added a uniform distribution over a collection of objects

docs/src/distributions.md

@@ -23,3 +23,9 @@ BoolDistribution
 ```@docs
 Deterministic
 ```
+
+## Uniform
+
+```@docs
+Uniform
+```

src/POMDPModelTools.jl

@@ -71,6 +71,10 @@ export
     Deterministic
 include("distributions/deterministic.jl")
 
+export
+    Uniform
+include("distributions/uniform.jl")
+
 # convenient implementations
 include("convenient_implementations.jl")
 

src/distributions/uniform.jl

@@ -0,0 +1,35 @@
+"""
+    Uniform(collection)
+
+Create a categorical distribution over a collection of objects.
+"""
+mutable struct Uniform{C, T}
+    collection::C
+    _set::Union{Set{T}, Nothing} # keep track of what's in the collection to make pdf more efficient
+end
+
+Uniform(c) = Uniform{typeof(c), eltype(c)}(c, nothing)
+Uniform(c::Set) = Uniform{typeof(c), eltype(c)}(c, c)
+
+rand(rng::AbstractRNG, d::Uniform) = rand(rng, d.collection)
+rand(rng::AbstractRNG, d::Uniform{<:NamedTuple}) = d.collection[rand(rng, 1:length(d.collection))]
+
+support(d::Uniform) = d.collection
+sampletype(::Type{Uniform{C, T}}) where {C,T} = T
+
+function pdf(d::Uniform, s)
+    d._set = something(d._set, Set(d.collection))
+    if s in d._set
+        return 1/length(d.collection)
+    else
+        return 0.0
+    end
+end
+
+mode(d::Uniform) = mode(d.collection)
+mean(d::Uniform) = mean(d.collection)
+
+function weighted_iterator(d::Uniform)
+    p = 1/length(d.collection)
+    return (x=>p for x in d.collection)
+end

test/runtests.jl

@@ -5,6 +5,7 @@ using Random
 using Test
 using Pkg
 using POMDPSimulators
+import Distributions.Categorical
 
 @testset "ordered" begin
     include("test_ordered_spaces.jl")
@@ -29,6 +30,9 @@ end
 @testset "deterministic" begin
     include("test_deterministic.jl")
 end
+@testset "uniform" begin
+    include("test_uniform.jl")
+end
 @testset "terminalstate" begin
     include("test_terminal_state.jl")
 end

test/test_uniform.jl

@@ -0,0 +1,22 @@
+d = Uniform([1])
+
+@test rand(d) == 1
+@test rand(MersenneTwister(4), d) == 1
+@test collect(support(d)) == [1]
+@test sampletype(d) == typeof(1)
+@test sampletype(typeof(d)) == typeof(1)
+@test pdf(d, 0) == 0.0
+@test pdf(d, 1) == 1.0
+@test mode(d) == 1
+@test mean(d) == 1
+@test typeof(mean(d)) == typeof(mean([1]))
+
+d2 = Uniform((:symbol,))
+@test rand(d2) == :symbol
+@test rand(MersenneTwister(4), d2) == :symbol
+@test collect(support(d2)) == [:symbol]
+@test sampletype(d2) == typeof(:symbol)
+@test sampletype(typeof(d2)) == typeof(:symbol)
+@test pdf(d2, :another) == 0.0
+@test pdf(d2, :symbol) == 1.0
+@test mode(d2) == :symbol

test/test_weighted_iteration.jl

@@ -1,5 +1,4 @@
 let
-    using Distributions
     dist = Categorical([0.4, 0.5, 0.1])
     c = collect(weighted_iterator(dist))
     @test c == [1=>0.4, 2=>0.5, 3=>0.1]