Update app.py

app.py

@@ -110,64 +110,63 @@ def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
 def run_seed_frame(seed_depth1, Strength_var, strength_grow, Teams_used, Total_Runs):
- RunsVar = 1
-seed_depth_def = seed_depth1
-Strength_var_def = Strength_var
-strength_grow_def = strength_grow
-Teams_used_def = Teams_used
-Total_Runs_def = Total_Runs
-
-while RunsVar <= seed_depth_def:
-    if RunsVar <= 3:
-        FieldStrength = Strength_var_def
-        RandomPortfolio, maps_dict = get_correlated_portfolio_for_sim(Total_Runs_def * 0.1)
-        FinalPortfolio = RandomPortfolio
-        FinalPortfolio2, maps_dict2 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * 0.1)
-        
-        # Replace pd.concat with pl.vstack
-        FinalPortfolio = pl.vstack([FinalPortfolio, FinalPortfolio2])
-        
-        maps_dict.update(maps_dict2)
-        del FinalPortfolio2
-        del maps_dict2
-    elif 3 < RunsVar <= 4:
-        FieldStrength += (strength_grow_def + ((30 - len(Teams_used_def)) * 0.001))
-        FinalPortfolio3, maps_dict3 = get_correlated_portfolio_for_sim(Total_Runs_def * 0.1)
-        FinalPortfolio4, maps_dict4 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * 0.1)
-        
-        # Replace pd.concat with pl.vstack
-        FinalPortfolio = pl.vstack([FinalPortfolio, FinalPortfolio3, FinalPortfolio4])
-        
-        # Replace drop_duplicates and reset_index
-        FinalPortfolio = FinalPortfolio.drop_duplicates(subset=["Projection", "Own"]).sort("index")
-
-        maps_dict.update(maps_dict3)
-        maps_dict.update(maps_dict4)
-        del FinalPortfolio3
-        del maps_dict3
-        del FinalPortfolio4
-        del maps_dict4
-    elif RunsVar > 4:
-        FieldStrength = 1
-        FinalPortfolio3, maps_dict3 = get_correlated_portfolio_for_sim(Total_Runs_def * 0.1)
-        FinalPortfolio4, maps_dict4 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * 0.1)
-        
-        # Replace pd.concat with pl.vstack
-        FinalPortfolio = pl.vstack([FinalPortfolio, FinalPortfolio3, FinalPortfolio4])
-        
-        # Replace drop_duplicates and reset_index
-        FinalPortfolio = FinalPortfolio.drop_duplicates(subset=["Projection", "Own"]).sort("index")
-        
-        maps_dict.update(maps_dict3)
-        maps_dict.update(maps_dict4)
-        del FinalPortfolio3
-        del maps_dict3
-        del FinalPortfolio4
-        del maps_dict4
-        
-    RunsVar += 1
+     RunsVar = 1
+    seed_depth_def = seed_depth1
+    Strength_var_def = Strength_var
+    strength_grow_def = strength_grow
+    Teams_used_def = Teams_used
+    Total_Runs_def = Total_Runs
+    
+    while RunsVar <= seed_depth_def:
+        if RunsVar <= 3:
+            FieldStrength = Strength_var_def
+            RandomPortfolio, maps_dict = get_correlated_portfolio_for_sim(Total_Runs_def * 0.1)
+            FinalPortfolio = RandomPortfolio
+            FinalPortfolio2, maps_dict2 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * 0.1)
+            
+            # Replace pd.concat with pl.vstack
+            FinalPortfolio = pl.vstack([FinalPortfolio, FinalPortfolio2])
+            
+            maps_dict.update(maps_dict2)
+            del FinalPortfolio2
+            del maps_dict2
+        elif 3 < RunsVar <= 4:
+            FieldStrength += (strength_grow_def + ((30 - len(Teams_used_def)) * 0.001))
+            FinalPortfolio3, maps_dict3 = get_correlated_portfolio_for_sim(Total_Runs_def * 0.1)
+            FinalPortfolio4, maps_dict4 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * 0.1)
+            
+            # Replace pd.concat with pl.vstack
+            FinalPortfolio = pl.vstack([FinalPortfolio, FinalPortfolio3, FinalPortfolio4])
+            
+            # Replace drop_duplicates and reset_index
+            FinalPortfolio = FinalPortfolio.drop_duplicates(subset=["Projection", "Own"]).sort("index")
+    
+            maps_dict.update(maps_dict3)
+            maps_dict.update(maps_dict4)
+            del FinalPortfolio3
+            del maps_dict3
+            del FinalPortfolio4
+            del maps_dict4
+        elif RunsVar > 4:
+            FieldStrength = 1
+            FinalPortfolio3, maps_dict3 = get_correlated_portfolio_for_sim(Total_Runs_def * 0.1)
+            FinalPortfolio4, maps_dict4 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * 0.1)
+            
+            # Replace pd.concat with pl.vstack
+            FinalPortfolio = pl.vstack([FinalPortfolio, FinalPortfolio3, FinalPortfolio4])
+            
+            # Replace drop_duplicates and reset_index
+            FinalPortfolio = FinalPortfolio.drop_duplicates(subset=["Projection", "Own"]).sort("index")
+            
+            maps_dict.update(maps_dict3)
+            maps_dict.update(maps_dict4)
+            del FinalPortfolio3
+            del maps_dict3
+            del FinalPortfolio4
+            del maps_dict4
+            
+        RunsVar += 1
 
-        
     return FinalPortfolio, maps_dict
 
 def create_stack_options(player_data, wr_var):