From 6448f30234491ac7e8fddcc113190714bb33b4c5 Mon Sep 17 00:00:00 2001
From: PasoStudio73 <paso.studio73@gmail.com>
Date: Sun, 6 Oct 2024 00:27:52 +0200
Subject: [PATCH] merge local

---
 src/analysis.jl  | 9 +++++----
 src/interface.jl | 1 +
 src/rules.jl     | 3 ---
 src/utils.jl     | 4 ++--
 4 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/src/analysis.jl b/src/analysis.jl
index 5cdc3bc..8b08c31 100644
--- a/src/analysis.jl
+++ b/src/analysis.jl
@@ -207,10 +207,11 @@ function modal_analisys(
         model = ModalDecisionTree(; relations = :IA7, features = metaconditions)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       
         mach = machine(model, X_train, y_train) |> fit!
     end
-    
-    # report(learned_dt_tree).printmodel(variable_names_map=variable_names)
     _, mtree = report(mach).sprinkle(X_test, y_test)
-    # printmodel(sole_dt; show_metrics = true, variable_names_map=variable_names)
+    
+    # report(mach).solemodel(variable_names)
 
-    ModalDecisionTrees.translate(mtree)
+    # model = ModalDecisionTree(; relations = :IA7, features = metaconditions)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       
+    # mach = machine(model, X_train, y_train)
+    # return model, mach
 end
\ No newline at end of file
diff --git a/src/interface.jl b/src/interface.jl
index 145bf04..fecc90d 100644
--- a/src/interface.jl
+++ b/src/interface.jl
@@ -79,4 +79,5 @@ function get_interesting_rules(
     prop_sole_dt = propositional_analisys(X, y, variable_names=variable_names, features=features, train_ratio=train_ratio, rng=rng)
     modal_sole_dt = modal_analisys(X, y; variable_names=variable_names, features=features, nwindows=nwindows, relative_overlap=relative_overlap, train_ratio=train_ratio, rng=rng)
     interesting_rules(prop_sole_dt, modal_sole_dt; features=features, variable_names=variable_names)
+    append_rules(interesting_rules; prop_sole_dt=prop_sole_dt, modal_sole_dt=modal_sole_dt)
 end
\ No newline at end of file
diff --git a/src/rules.jl b/src/rules.jl
index 8a5b1e2..610f886 100644
--- a/src/rules.jl
+++ b/src/rules.jl
@@ -32,9 +32,6 @@ function interesting_rules(
     variable_names::AbstractVector{String},
 )
     if !isnothing(prop_sole_dt)
-        metaconditions = get(propositional_feature_dict, features) do
-            error("Unknown set of features: $features.")
-        end
 
         irules = listrules(
             prop_sole_dt,
diff --git a/src/utils.jl b/src/utils.jl
index 6854a26..5f2cd82 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -14,8 +14,8 @@ function partitioning(X::DataFrame, y::CategoricalArray; train_ratio::Float64=0.
     train, test = partition(eachindex(y), train_ratio, shuffle=true, rng=rng)
     X_train, y_train = X[train, :], y[train]
     X_test, y_test = X[test, :], y[test]
-    println("Training set size: ", size(X_train, 1), ", features: ", size(X_train, 2), " - ", length(y_train))
-    println("Test set size: ", size(X_test, 1), ", features: ", size(X_test, 2), " - ", length(y_test))
+    println("Training set size: ", size(X_train, 1), ", features: ", size(X_train, 2))
+    println("Test set size: ", size(X_test, 1), ", features: ", size(X_test, 2))
     return X_train, y_train, X_test, y_test
 end