Update src/bin/semantic_similarity_infer.py

src/bin/semantic_similarity_infer.py

@@ -52,7 +52,7 @@ def calculateCorrelationforOntology(aspect, matrix_type):
     similarityMatrixNameDict = {
         "All": os.path.join(script_dir, "../data/preprocess/human_" + aspect + "_proteinSimilarityMatrix.csv"),
         "500": os.path.join(script_dir, "../data/preprocess/human_" + aspect + "_proteinSimilarityMatrix_for_highest_annotated_500_proteins.csv"),
-        "Sparse": os.path.join(script_dir, "../data/preprocess/human_" + aspect + "_proteinSimilarityMatrix_for_highest_annotated_500_proteins.csv"),
+        "sparse": os.path.join(script_dir, "../data/preprocess/human_" + aspect + "_proteinSimilarityMatrix_for_highest_annotated_500_proteins.csv"),
         "200": os.path.join(script_dir, "../data/preprocess/human_" + aspect + "_proteinSimilarityMatrix_for_highest_annotated_200_proteins.csv")
     }
 
@@ -64,7 +64,7 @@ def calculateCorrelationforOntology(aspect, matrix_type):
     for prot in proteinList:
         proteinListNew.append(prot)
 
-    if matrix_type == "Sparse":
+    if matrix_type == "sparse":
         sparsified_path = os.path.join(script_dir, "../data/auxilary_input/SparsifiedSimilarityCoordinates_" + aspect + "_for_highest_500.npy")
         sparsified_similarity_coordinates = np.load(sparsified_path)
         protParamList = sparsified_similarity_coordinates
@@ -77,7 +77,7 @@ def calculateCorrelationforOntology(aspect, matrix_type):
     for tup in tqdm(protParamList):
         i = tup[0]
         j = tup[1]
-        if matrix_type == "Sparse":
+        if matrix_type == "sparse":
             protein1 = proteinListNew[i]
             protein2 = proteinListNew[j]
             real = human_proteinSimilarityMatrix.loc[protein1, protein2]