Update app.py

app.py

@@ -245,17 +245,15 @@ def create_random_portfolio(Total_Sample_Size, raw_baselines, field_growth):
                 if max_var <= 10:
                     ranges_dict['g_range'] = round(max_var)
                 elif max_var > 10 and max_var <= 16:
-                    ranges_dict['dst_range'] = round(max_var / 1.5)
+                    ranges_dict['g_range'] = round(max_var / 1.5)
                 elif max_var > 16:
-                    ranges_dict['dst_range'] = round(max_var / 2)
+                    ranges_dict['g_range'] = round(max_var / 2)
                 
                 # Generate random portfolios
                 rng = np.random.default_rng()
                 total_elements = [2, 3, 2, 1, 1]
                 keys = ['c', 'w', 'd', 'g', 'util']
                 
-                st.write(max_var)
-                
                 all_choices = [rng.choice(ranges_dict[f"{key}_range"], size=(Total_Sample_Size, elem)) for key, elem in zip(keys, total_elements)]
                 RandomPortfolio = pd.DataFrame(np.hstack(all_choices), columns=['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'G', 'UTIL'])
                 RandomPortfolio['User/Field'] = 0
@@ -268,9 +266,9 @@ def create_random_portfolio(Total_Sample_Size, raw_baselines, field_growth):
                 if max_var <= 10:
                     ranges_dict['g_range'] = round(max_var)
                 elif max_var > 10 and max_var <= 16:
-                    ranges_dict['dst_range'] = round(max_var)
+                    ranges_dict['g_range'] = round(max_var)
                 elif max_var > 16:
-                    ranges_dict['dst_range'] = round(max_var)
+                    ranges_dict['g_range'] = round(max_var)
                 
                 # Generate random portfolios
                 rng = np.random.default_rng()