Update with penalty values

.gitignore

@@ -8,4 +8,3 @@ torchGeometricDatasets
 tests/generatedGraphs
 visualizations
 evaluation_results
-.env
\ No newline at end of file

README.md

@@ -18,14 +18,14 @@ The script allows for running experiments on two types of datasets: structured a
 First, create and activate a virtual environment:
 
 ```bash
-# Create virtual environment
-python -m venv venv
+# Create virtual environment with .venv directory
+python -m venv .venv
 
 # Activate virtual environment
 # On Windows
-venv\Scripts\activate
+.venv\Scripts\activate
 # On Unix or MacOS
-source venv/bin/activate
+source .venv/bin/activate
 ```
 
 ### 2. Install Dependencies

requirements.txt

@@ -31,3 +31,4 @@ urllib3==2.2.2
 yarl==1.9.4
 python-dotenv==1.0.1
 pytest==8.3.3
+tabulate==0.9.0
\ No newline at end of file

structured_datasets_experiment.py

@@ -14,7 +14,7 @@ from ontolearn.metrics import Accuracy, Precision, Recall, F1
 from pathlib import Path
 
 
-def explain_gnn(model, dataset, datasetName, run_dir, add_node_type, high_level_concepts=None, create_high_level_concepts_as_boolean=True, selected_labels=None):
+def explain_gnn(model, dataset, datasetName, run_dir, add_node_type, high_level_concepts=None, create_high_level_concepts_as_boolean=True, selected_labels=None, penalty=1):
     """Explain GNN predictions and store results in a CSV file."""
     renderer = DLSyntaxObjectRenderer()
     fileName = datasetName
@@ -42,7 +42,7 @@ def explain_gnn(model, dataset, datasetName, run_dir, add_node_type, high_level_
     
     for label in labels_to_evaluate:
         # Generate explanations
-        hypotheses, explainer_model = explainer.explain(label, 5, max_runtime=90, num_generations=1000)
+        hypotheses, explainer_model = explainer.explain(label, 5, max_runtime=90, num_generations=1000, penalty=penalty)
 
         # Best hypothesis
         best_hypothesis = hypotheses[0]