added weighted_particles, clarified that particles returns an iterator

src/ParticleFilters.jl

@@ -25,8 +25,10 @@ export
     resample,
     n_particles,
     particles,
+    weighted_particles,
     weight_sum,
     weight,
+    particle,
     weights,
     obs_weight
 
@@ -85,10 +87,17 @@ function n_particles end
 """
     particles(b::AbstractParticleBelief)
 
-Return a vector of the particles.
+Return an iterator over the particles.
 """
 function particles end
 
+"""
+    weighted_particles(b::AbstractParticleBelief)
+
+Return an iterator over particle-weight pairs.
+"""
+function weighted_particles end
+
 """
     weight_sum(b::AbstractParticleBelief)
 
@@ -103,6 +112,14 @@ Return the weight for particle i.
 """
 function weight end
 
+
+"""
+    particle(b::AbstractParticleBelief, i)
+
+Return particle i.
+"""
+function particle end
+
 """
     obs_weight(pomdp, sp, o)
     obs_weight(pomdp, a, sp, o)

src/beliefs.jl

@@ -1,15 +1,19 @@
 
 n_particles(b::ParticleCollection) = length(b.particles)
 particles(p::ParticleCollection) = p.particles
+weighted_particles(p::ParticleCollection) = (p=>1.0/length(p.particles) for p in p.particles)
 weight_sum(::ParticleCollection) = 1.0
 weight(b::ParticleCollection, i::Int) = 1.0/length(b.particles)
+particle(b::ParticleCollection, i::Int) = b.particles[i]
 rand(rng::AbstractRNG, b::ParticleCollection) = b.particles[rand(rng, 1:length(b.particles))]
 mean(b::ParticleCollection) = sum(b.particles)/length(b.particles)
 
 n_particles(b::WeightedParticleBelief) = length(b.particles)
 particles(p::WeightedParticleBelief) = p.particles
+weighted_particles(b::WeightedParticleBelief) = (b.particles[i]=>b.weights[i] for i in 1:length(b.particles))
 weight_sum(b::WeightedParticleBelief) = b.weight_sum
 weight(b::WeightedParticleBelief, i::Int) = b.weights[i]
+particle(b::WeightedParticleBelief, i::Int) = b.particles[i]
 weights(b::WeightedParticleBelief) = b.weights
 
 function rand(rng::AbstractRNG, b::WeightedParticleBelief)

test/runtests.jl

@@ -31,3 +31,4 @@ b = initialize_belief(filter, initial_state_distribution(p))
 m = mode(b)
 m = mean(b)
 it = iterator(b)
+weighted_particles(b)