优化log+6
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@ -995,7 +995,7 @@ class FreqaiPrimer(IStrategy):
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price_bb_ratios = (dataframe['close'] / dataframe['bb_lower_1h']).iloc[-5:]
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bb_threshold = self.bb_lower_deviation.value # 价格/布林带下轨应该小于这个值
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bb_lower_visual = ''.join([get_color_emoji(val, bb_threshold, 'less_than') for val in price_bb_ratios])
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self.strategy_log(f" - 价格接近布林带下轨(越红越近): [{bb_lower_visual}]")
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self.strategy_log(f" - 价格接近布林带下轨(越绿越近): [{bb_lower_visual}]")
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# 如果EMA条件满足但最终条件未满足,输出详细信息
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if ema_trend_count > 0 and final_condition_count == 0:
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@ -1399,7 +1399,7 @@ class FreqaiPrimer(IStrategy):
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price_bb_ratios = (df['close'] / df['bb_lower_3m']).iloc[-5:]
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bb_threshold = self.bb_lower_deviation.value # 价格/布林带下轨应该小于这个值
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bb_lower_visual = ''.join([get_color_emoji(val, bb_threshold, 'less_than') for val in price_bb_ratios])
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self.strategy_log(f" - 价格<布林下轨*{bb_threshold}(越红越近): [{bb_lower_visual}]")
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self.strategy_log(f" - 价格<布林下轨*{bb_threshold}(越绿越近): [{bb_lower_visual}]")
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# EMA趋势过滤条件可视化 (布尔值,使用原来的✅❌)
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ema_cross_condition = df['ema5_cross_above_ema20']
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