inject rng in rule extraction strategy

Author: PasoStudio73

src/dataset.jl

@@ -306,6 +306,8 @@ Extract the logiset (if present) from the dataset's MLJ machine.
 """
 get_logiset(ds::ModalDataSet)::SupportedLogiset = ds.mach.data[1].modalities[1]
 
+get_rng(ds::AbstractDataSet) = get_rng(ds.pinfo)
+
 # ---------------------------------------------------------------------------- #
 #                           MLJ models's extra setup                           #
 # ---------------------------------------------------------------------------- #

src/extractrules.jl

@@ -23,7 +23,7 @@ to_namedtuple(x) = NamedTuple{fieldnames(typeof(x))}(ntuple(i -> getfield(x, i),
 # ---------------------------------------------------------------------------- #
 function extractrules(
     extractor :: InTreesRuleExtractor,
-    params    :: NamedTuple,
+    _         :: NamedTuple,
     ds        :: AbstractDataSet,
     solem     :: Vector{AbstractModel}
 )::Vector{DecisionSet}

src/partition.jl

@@ -32,8 +32,10 @@ struct PartitionInfo{T} <: AbstractPartitionInfo
 end
 
 # ---------------------------------------------------------------------------- #
-#                                  base show                                   #
+#                                   methods                                    #
 # ---------------------------------------------------------------------------- #
+get_rng(p::PartitionInfo) = p.rng
+
 function Base.show(io::IO, info::PartitionInfo)
     println(io, "PartitionInfo:")
     for field in fieldnames(PartitionInfo)

src/symbolic_analysis.jl

@@ -218,6 +218,18 @@ function sole_predict(solem::AbstractModel, y_test::AbstractVector{<:Label})
         preds
 end
 
+# set the random number generator for a rule extraction strategy
+function set_rng(r::RuleExtractor, rng::Random.AbstractRNG)::RuleExtractor
+    T = typeof(r)
+
+    fnames = fieldnames(T)
+    fvalues = map(fnames) do fn
+        fn === :rng ? rng : getfield(r, fn)
+    end
+    
+    return T(; NamedTuple{fnames}(fvalues)...)
+end
+
 # ---------------------------------------------------------------------------- #
 #                                eval measures                                 #
 # ---------------------------------------------------------------------------- #
@@ -285,10 +297,11 @@ end
 #                         internal symbolic_analysis                           #
 # ---------------------------------------------------------------------------- #
 function _symbolic_analysis!(
-    modelset::ModelSet;
-    extractor::Union{MaybeRuleExtractor,Tuple{RuleExtractor,NamedTuple}}=nothing,
-    association::MaybeAbstractAssociationRuleExtractor=nothing,
-    measures::Tuple{Vararg{FussyMeasure}}=()
+    modelset    :: AbstractModelSet;
+    extractor   :: Union{MaybeRuleExtractor,Tuple{RuleExtractor,NamedTuple}}=nothing,
+    # extractor::MaybeRuleExtractor=nothing,
+    association :: MaybeAbstractAssociationRuleExtractor=nothing,
+    measures    :: Tuple{Vararg{FussyMeasure}}=()
 )::ModelSet
     ds    = dsetup(modelset)
     solem = solemodels(modelset)
@@ -300,7 +313,8 @@ function _symbolic_analysis!(
         else
             params = NamedTuple(;)
         end
-        
+
+        :rng ∈ fieldnames(typeof(extractor)) && (extractor = set_rng(extractor, get_rng(ds)))
         extractrules(extractor, params, ds, solem)
     end)