Zeus_8_3_2_B_4_2 tests tendancies

Zeus_8_3_2_B_4_2.py

@@ -155,7 +155,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         # last_candle_12 = dataframe.iloc[-13].squeeze()
 
         # allow_to_buy = True #(not self.stop_all) #& (not self.all_down)
-        allow_to_buy = True  # (rate <= float(limit)) | (entry_tag == 'force_entry')
+        allow_to_buy = not last_candle['tendency'] in ('B--', 'B++')  # (rate <= float(limit)) | (entry_tag == 'force_entry')
         self.trades = list()
         dispo = round(self.wallets.get_available_stake_amount())
 
@@ -166,7 +166,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         self.pairs[pair]['count_of_buys'] = 1
         self.pairs[pair]['current_profit'] = 0
 
-        print(
+        self.printLog(
             f"|{'-' * 18}+{'-' * 12}+{'-' * 5}+{'-' * 20}+{'-' * 14}+{'-' * 8}+{'-' * 10}+{'-' * 7}+{'-' * 13}+{'-' * 14}+{'-' * 14}+{'-' * 7}+{'-' * 12}|"
         )
 
@@ -175,7 +175,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         self.log_trade(
             last_candle=last_candle,
             date=current_time,
-            action="START BUY",
+            action="START BUY" if allow_to_buy else "Canceled",
             pair=pair,
             rate=rate,
             dispo=dispo,
@@ -250,8 +250,10 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         self.pairs[pair]['current_profit'] = current_profit
         pct_first = round((last_candle['close'] - self.pairs[pair]['first_buy']) / self.pairs[pair]['first_buy'], 3)
 
-        # if (last_candle['tendency'] in ('H++', 'H--')):
+        if (last_candle['tendency'] in ('H++', 'H--')) \
-        #     return None
+            and (last_candle['tendency_1d'] in ('H++', 'H--')) \
+            and (last_candle['tendency_1d'] in ('H++', 'H--')) :
+            return None
 
         # if (last_candle['rsi_1d'] > 50) & (last_candle['percent12'] < 0.0):
         if (last_candle['percent3'] < 0.0) & (current_profit > 0.05): #last_candle['min_max200'] / 3):
@@ -318,11 +320,11 @@ class Zeus_8_3_2_B_4_2(IStrategy):
             # print(
             #     f"|{'-' * 18}+{'-' * 12}+{'-' * 12}+{'-' * 20}+{'-' * 14}+{'-' * 8}+{'-' * 10}+{'-' * 7}+{'-' * 13}+{'-' * 14}+{'-' * 14}+{'-' * 7}+{'-' * 12}|"
             # )
-            print(
+            self.printLog(
-                f"| {'Date':<16} | {'Action':<10} |{'Pair':<5}| {'Trade Type':<18} | {'Rate':>12} | {'Dispo':>6} | {'Profit':>8} | {'Pct':>5} | {'max_touch':>11} | {'last_lost':>12} | {'last_max':>12} | {'Buys':>5} | {'Stake':>10} |"
+                f"| {'Date':<16} | {'Action':<10} |{'Pair':<5}| {'Trade Type':<18} | {'Rate':>12} | {'Dispo':>6} | {'Profit':>8} | {'Pct':>6} | {'max_touch':>11} | {'last_lost':>12} | {'last_max':>12} | {'Buys':>5} | {'Stake':>10} |"
             )
-            print(
+            self.printLog(
-                f"|{'-' * 18}+{'-' * 12}+{'-' * 5}+{'-' * 20}+{'-' * 14}+{'-' * 8}+{'-' * 10}+{'-' * 7}+{'-' * 13}+{'-' * 14}+{'-' * 14}+{'-' * 7}+{'-' * 12}|"
+                f"|{'-' * 18}+{'-' * 12}+{'-' * 5}+{'-' * 20}+{'-' * 14}+{'-' * 8}+{'-' * 10}+{'-' * 8}+{'-' * 13}+{'-' * 14}+{'-' * 14}+{'-' * 7}+{'-' * 12}|"
             )
             self.columns_logged += 1
         date = str(date)[:16] if date else "-"
@@ -362,27 +364,32 @@ class Zeus_8_3_2_B_4_2(IStrategy):
                 + " " + str(int(last_candle['rsi_1h'])) \
                 + " " + str(int(last_candle['rsi_diff_1h']))
 
-        print(
+        self.printLog(
             f"| {date:<16} | {action:<10} | {pair[0:3]:<3} | {trade_type or '-':<18} | {rate or '-':>12} | {dispo or '-':>6} "
-            f"| {profit or '-':>8} | {pct_max or '-':>5} | {max_touch or '-':>11} | {last_lost or '-':>12} "
+            f"| {profit or '-':>8} | {pct_max or '-':>6} | {max_touch or '-':>11} | {last_lost or '-':>12} "
             f"| {round(self.pairs[pair]['last_max'], 2) or '-':>12} | {buys or '-':>5} | {stake or '-':>10} "
             f"| {last_candle['tendency'] or '-':>3} | {last_candle['tendency_1h'] or '-':>3} | {last_candle['tendency_1d'] or '-':>3} |"
         )
 
+    def printLog(self, str):
+        print(str)
+        logger.info(str)
+
     def add_tendency_column(self, dataframe: pd.DataFrame) -> pd.DataFrame:
         def tag_by_derivatives(row):
             d1 = row['mid_smooth_deriv1']
             d2 = row['mid_smooth_deriv2']
-    
+            d1_lim_inf = -5
-            if d1 == 0.0 and d2 == 0.0:
+            d1_lim_sup = 5
+            if d1 >= d1_lim_inf and d1 <= d1_lim_sup: # and d2 >= d2_lim_inf and d2 <= d2_lim_sup:
                 return 'P' # Palier
             if d1 == 0.0:
                 return 'DH' if d2 > 0 else 'DB' #Depart Hausse / Départ Baisse
-            if d1 > 0:
+            if d1 > d1_lim_sup:
                 return 'H++' if d2 > 0 else 'H--' #Acceleration Hausse / Ralentissement Hausse
-            if d1 < 0:
+            if d1 < d1_lim_inf:
                 return 'B++' if d2 < 0 else 'B--' # Accéleration Baisse / Ralentissement Baisse
-            return 'indetermine'
+            return 'Mid'
 
         dataframe['tendency'] = dataframe.apply(tag_by_derivatives, axis=1)
         return dataframe
@@ -650,10 +657,13 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         # 2. Calcul du lissage sur 200 bougies par moyenne mobile médiane
         dataframe['mid_smooth'] = dataframe['mid'].rolling(window=window, center=True, min_periods=1).median().rolling(
             3).mean()
+        dataframe['mid_smooth_tag_max'] = (dataframe['mid_smooth'].shift(1)) == 0 & (dataframe['mid_smooth'] < 0)
+        dataframe['mid_smooth_tag_min'] = (dataframe['mid_smooth'].shift(1)) == 0 & (dataframe['mid_smooth'] > 0)
+
         # 2. Dérivée première = différence entre deux bougies successives
-        dataframe['mid_smooth_deriv1'] = dataframe['mid_smooth'].diff()
+        dataframe['mid_smooth_deriv1'] = round(dataframe['mid_smooth'].diff(), 2)
         # 3. Dérivée seconde = différence de la dérivée première
-        dataframe['mid_smooth_deriv2'] = dataframe['mid_smooth_deriv1'].diff()
+        dataframe['mid_smooth_deriv2'] = round(dataframe['mid_smooth_deriv1'].diff(), 2)
         dataframe = self.add_tendency_column(dataframe)
         return dataframe
 
@@ -886,7 +896,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
 
         first_price = self.pairs[pair]['first_buy']
 
-        last_max = current_price
+        last_max = last_candle['max200']
         if self.pairs[pair]['last_max'] > 0:
             last_max = self.pairs[pair]['last_max']
         last_count = self.pairs[pair]['last_count_of_buys']