added ImplicitDistribution

docs/src/distributions.md

@@ -8,12 +8,20 @@ This package also supplies [`showdistribution`](@ref) for pretty printing distri
 
 `SparseCat` is a sparse categorical distribution which is specified by simply providing a list of possible values (states or observations) and the probabilities corresponding to those particular objects.
 
-Example: `SparseCat([1,2,3], [0.1,0.2,0.7])` is a categorical distribution that assignes probability 0.1 to `1`, 0.2 to `2`, 0.7 to `3`, and 0 to all other values.
+Example: `SparseCat([1,2,3], [0.1,0.2,0.7])` is a categorical distribution that assigns probability 0.1 to `1`, 0.2 to `2`, 0.7 to `3`, and 0 to all other values.
 
 ```@docs
 SparseCat
 ```
 
+## Implicit
+
+In situations where a distribution object is required, but the pdf is difficult to specify and only samples are required, `ImplicitDistribution` provides a convenient way to package a sampling function.
+
+```@docs
+ImplicitDistribution
+```
+
 ## Bool Distribution
 
 ```@docs

src/POMDPModelTools.jl

@@ -79,6 +79,10 @@ export
     UnsafeUniform
 include("distributions/uniform.jl")
 
+export
+    ImplicitDistribution
+include("distributions/implicit.jl")
+
 # convenient implementations
 include("convenient_implementations.jl")
 

src/distributions/implicit.jl

@@ -0,0 +1,43 @@
+"""
+    ImplicitDistribution(sample_function, args...)
+
+Define a distribution that can only be sampled from using `rand`, but has no explicit `pdf`.
+
+Each time `rand(rng, d::ImplicitDistribution)` is called,
+```julia
+sample_function(args..., rng)
+```
+will be called to generate a new sample.
+
+`ImplicitDistribution` is designed to be used with anonymous functions or the `do` syntax as follows:
+
+# Examples
+
+```julia
+ImplicitDistribution(rng->rand(rng)^2)
+```
+
+```julia
+struct MyMDP <: MDP{Float64, Int} end
+
+function POMDPs.transition(m::MyMDP, s, a)
+    ImplicitDistribution(s, a) do s, a, rng
+        return s + a + 0.001*randn(rng)
+    end
+end
+
+td = transition(MyMDP(), 1.0, 1)
+rand(td) # will return a number near 2
+```
+"""
+struct ImplicitDistribution{F<:Function, A}
+    f::F
+    args::A
+end
+
+ImplicitDistribution(f::Function, args...) = ImplicitDistribution(f, args)
+
+function Base.rand(rng::AbstractRNG, s::Random.SamplerTrivial{<:ImplicitDistribution})
+    d = s[]
+    d.f(d.args..., rng)
+end

test/runtests.jl

@@ -37,6 +37,9 @@ using SparseArrays
     @testset "uniform" begin
         include("test_uniform.jl")
     end
+    @testset "implicit" begin
+        include("test_implicit.jl")
+    end
     @testset "terminalstate" begin
         include("test_terminal_state.jl")
     end

test/test_implicit.jl

@@ -0,0 +1,12 @@
+struct IMDP <: MDP{Float64, Int} end
+
+function POMDPs.transition(m::IMDP, s, a)
+    ImplicitDistribution(s, a) do s, a, rng
+        return s + a + rand(rng)
+    end
+end
+
+m = IMDP()
+
+td = transition(m, 1.0, 1)
+@test 2 <= rand(td) <= 3