From 5e532bd44d067ea585db808f247e224ab7acf670 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?J=C3=A9r=C3=B4me=20Delacotte?= <jerome.delacotte@bappli.com>
Date: Thu, 22 May 2025 20:51:48 +0200
Subject: [PATCH] Calcul 20240101-20250514 1204$ 276.5$

---
 Zeus_8_3_2_B_4_2.py               | 19 +++++--------------
 tools/analyse_hyperopt/analyse.py | 13 +++++++++++++
 2 files changed, 18 insertions(+), 14 deletions(-)
 create mode 100644 tools/analyse_hyperopt/analyse.py

diff --git a/Zeus_8_3_2_B_4_2.py b/Zeus_8_3_2_B_4_2.py
index 72f9e7c..6be0abb 100644
--- a/Zeus_8_3_2_B_4_2.py
+++ b/Zeus_8_3_2_B_4_2.py
@@ -349,8 +349,8 @@ class Zeus_8_3_2_B_4_2(IStrategy):
     # =========================================================================
     # Parameters hyperopt
 
-    buy_val = IntParameter(1, 10, default=50, space='buy')
-    buy_val_adjust = IntParameter(1, 10, default=50, space='buy')
+    buy_mid_smooth_3_deriv1 = DecimalParameter(-0.1, 0.1, decimals=2,  default=-0.06, space='buy')
+    buy_mid_smooth_24_deriv1 = DecimalParameter(-0.6, 0, decimals=2,  default=-0.03, space='buy')
 
     def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, time_in_force: str,
                             current_time: datetime, entry_tag: Optional[str], **kwargs) -> bool:
@@ -596,7 +596,8 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         if not self.dp.runmode.value in ('backtest', 'hyperopt'):
             logger.info(str)
         else:
-            print(str)
+            if not self.dp.runmode.value in ('hyperopt'):
+                print(str)
 
     def add_tendency_column(self, dataframe: pd.DataFrame, suffixe='') -> pd.DataFrame:
         def tag_by_derivatives(row):
@@ -740,7 +741,6 @@ class Zeus_8_3_2_B_4_2(IStrategy):
                 for trade in self.trades:
                     if trade.pair != pair:
                         continue
-                    print(trade)
                     filled_buys = trade.select_filled_orders('buy')
                     count = 0
                     amount = 0
@@ -752,14 +752,12 @@ class Zeus_8_3_2_B_4_2(IStrategy):
                         # Order(id=2396, trade=1019, order_id=29870026652, side=buy, filled=0.00078, price=63921.01,
                         # status=closed, date=2024-08-26 02:20:11)
                         dataframe['last_price'] = buy.price
-                        print(buy)
                         count = count + 1
                         amount += buy.price * buy.filled
                     # dataframe['mid_price'] = (dataframe['last_price'] + dataframe['first_price']) / 2
                     count_buys = count
                     # dataframe['limit'] = dataframe['last_price'] * (1 - self.baisse[count] / 100)
                     # dataframe['amount'] = amount
-                    print(f"amount= {amount}")
 
         # dataframe['mid_smooth_tag'] = qtpylib.crossed_below(dataframe['mid_smooth_24_deriv1'], dataframe['mid_smooth_deriv2_24'])
 
@@ -851,7 +849,6 @@ class Zeus_8_3_2_B_4_2(IStrategy):
 
     def getOpenTrades(self):
         # if len(self.trades) == 0:
-        print('search open trades')
         self.trades = Trade.get_open_trades()
         return self.trades
 
@@ -863,11 +860,6 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         # self.getBinanceOrderBook(pair, dataframe)
         last_candle = dataframe.iloc[-1].squeeze()
 
-        print("---------------" + pair + "----------------")
-        print('adjust stake amount ' + str(self.adjust_stake_amount(pair, dataframe.iloc[-1])))
-        # print('adjust exit price ' + str(self.adjust_exit_price(dataframe.iloc[-1])))
-        print('calcul expected_profit ' + str(expected_profit))
-
         # dataframe.loc[
         #     (
         #         (dataframe['percent'] > 0)
@@ -893,7 +885,6 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         dataframe['test'] = np.where(dataframe['enter_long'] == 1, dataframe['close'] * 1.01, np.nan)
 
         self.paliers = self.get_dca_stakes()
-        print(self.paliers)
 
         if self.dp.runmode.value in ('backtest'):
             today = datetime.now().strftime("%Y-%m-%d-%H:%M:%S")
@@ -1130,7 +1121,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
 
         # if (days_since_open > count_of_buys) & (0 < count_of_buys <= max_buys) & (current_rate <= limit) & (last_candle['enter_long'] == 1):
 
-        condition = True
+        condition = True #(last_candle['mid_smooth_3_deriv1'] > self.buy_mid_smooth_3_deriv1.value) and (last_candle['mid_smooth_24_deriv1'] > self.buy_mid_smooth_24_deriv1.value)
                     #     (last_candle['enter_long'] == 1 & (count_of_buys < 3)) \
                     # or ((before_last_candle['mid_re_smooth_3_deriv1'] <= 0) & (last_candle['mid_re_smooth_3_deriv1'] >= 0) & (3 <= count_of_buys < 6)) \
                     # or ((before_last_candle['mid_smooth_1h_deriv1'] <= 0) & (last_candle['mid_smooth_1h_deriv1'] >= 0) & (6 <= count_of_buys))
diff --git a/tools/analyse_hyperopt/analyse.py b/tools/analyse_hyperopt/analyse.py
new file mode 100644
index 0000000..4326bc8
--- /dev/null
+++ b/tools/analyse_hyperopt/analyse.py
@@ -0,0 +1,13 @@
+import json
+
+with open('/home/jerome/Perso/freqtradeDocker/user_data/hyperopts/hyperopt_results_2025-05-21_XX.json') as f:
+    results = json.load(f)
+
+def custom_score(res):
+    stake = res.get('avg_stake_amount', 1e6)
+    duration = res.get('avg_duration', 1e6)
+    profit = res.get('profit_total_usdt', -1e6)
+    return -stake * 0.4 - duration * 0.3 + profit * 0.3
+
+best = sorted(results, key=custom_score, reverse=True)[0]
+print("Best configuration based on custom score:", best)