diff --git a/bpeng/pna/score_calculation.py b/bpeng/pna/score_calculation.py
index 8b58ca0b2ca7e7b35a97541974881156a2863d92..c4266d21b9a8cd58cb07a730635139f92fe707fa 100644
--- a/bpeng/pna/score_calculation.py
+++ b/bpeng/pna/score_calculation.py
@@ -9,29 +9,29 @@ def calculate_score_weight(weight_list, details_list):
         index = weight_list[i][0]-1
         score_weight[index] += weight_list[i][1]
 
-    heating_violations_score = [0, 1, 3, 5]
-    num = [0, 1, 3, 11]
-    for i in range(len(num)):
-        initial_value = heating_violations_score[i]
-        if not i == len(num)-1 and details_list['num_of_heating_violations'] < num[i+1]:
-            break
-    score_weight[0] += initial_value
-
-    dob_violations_score = [5, 4, 3, 4, 5]
-    num = [0, 1, 4, 20, 100]
-    for i in range(len(num)):
-        initial_value = dob_violations_score[i]
-        if not i == len(num)-1 and details_list['num_of_dob_violations'] < num[i+1]:
-            break
-    score_weight[3] += initial_value
-
-    ownership_scores = {
-        'Single': 3,
-        'LLC': 5, 
-        'Corporate': 5, 
-        'Non-Profit': 3
-    }
-    score_weight[3] += ownership_scores[details_list['legal_ownership']]
+    # heating_violations_score = [0, 1, 3, 5]
+    # num = [0, 1, 3, 11]
+    # for i in range(len(num)):
+    #     initial_value = heating_violations_score[i]
+    #     if not i == len(num)-1 and details_list['num_of_heating_violations'] < num[i+1]:
+    #         break
+    # score_weight[0] += initial_value
+
+    # dob_violations_score = [5, 4, 3, 4, 5]
+    # num = [0, 1, 4, 20, 100]
+    # for i in range(len(num)):
+    #     initial_value = dob_violations_score[i]
+    #     if not i == len(num)-1 and details_list['num_of_dob_violations'] < num[i+1]:
+    #         break
+    # score_weight[3] += initial_value
+
+    # ownership_scores = {
+    #     'Single': 3,
+    #     'LLC': 5, 
+    #     'Corporate': 5, 
+    #     'Non-Profit': 3
+    # }
+    # score_weight[3] += ownership_scores[details_list['legal_ownership']]
 
     for index in range(len(score_weight)):
         final_criteria_scores.append((index+1, score_weight[index]))