removed obs_weight (#11)

* removed obs_weight

* changed obs_weight in README

README.md

@@ -22,7 +22,7 @@ ParticleFilters.jl can be be used with or without the [POMDPs.jl](https://github
 
 ## Usage without POMDPs.jl
 
-ParticleFilters.jl uses a simple interface consisting of the functions [`generate_s(model, state, control, rng)`](http://juliapomdp.github.io/POMDPs.jl/latest/api/#POMDPs.generate_s) and [`observation(model, control, state)`](http://juliapomdp.github.io/POMDPs.jl/latest/api/#POMDPs.observation) borrowed from [POMDPs.jl](https://github.com/JuliaPOMDP/POMDPs.jl). `generate_s()` should return the next state given the current state and control input; `observation()` should return the observation distribution for a state. If it is difficult to write the observation distribution, the shortcut function `ParticleFilters.obs_weight(model, control, state, observation)` that returns the weight (pdf) for the observation given the state and control can be implemented instead.
+ParticleFilters.jl uses a simple interface consisting of the functions [`generate_s(model, state, control, rng)`](http://juliapomdp.github.io/POMDPs.jl/latest/api/#POMDPs.generate_s) and [`observation(model, control, state)`](http://juliapomdp.github.io/POMDPs.jl/latest/api/#POMDPs.observation) borrowed from [POMDPs.jl](https://github.com/JuliaPOMDP/POMDPs.jl). `generate_s()` should return the next state given the current state and control input; `observation()` should return the observation distribution for a state. If it is difficult to write the observation distribution, the shortcut function `POMDPToolbox.obs_weight(model, control, state, observation)` that returns the weight (pdf) for the observation given the state and control can be implemented instead.
 
 Once these two functions have been implemented to define the system dynamics and observation model, the function `update(filter, b, a, o)` can then be used to carry out a single update of the particle filter. It will return a `ParticleCollection` representing the belief at the next time step.
 

REQUIRE

@@ -1,4 +1,4 @@
 julia 0.6
 StatsBase
 POMDPs 0.6
-POMDPToolbox 0.2.6 0.2.7
+POMDPToolbox 0.2.7

src/ParticleFilters.jl

@@ -12,6 +12,7 @@ import POMDPs: sampletype
 import Base: rand, mean
 
 using POMDPToolbox
+import POMDPToolbox: obs_weight
 using StatsBase
 
 export
@@ -123,15 +124,6 @@ Return particle i.
 """
 function particle end
 
-"""
-    obs_weight(pomdp, sp, o)
-    obs_weight(pomdp, a, sp, o)
-    obs_weight(pomdp, s, a, sp, o)
-
-Return a weight proportional to the likelihood of receiving observation o from state sp (and a and s if they are present).
-"""
-function obs_weight end # implemented in obs_weight
-
 ### Basic Particle Filter ###
 # implements the POMDPs.jl Updater interface
 # see updater.jl for implementations
@@ -222,7 +214,6 @@ include("unweighted.jl")
 include("beliefs.jl")
 include("updater.jl")
 include("resamplers.jl")
-include("obs_weight.jl")
 include("policies.jl")
 
 end # module