drawdown calc fixes + compound round fix

app.py

@@ -295,24 +295,23 @@ def get_sd_df(sd_df, sd, bot_selections, dca1, dca2, dca3, dca4, dca5, dca6, fee
     sd_df['Cumulative P/L (-)'] = sd_df['Net P/L Per Trade (-)'].cumsum()
     return sd_df
     
-def get_account_drawdown(trades, principal):
+def get_account_drawdown(trades, principal_balance):
     max_draw = 0.0
     beg = 0 
     fin = 0 
-    try:
-        trades = trades.dropna()
-        for candidate in trades.index[:-1]:
-            future = trades[candidate+1:]
-            delta = future - trades[candidate]
+    trades = np.hstack([0.0, trades.dropna().values]) + principal_balance
+    if len(trades) > 2:
+        for ind in range(len(trades)-1):
+            delta = trades[ind+1:] - trades[ind]
             if max_draw > delta.min():
                 max_draw = min(max_draw, delta.min())
-                beg = candidate 
+                beg = ind
                 fin = delta.argmin()
-                max_draw_perc = max_draw/(principal+trades[beg])
-    except:
+                max_draw_perc = 100*max_draw/(trades[beg])
+    else: 
         max_draw = min(max_draw, trades)
-        max_draw_perc = max_draw/(principal_balance)
-    return 100*max_draw_perc, (beg, fin)
+        max_draw_perc = 100*max_draw/(principal_balance)
+    return max_draw_perc 
     
 def runapp() -> None:
             bot_selections = "Pure Bread"
@@ -408,10 +407,10 @@ def runapp() -> None:
                     df['Compounded Return'] = df['Return Per Trade'].cumprod()
                     df['New Balance'] = [min(dollar_cap/lev, bal*principal_balance) for bal in df['Compounded Return']]
                     df['Balance used in Trade'] = np.concatenate([[principal_balance], df['New Balance'].values[:-1]])
-                df['Net P/L Per Trade'] = (df['Return Per Trade']-1)*df['Balance used in Trade']
+                df['Net P/L Per Trade'] = drop_frac_cents((df['Return Per Trade']-1)*df['Balance used in Trade'])
                 df['Cumulative P/L'] = df['Net P/L Per Trade'].cumsum()
 
-                max_draw, (beg, fin) = get_account_drawdown(df['Cumulative P/L'], principal_balance)
+                max_draw = get_account_drawdown(df['Cumulative P/L'], principal_balance)
                 cum_pl = df.loc[df.dropna().index[-1],'Cumulative P/L'] + principal_balance
 
                 effective_return = 100*((cum_pl - principal_balance)/principal_balance)