Dynamic Coverage of a bimodal distribution

Here is an example of Dyamic SMC used to explore a bimodal distribution.

# After necessary imports
# Define probability distribution
xmin, xmax = (-100.0, 100.0)
ymin, ymax = (-100.0, 100.0)
prob_dist = ProbDist(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, Nx=100, Ny=100)
# first set everything to zero
prob_dist.set_zero()

# adding first gaussian distribution 
prob_dist.add_gaussian(mu_1, cov_1, 1.0)

# adding second gaussian distribution
prob_dist.add_gaussian(mu_2, cov_2, 1.0)

# Define StaticSMC coverage object
dynamic_smc = DynamicSMC(prob_dist)

# Add agents (with random initial locations) to coverage object
for _ in range(10):
    random_state = (xmin + (xmax - xmin) * random.random(),
                    ymin + (ymax - ymin) * random.random())
    dynamic_smc.add_agent(Agent(random_state[0], random_state[1]))

# Run the algorithm (1000 time-steps of size 1)
dynamic_smc.time_steps(1000, 1) 

Below is shown an animation of the trajectories exploring the bimodal distribution using Dynamic SMC. The green coloring represents the bimodal distribution to be covered. To see the full code for this example, look here.