl.mcl_update(self.particle_list, message,
target_particles=self.target_particles) # Update
self.i += 1
def __init__(self,
ax,
global_map,
particle_list,
target_particles=300,
draw_max=2000,
resample_period=10):
self.ax = ax
self.draw_max = draw_max
self.global_map = global_map
self.particle_list = particle_list
mcl.draw_map_state(global_map,
particle_list,
ax=self.ax,
draw_max=self.draw_max)
self.i = 1
self.target_particles = target_particles
self.resample_period = resample_period
def update(self, message):
if self.i % self.resample_period == 0: # Resample and plot state
self.particle_list = mcl.mcl_update(
self.particle_list,
message,
resample=True,
target_particles=self.target_particles) # Update
plt.cla()
mcl.draw_map_state(self.global_map,
self.particle_list,
self.ax,
draw_max=self.draw_max)
#print(pd.Series([p.weight for p in self.particle_list]).describe())
else: # Just update particle weights / locations - do not resample
self.particle_list = mcl.mcl_update(
self.particle_list,
message,
target_particles=self.target_particles) # Update
self.i += 1
