Sync rules alg with paper (remove clusters based groups)

src/rules.py

@@ -288,6 +288,26 @@ def simplify_and_group_rules(
     return new_rules
 
 
+def simplify_rules(X: pd.DataFrame, rules: List[Rule]) -> List[Rule]:
+    minmax = _get_variables_minmax(X)
+
+    new_rules: List[Rule] = []
+    for rule in rules:
+        intervals = _get_varibles_interval(rule.get_antecedent())
+        new_atoms = []
+        for key, value in intervals.items():
+            val: float = 0
+            if value[0] is None and value[1] is not None:
+                val = minmax[key][0]
+            if value[1] is None and value[0] is not None:
+                val = minmax[key][1]
+            if value[0] is not None and value[1] is not None:
+                val = (value[0] + value[1]) / 2
+            new_atoms.append(RuleAtom(key, ComparisonType.EQUALS, val))
+        new_rules.append(Rule(new_atoms, rule.get_consequent()))
+    return new_rules
+
+
 def _get_fuzzy_rule_atom(
     fuzzy_variable: FuzzyVariable, value: float
 ) -> Tuple[Term, float]:
@@ -299,6 +319,30 @@ def _get_fuzzy_rule_atom(
     return (fuzzy_variable[best_value[0]], best_value[1])
 
 
+def simplify_rules_fuzz(
+    X: pd.DataFrame,
+    rules: List[Rule],
+    fuzzy_variables: Dict[str, FuzzyVariable],
+) -> List[Rule]:
+    minmax = _get_variables_minmax(X)
+
+    new_rules: List[Rule] = []
+    for rule in rules:
+        intervals = _get_varibles_interval(rule.get_antecedent())
+        new_atoms = []
+        for key, value in intervals.items():
+            val: float = 0
+            if value[0] is None and value[1] is not None:
+                val = minmax[key][0]
+            if value[1] is None and value[0] is not None:
+                val = minmax[key][1]
+            if value[0] is not None and value[1] is not None:
+                val = (value[0] + value[1]) / 2
+            new_atoms.append(RuleAtom(key, ComparisonType.EQUALS, val))
+        new_rules.append(Rule(new_atoms, rule.get_consequent()))
+    return new_rules
+
+
 def _get_fuzzy_rules(
     rules: List[Rule], fuzzy_variables: Dict[str, FuzzyVariable]
 ) -> List[Tuple[List[RuleAtom], Term, float]]:
@@ -328,11 +372,11 @@ def _get_fuzzy_rules(
 
 
 def _delete_same_fuzzy_rules(
-    rules_cluster: List[Tuple[List[RuleAtom], Term, float]]
+    rules: List[Tuple[List[RuleAtom], Term, float]]
 ) -> List[Tuple[List[RuleAtom], Term, float]]:
     same_rules: List[int] = []
-    for rule1_index, rule1 in enumerate(rules_cluster):
-        for rule2_index, rule2 in enumerate(rules_cluster):
+    for rule1_index, rule1 in enumerate(rules):
+        for rule2_index, rule2 in enumerate(rules):
             if rule1_index >= rule2_index:
                 continue
             # Remove the same rules
@@ -347,10 +391,10 @@ def _delete_same_fuzzy_rules(
             if str(rule1[0]) == str(rule2[0]) and str(rule1[2]) > str(rule2[2]):
                 same_rules.append(rule1_index)
                 break
-    return [rule for index, rule in enumerate(rules_cluster) if index not in same_rules]
+    return [rule for index, rule in enumerate(rules) if index not in same_rules]
 
 
-def get_fuzzy_rules(
+def get_grouped_fuzzy_rules(
     clustered_rules: List[List[Rule]], fuzzy_variables: Dict[str, FuzzyVariable]
 ) -> List[FuzzyRule]:
     fuzzy_rules: List[List[Tuple[List[RuleAtom], Term, float]]] = []
@@ -363,3 +407,12 @@ def get_fuzzy_rules(
         for cluster in fuzzy_rules
         for item in cluster
     ]
+
+
+def get_fuzzy_rules(
+    rules: List[Rule], fuzzy_variables: Dict[str, FuzzyVariable]
+) -> List[FuzzyRule]:
+    fuzzy_rules: List[Tuple[List[RuleAtom], Term, float]] = []
+    fuzzy_rules = _get_fuzzy_rules(rules, fuzzy_variables)
+    fuzzy_rules = _delete_same_fuzzy_rules(fuzzy_rules)
+    return [FuzzyRule(reduce(and_, item[0]), item[1]) for item in fuzzy_rules]