removed commented lines

Author: dwijenchawra

src/DiscreteBayesNet/discrete_bayes_net.jl

@@ -244,7 +244,6 @@ function statistics(dag::DAG, data::DataFrame)
 
     parents = [inneighbors(dag, i) for i in 1:n]
     ncategories = [Int(infer_number_of_instantiations(data[!,i])) for i in 1 : n]
-#     datamat = convert(Matrix{Int}, data)'
     datamat = Matrix{Int}(data)'
 
     statistics(parents, ncategories, datamat)
@@ -256,7 +255,6 @@ function statistics(bn::DiscreteBayesNet, target::NodeName, data::DataFrame)
     targetind = bn.name_to_index[target]
     parents = inneighbors(bn.dag, targetind)
     ncategories = [Int(infer_number_of_instantiations(data[!,i])) for i in 1 : n]
-#     datamat = convert(Matrix{Int}, data)'
     datamat = Matrix{Int}(data)'
     statistics(targetind, parents, ncategories, datamat)
 end

src/DiscreteBayesNet/structure_scoring.jl

@@ -111,7 +111,6 @@ function bayesian_score(bn::DiscreteBayesNet, data::DataFrame, prior::DirichletP
     n = length(bn)
     parent_list = Array{Vector{Int}}(undef, n)
     ncategories = Array{Int}(undef, n)
-#     datamat = convert(Matrix{Int}, data)'
     datamat = Matrix{Int}(data)'
 
     for (i,cpd) in enumerate(bn.cpds)

src/sampling.jl

@@ -170,7 +170,6 @@ function get_weighted_dataframe(bn::BayesNet, nsamples::Integer, evidence::Assig
     t[:p] = w / sum(w)
 
 
-#     convert(DataFrame, t)
     t = DataFrame(t)
 end