diff --git a/Zeus_8_3_2_B_4_2.py b/Zeus_8_3_2_B_4_2.py index dd311c5..38d35ad 100644 --- a/Zeus_8_3_2_B_4_2.py +++ b/Zeus_8_3_2_B_4_2.py @@ -318,8 +318,8 @@ class Zeus_8_3_2_B_4_2(IStrategy): self.pairs[pair]['count_of_buys'] = 1 self.pairs[pair]['current_profit'] = 0 self.pairs[pair]['last_palier_index'] = -1 - self.pairs[pair]['last_max'] = max(last_candle['haclose'], self.pairs[pair]['last_max']) - self.pairs[pair]['last_min'] = min(last_candle['haclose'], self.pairs[pair]['last_min']) + self.pairs[pair]['last_max'] = max(last_candle['close'], self.pairs[pair]['last_max']) + self.pairs[pair]['last_min'] = min(last_candle['close'], self.pairs[pair]['last_min']) dispo = round(self.wallets.get_available_stake_amount()) self.printLineLog() @@ -409,8 +409,8 @@ class Zeus_8_3_2_B_4_2(IStrategy): # print(f"current_time={current_time} current_profit={current_profit} expected_profit={expected_profit}") max_touch_before = self.pairs[pair]['max_touch'] - self.pairs[pair]['last_max'] = max(last_candle['haclose'], self.pairs[pair]['last_max']) - self.pairs[pair]['last_min'] = min(last_candle['haclose'], self.pairs[pair]['last_min']) + self.pairs[pair]['last_max'] = max(last_candle['close'], self.pairs[pair]['last_max']) + self.pairs[pair]['last_min'] = min(last_candle['close'], self.pairs[pair]['last_min']) count_of_buys = trade.nr_of_successful_entries @@ -456,7 +456,7 @@ class Zeus_8_3_2_B_4_2(IStrategy): # self.trades = list() # return 'pft_' + str(count_of_buys) - self.pairs[pair]['max_touch'] = max(last_candle['haclose'], self.pairs[pair]['max_touch']) + self.pairs[pair]['max_touch'] = max(last_candle['close'], self.pairs[pair]['max_touch']) def getShortName(self, pair): @@ -538,7 +538,7 @@ class Zeus_8_3_2_B_4_2(IStrategy): sma5 = str(sma5_1d) + ' ' + str(sma5_1h) - last_lost = round((last_candle['haclose'] - self.pairs[pair]['max_touch']) / self.pairs[pair]['max_touch'], 3) + last_lost = round((last_candle['close'] - self.pairs[pair]['max_touch']) / self.pairs[pair]['max_touch'], 3) if buys is None: buys = '' @@ -855,7 +855,7 @@ class Zeus_8_3_2_B_4_2(IStrategy): # # self.calculateProbabilite2Index(dataframe, ['futur_percent_1d'], 'sma24_deriv1_1h', 'sma5_1d') - dataframe['ema_volume'] = 20 * (dataframe['volume'] * dataframe['hapercent']) / ( + dataframe['ema_volume'] = 20 * (dataframe['volume'] * dataframe['percent']) / ( abs(dataframe['volume'].shift(1)) + abs(dataframe['volume'].shift(2))) self.calculeDerivees(dataframe, 'ema_volume', factor_1=10, factor_2=1) @@ -948,7 +948,7 @@ class Zeus_8_3_2_B_4_2(IStrategy): & (dataframe['mid_smooth_1h_deriv1'].shift(1) <= dataframe['mid_smooth_1h_deriv1'])), dataframe['close'], np.nan) dataframe['test'] = np.where(dataframe['enter_long'] == 1, dataframe['close'] * 1.01, np.nan) - dataframe['perte_02'] = np.where((dataframe['hapercent3'] * 100 < -0.2), dataframe['close'], np.nan) + dataframe['perte_02'] = np.where((dataframe['percent3'] * 100 < -0.2), dataframe['close'], np.nan) dataframe['mid_smooth_1h_deriv2_inv'] = np.where((dataframe['mid_smooth_1h_deriv2'].shift(2) >= dataframe['mid_smooth_1h_deriv2'].shift(1)) & (dataframe['mid_smooth_1h_deriv2'].shift(1) <= dataframe['mid_smooth_1h_deriv2']), dataframe['close'], np.nan)