Update src/bin/PROBE.py

src/bin/PROBE.py

@@ -29,9 +29,8 @@ def run_probe(benchmarks, representation_name, representation_file_human, repres
         ssi.protein_names = ssi.representation_dataframe['Entry'].tolist()
         ssi.similarity_tasks = similarity_tasks
         ssi.detailed_output = detailed_output
-        print("IN SIMILARITY CALC")
         similarity_result = ssi.calculate_all_correlations()
-        print("OUT SIMILARITY CALC")
+        print("Similarity Result:")
         print(similarity_result)
         
 
@@ -42,7 +41,9 @@ def run_probe(benchmarks, representation_name, representation_file_human, repres
         fp.representation_dataframe = human_representation_dataframe
         fp.representation_name = representation_name
         fp.detailed_output = detailed_output
-        fp.pred_output()
+        function_results = fp.pred_output()
+        print("Function results:")
+        print(function_results)
 
     if "family" in benchmarks:
         print("\n\nDrug target protein family classification benchmark is running...\n")
@@ -50,13 +51,17 @@ def run_probe(benchmarks, representation_name, representation_file_human, repres
         tfc.representation_name = representation_name
         tfc.detailed_output = detailed_output
         for dataset in family_prediction_dataset:
-            tfc.score_protein_rep(dataset)
+            family_result = tfc.score_protein_rep(dataset)
+            print(f"Family results for {dataset}:")
+            print(family_result)
 
     if "affinity" in benchmarks:
         print("\n\nProtein-protein binding affinity estimation benchmark is running...\n")
         bae.skempi_vectors_path = representation_file_affinity
         bae.representation_name = representation_name
-        bae.predict_affinities_and_report_results()
+        affinity result = bae.predict_affinities_and_report_results()
+        print("Affinity Results:")
+        print(affinity_result)
 
     print("\n\nPROBE (Protein RepresentatiOn Benchmark) run is finished...\n")
     return 0