Add prototype for justification in create_justification method

Author: Balramt

owlapy/owl_reasoner.py

@@ -1018,110 +1018,6 @@ def reset_and_disable_cache(self):
 
 
 class SyncReasoner(AbstractOWLReasoner):
-
-    # def create_justifications(self, owl_individuals: Set[OWLNamedIndividual] = None,
-    #                           owl_class_expression: OWLClassExpression = None) -> List[Set[OWLAxiom]]:
-    #     """
-    #     Generate justifications for why the given individual(s) are inferred to be instances of the specified class.
-    #
-    #     Args:
-    #         owl_individuals (Set[OWLNamedIndividual]): Set of individuals to explain.
-    #         owl_class_expression (OWLClassExpression): Class expression to justify.
-    #
-    #     Returns:
-    #         List of sets of OWLAxioms, each representing a justification.
-    #     """
-    #     if owl_individuals is None or owl_class_expression is None:
-    #         raise ValueError("Both owl_individuals and owl_class_expression are required.")
-    #
-    #     import com.clarkparsia.owlapi.explanation.BlackBoxExplanation;
-    #     import com.clarkparsia.owlapi.explanation.ExplanationGenerator;
-    #     import com.clarkparsia.owlapi.explanation.SingleExplanationGeneratorImpl;
-    #     #from org.semanticweb.owl.explanation.api import ExplanationGeneratorFactory
-    #    # from org.semanticweb.owlapi.explanation.impl import ExplanationGeneratorFactoryImpl
-    #
-    #   #  from org.semanticweb.owl.explanation.api import Explanation
-    #    # from org.semanticweb.owl.explanation.impl.blackbox import BlackBoxExplanation
-    #    from org.semanticweb.owlapi.explanation import ExplanationGeneratorFactoryImpl
-    #
-    #     justifications = []
-    #
-    #     # Java OWL API types
-    #     j_class_expr = self.mapper.map_(owl_class_expression)
-    #     j_ontology = self._owlapi_ontology
-    #
-    #     # Explanation setup
-    #     factory = ExplanationGeneratorFactoryImpl()
-    #     generator = factory.createExplanationGenerator(self._owlapi_reasoner)
-    #
-    #     for ind in owl_individuals:
-    #         j_individual = self.mapper.map_(ind)
-    #         axiom = self._owlapi_manager.getOWLDataFactory().getOWLClassAssertionAxiom(j_class_expr, j_individual)
-    #
-    #         # Get multiple explanations (justifications)
-    #         explanations = generator.getExplanations(axiom, 10)  # limit to 10 justifications
-    #         for explanation in explanations:
-    #             axiom_set = explanation.getAxioms()
-    #             py_axioms = {self.mapper.map_(ax) for ax in axiom_set}
-    #             justifications.append(py_axioms)
-    #
-    #     return justifications
-
-    # def create_justifications(self, owl_individuals: Set[OWLNamedIndividual] = None,
-    #                           owl_class_expression: OWLClassExpression = None) -> List[Set[OWLAxiom]]:
-    #     """
-    #     Generate justifications for why the given individual(s) are inferred to be instances of the specified class.
-    #
-    #     Args:
-    #         owl_individuals (Set[OWLNamedIndividual]): Set of individuals to explain.
-    #         owl_class_expression (OWLClassExpression): Class expression to justify.
-    #
-    #     Returns:
-    #         List of sets of OWLAxioms, each representing a justification.
-    #     """
-    #     if owl_individuals is None or owl_class_expression is None:
-    #         raise ValueError("Both owl_individuals and owl_class_expression are required.")
-    #
-    #     # Import Clark & Parsia explanation classes via JPype
-    #     from com.clarkparsia.owlapi.explanation import BlackBoxExplanation, SingleExplanationGeneratorImpl, ExplanationGenerator
-    #     from com.clarkparsia.owlapi.explanation.util import MultipleExplanationGenerator
-    #     # Import PelletReasonerFactory
-    #     from openllet.owlapi import PelletReasonerFactory
-    #
-    #     justifications = []
-    #
-    #     # Map to Java OWL API types
-    #     j_class_expr = self.mapper.map_(owl_class_expression)
-    #     j_ontology = self._owlapi_ontology
-    #     j_reasoner = self._owlapi_reasoner
-    #     j_data_factory = self._owlapi_manager.getOWLDataFactory()
-    #
-    #     # Create the reasoner factory (not the reasoner instance)
-    #     reasoner_factory = PelletReasonerFactory.getInstance()
-    #
-    #     # Create explanation generator
-    #     blackbox_exp = BlackBoxExplanation(j_ontology,reasoner_factory, j_reasoner)
-    #     mult_expl_gen = MultipleExplanationGenerator(blackbox_exp)
-    #     #explanation_gen = SingleExplanationGeneratorImpl(blackbox_exp)
-    #     explanation_gen = blackbox_exp
-    #     print("explanation_gen ",explanation_gen)
-    #     print("Explanation generator class:", explanation_gen.getClass().getName())
-    #
-    #     # For each individual, get explanations for class assertion axiom
-    #     for ind in owl_individuals:
-    #         j_individual = self.mapper.map_(ind)
-    #         axiom = j_data_factory.getOWLClassAssertionAxiom(j_class_expr, j_individual)
-    #
-    #         # Get multiple explanations (limit 10)
-    #         explanations = explanation_gen.getExplanations(axiom, 10)
-    #
-    #         for explanation in explanations:
-    #             # explanation is a Set<OWLAxiom>
-    #             py_axioms = {self.mapper.map_(ax) for ax in explanation}
-    #             justifications.append(py_axioms)
-    #
-    #     return justifications
-
     def create_justifications(self, owl_individuals: Set[OWLNamedIndividual] = None,
                               owl_class_expression: OWLClassExpression = None) -> List[Set[OWLAxiom]]:
         """
@@ -1140,19 +1036,15 @@ def create_justifications(self, owl_individuals: Set[OWLNamedIndividual] = None,
         # Import necessary Java classes
         from com.clarkparsia.owlapi.explanation import BlackBoxExplanation, ExplanationGenerator,HSTExplanationGenerator,SatisfiabilityConverter
         from openllet.owlapi import PelletReasonerFactory
-        from org.semanticweb.owlapi.model import OWLClassExpression
-
-        justifications = []
 
         # Map Python OWL API types to Java OWL API types
         j_class_expr = self.mapper.map_(owl_class_expression)
-        #print("j_class_expr", j_class_expr)
         j_individual = self.mapper.map_(owl_individuals)
-        #print("j_individual",j_individual)
         j_ontology = self._owlapi_ontology
-        #print("j_ontology", j_ontology)
         j_reasoner = self._owlapi_reasoner
         j_data_factory = self._owlapi_manager.getOWLDataFactory()
+
+
       #  owl_individuals_istances = self._instances(owl_class_expression, direct=False)
        # print("owl_individuals_istances", owl_individuals_istances)
        # j_individuals= self.mapper.map_(owl_individuals_istances)
@@ -1165,14 +1057,7 @@ def create_justifications(self, owl_individuals: Set[OWLNamedIndividual] = None,
         blackbox_exp = BlackBoxExplanation(j_ontology, reasoner_factory, j_reasoner)
 
         explanation_gen = HSTExplanationGenerator(blackbox_exp)
-        #j_explanations = explanation_gen.getExplanations(j_class_expr)
         converter = SatisfiabilityConverter(j_data_factory)
-        #print("j_explanations",j_explanations)
-
-
-        # ExplanationGenerator implements ExplanationGenerator interface
-       # explanation_gen = blackbox_exp
-
         justifications = []
 
 
@@ -1185,9 +1070,6 @@ def create_justifications(self, owl_individuals: Set[OWLNamedIndividual] = None,
             # Step 2: Convert to unsatisfiable class
             unsat_class = converter.convert(class_assertion_axiom)
 
-
-           # print("class_assertion_axiom",class_assertion_axiom)
-
             # Get justifications
             j_explanations = explanation_gen.getExplanations(unsat_class)