support for ArrayOfUnivariateDistribution

src/that_should_be_in_Distributions.jl

@@ -17,52 +17,51 @@ function fit_mle(g::D, args...) where {D<:Distribution}
     fit_mle(typeof(g), args...)
 end
 
-fit_mle(d::T, x::AbstractArray{<:Integer}) where {T<:Binomial} =
-    fit_mle(T, suffstats(T, ntrials(d), x))
-fit_mle(d::T, x::AbstractArray{<:Integer}) where {T<:Categorical} =
-    fit_mle(T, ncategories(d), x)
+fit_mle(d::T, x::AbstractArray{<:Integer}) where {T<:Binomial} = fit_mle(T, suffstats(T, ntrials(d), x))
+fit_mle(d::T, x::AbstractArray{<:Integer}) where {T<:Categorical} = fit_mle(T, ncategories(d), x)
 
 ## * `fit_mle` for `product_distribution`
 
+#TODO: add deprecation notice!
+#TODO! but currently still have `product_distribution([d1, d2]) ≠ product_distribution(d1, d2)` (first is still `Product` while second is `Distributions.ProductDistribution`)
+#TODO! open issue in `Distributions.jl`
+
 """
     fit_mle(g::Product, x::AbstractMatrix)
     fit_mle(g::Product, x::AbstractMatrix, γ::AbstractVector)
 
 The `fit_mle` for multivariate Product distributions `g` is the `product_distribution` of `fit_mle` of each components of `g`.
-Product is meant to be depreacated in next version of `Distribution.jl`. Use the analog `VectorOfUnivariateDistribution` type instead.
+Product is meant to be depreacated in next versions of `Distribution.jl`. Use the analog `VectorOfUnivariateDistribution` type instead.
 """
 function fit_mle(g::Product, x::AbstractMatrix, args...)
     d = size(x, 1)
-    length(g) == d ||
-        throw(DimensionMismatch("The dimensions of g and x are inconsistent."))
-    return product_distribution([
-        fit_mle(g.v[s], y, args...) for (s, y) in enumerate(eachrow(x))
-    ])
+    length(g) == d || throw(DimensionMismatch("The dimensions of g and x are inconsistent."))
+    return product_distribution([fit_mle(g.v[s], y, args...) for (s, y) in enumerate(eachrow(x))])
 end
 
 params(g::Product) = params.(g.v)
 
-#! `ArrayOfUnivariateDistribution` is not released yet
-# params(d::ArrayOfUnivariateDistribution) = params.(d.dists)
+params(d::ArrayOfUnivariateDistribution) = params.(d.dists) # 
 
-# #### Fitting
-# promote_sample(::Type{dT}, x::AbstractArray{T}) where {T<:Real, dT<:Real} = T <: dT ? x : convert.(dT, x)
+#### Fitting
+promote_sample(::Type{dT}, x::AbstractArray{T}) where {T<:Real,dT<:Real} = T <: dT ? x : convert.(dT, x)
 
-# """
-#     fit_mle(dists::ArrayOfUnivariateDistribution, x::AbstractArray)
-#     fit_mle(dists::ArrayOfUnivariateDistribution, x::AbstractArray, γ::AbstractVector)
+"""
+    fit_mle(dists::ArrayOfUnivariateDistribution, x::AbstractArray)
+    fit_mle(dists::ArrayOfUnivariateDistribution, x::AbstractArray, γ::AbstractVector)
 
-# The `fit_mle` for a `ArrayOfUnivariateDistribution` distributions `dists` is the `product_distribution` of `fit_mle` of each components of `dists`.
-# """
-# function fit_mle(dists::VectorOfUnivariateDistribution, x::AbstractMatrix{<:Real}, args...)
-#     length(dists) == size(x, 1) || throw(DimensionMismatch("The dimensions of dists and x are inconsistent."))
-#     return product_distribution([fit_mle(d, promote_sample(eltype(d), x[s, :]), args...) for (s, d) in enumerate(dists.dists)])
-# end
+The `fit_mle` for a `ArrayOfUnivariateDistribution` distributions `dists` is the `product_distribution` of `fit_mle` of each components of `dists`.
+`VectorOfUnivariateDistribution` should act like old `Product` while `ArrayOfUnivariateDistribution` are not really tested yet.
+"""
+function fit_mle(dists::VectorOfUnivariateDistribution, x::AbstractMatrix{<:Real}, args...)
+    length(dists) == size(x, 1) || throw(DimensionMismatch("The dimensions of dists and x are inconsistent."))
+    return product_distribution([fit_mle(d, promote_sample(eltype(d), x[s, :]), args...) for (s, d) in enumerate(dists.dists)]...)
+end
 
-# function fit_mle(dists::ArrayOfUnivariateDistribution, x::AbstractArray, args...)
-#     size(dists) == size(first(x)) || throw(DimensionMismatch("The dimensions of dists and x are inconsistent."))
-#     return product_distribution([fit_mle(d, promote_sample(eltype(d), [x[i][s] for i in eachindex(x)]), args...) for (s, d) in enumerate(dists.dists)])
-# end
+function fit_mle(dists::ArrayOfUnivariateDistribution, x::AbstractArray, args...)
+    size(dists) == size(first(x)) || throw(DimensionMismatch("The dimensions of dists and x are inconsistent."))
+    return product_distribution([fit_mle(d, promote_sample(eltype(d), [x[i][s] for i in eachindex(x)]), args...) for (s, d) in enumerate(dists.dists)]...)
+end
 
 
 ## * New `fit_mle` * ##