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diff --git a/ontoScorer/metrics.py b/ontoScorer/metrics.py
index 73fd413c38cce339f00800388902305f355985e0..feedd3327057aa10299e37b6698be1c4cf9f1f2f 100644
--- a/ontoScorer/metrics.py
+++ b/ontoScorer/metrics.py
@@ -2,28 +2,84 @@
# -*-coding:Utf-8 -*
#==============================================================================
-# ontoScorer: [brief description of the module]
+# ontoScorer: Ontology Scoring Module
#------------------------------------------------------------------------------
-# Detailed module description
+# This module provides metrics to evaluate and compare different ontologies.
+# It calculates precision, recall, and F1 score for various ontology elements
+# such as classes, object properties, data properties, restrictions, individuals,
+# and annotations. It also computes an overall score taking into account all
+# the ontology elements. The comparison is performed between a reference ontology
+# and a generated ontology, allowing users to evaluate how well the generated
+# ontology matches the reference.
#==============================================================================
+
from sklearn.metrics import precision_score, recall_score, f1_score
from ontoScorer.ontology import Ontology
class Metrics:
+
+ #--------------------------------------------------------------------------
+ # Constructor(s)
+ #--------------------------------------------------------------------------
+
def __init__(self):
- self.precision = 0
- self.recall = 0
- self.f1 = 0
+ self.scores = {
+ "class": {"precision": 0, "recall": 0, "f1": 0},
+ "object_property": {"precision": 0, "recall": 0, "f1": 0},
+ "data_property": {"precision": 0, "recall": 0, "f1": 0},
+ "restriction": {"precision": 0, "recall": 0, "f1": 0},
+ "individual": {"precision": 0, "recall": 0, "f1": 0},
+ "annotation": {"precision": 0, "recall": 0, "f1": 0},
+ "overall": {"precision": 0, "recall": 0, "f1": 0}
+ }
+
+
+ #--------------------------------------------------------------------------
+ # Computing Method(s)
+ #--------------------------------------------------------------------------
def calculate(self, reference_ontology, generated_ontology):
- reference_classes = set([cls.name() for cls in reference_ontology.get_classes()])
- generated_classes = set([cls.name() for cls in generated_ontology.get_classes()])
+ methods = [
+ ("class", "get_classes"),
+ ("object_property", "get_object_properties"),
+ ("data_property", "get_data_properties"),
+ ("restriction", "get_restrictions"),
+ ("individual", "get_individuals"),
+ #("annotation", "get_annotations")
+ ]
+
+ y_true_overall = []
+ y_pred_overall = []
+
+ for score_name, method_name in methods:
+ reference_elements = set([elem.name() for elem in getattr(reference_ontology, method_name)()])
+ generated_elements = set([elem.name() for elem in getattr(generated_ontology, method_name)()])
+
+ all_elements = reference_elements.union(generated_elements)
+ y_true = [1 if elem in reference_elements else 0 for elem in all_elements]
+ y_pred = [1 if elem in generated_elements else 0 for elem in all_elements]
+
+ self.scores[score_name]["precision"] = precision_score(y_true, y_pred)
+ self.scores[score_name]["recall"] = recall_score(y_true, y_pred)
+ self.scores[score_name]["f1"] = f1_score(y_true, y_pred)
- all_classes = reference_classes.union(generated_classes)
- y_true = [1 if cls in reference_classes else 0 for cls in all_classes]
- y_pred = [1 if cls in generated_classes else 0 for cls in all_classes]
+ y_true_overall.extend(y_true)
+ y_pred_overall.extend(y_pred)
- self.precision = precision_score(y_true, y_pred)
- self.recall = recall_score(y_true, y_pred)
- self.f1 = f1_score(y_true, y_pred)
\ No newline at end of file
+ self.scores["overall"]["precision"] = precision_score(y_true_overall, y_pred_overall)
+ self.scores["overall"]["recall"] = recall_score(y_true_overall, y_pred_overall)
+ self.scores["overall"]["f1"] = f1_score(y_true_overall, y_pred_overall)
+
+
+ #--------------------------------------------------------------------------
+ # Printing Method(s)
+ #--------------------------------------------------------------------------
+
+ def print_scores(self):
+ for element, scores in self.scores.items():
+ print(f"Metrics for {element.capitalize()}:")
+ print(f"\tPrecision: {scores['precision']:.4f}")
+ print(f"\tRecall: {scores['recall']:.4f}")
+ print(f"\tF1 Score: {scores['f1']:.4f}")
+ print("----------------------------")
\ No newline at end of file
diff --git a/ontoScorer/ontology.py b/ontoScorer/ontology.py
index 90d432950bd7f96755e8036d5c8a71e86cd3b717..cb2d501cd78090b846f8c42725596f5994bd4388 100644
--- a/ontoScorer/ontology.py
+++ b/ontoScorer/ontology.py
@@ -114,17 +114,21 @@ class Ontology:
return self._get_elements_of_type(OWL.Restriction)
def get_individuals(self) -> list:
- """Extract all individuals from the ontology."""
- all_types = set(self.graph.subjects(RDF.type))
- non_individuals = {element.reference for element in
- self.get_classes() +
- self.get_object_properties() +
- self.get_data_properties()}
+ """Extract all individuals from the ontology, including elements explicitly typed as owl:Individual,
+ owl:NamedIndividual or any class."""
- individuals = all_types - non_individuals
-
- return [NamedElement(i, self.graph) if isinstance(i, URIRef) else BlankElement(i, self.graph)
- for i in individuals]
+ # Getting elements of type owl:NamedIndividual and owl:Individual
+ individuals = self._get_elements_of_type(OWL.NamedIndividual)
+ individuals += self._get_elements_of_type(URIRef("http://www.w3.org/2002/07/owl#Individual"))
+
+ # Getting all elements typed as one of the classes
+ all_classes = {cls.reference for cls in self.get_classes()}
+ for cls in all_classes:
+ individuals += [NamedElement(s, self.graph) if isinstance(s, URIRef) else BlankElement(s, self.graph)
+ for s, _, o in self.graph.triples((None, RDF.type, cls))]
+
+ return list(set(individuals)) # Ensuring uniqueness
+
def get_annotations(self):
"""Extract all annotation comments from the ontology."""
diff --git a/ontoScorer/report.py b/ontoScorer/report.py
index 30f7659bb493a623975d29a418ae5f42f48bf32a..a5df58a36f0422d36b97f5f5a6cd3425f8bd78d1 100644
--- a/ontoScorer/report.py
+++ b/ontoScorer/report.py
@@ -33,9 +33,9 @@ class Report:
report_str += "The generated ontology and the reference ontology have the same number of classes."
report_str += "\n\nEvaluation Metrics:"
- report_str += f"\nPrecision: {self.metrics.precision}"
- report_str += f"\nRecall: {self.metrics.recall}"
- report_str += f"\nF1 Score: {self.metrics.f1}"
+ report_str += f'\nPrecision: {self.metrics.scores["overall"]["precision"]}'
+ report_str += f'\nRecall: {self.metrics.scores["overall"]["recall"]}'
+ report_str += f'\nF1 Score: {self.metrics.scores["overall"]["f1"]}'
return report_str
diff --git a/tests/test_metrics.py b/tests/test_metrics.py
index 4415d78eaa2ad835966f1b350fdefbdf3e9d9d61..9dc65011609dc3e73c66cfba0a52ac1402f00440 100644
--- a/tests/test_metrics.py
+++ b/tests/test_metrics.py
@@ -2,9 +2,39 @@
# -*-coding:Utf-8 -*
#==============================================================================
-# ontoScorer: [brief description of the module]
+# test_metrics: Metrics Testing Module
#------------------------------------------------------------------------------
-# Detailed module description, if needed
+# Contains tests for verifying functionality of the Metrics class.
#==============================================================================
-# TODO
+import unittest
+import os
+from context import ontoScorer
+from ontoScorer.ontology import Ontology
+from ontoScorer.metrics import Metrics
+
+class TestMetrics(unittest.TestCase):
+
+ def setUp(self):
+ DATA_FOLDER_PATH = f'{os.path.dirname(os.path.abspath(__file__))}/test_data'
+ self.ontology1_path = f"{DATA_FOLDER_PATH}/ontology_a.ttl"
+ self.ontology2_path = f"{DATA_FOLDER_PATH}/ontology_b.ttl"
+ self.onto1 = Ontology(self.ontology1_path)
+ self.onto2 = Ontology(self.ontology2_path)
+ self.metrics = Metrics()
+
+ def test_calculate_scores(self):
+ self.metrics.calculate(self.onto1, self.onto2)
+ for key in self.metrics.scores:
+ self.assertTrue(0 <= self.metrics.scores[key]["precision"] <= 1)
+ self.assertTrue(0 <= self.metrics.scores[key]["recall"] <= 1)
+ self.assertTrue(0 <= self.metrics.scores[key]["f1"] <= 1)
+
+
+ def test_print_scores(self):
+ self.metrics.calculate(self.onto1, self.onto2)
+ self.metrics.print_scores()
+
+
+if __name__ == "__main__":
+ unittest.main()
diff --git a/tests/test_ontology.py b/tests/test_ontology.py
index 8da3b2eea6aad01ab668e23029d6fcf0e27fb401..da89d127abbd6f1dc7701f9fd0922c030e497281 100644
--- a/tests/test_ontology.py
+++ b/tests/test_ontology.py
@@ -68,7 +68,7 @@ class TestOntology(unittest.TestCase):
def test_get_individuals(self):
individuals_names = {ind.name() for ind in self.onto1.get_individuals()}
-
+ self.assertEqual(len(individuals_names), 1)
self.assertIn("SolarSystem", individuals_names)
self.assertNotIn("gravitation", individuals_names)