fix rl test;
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@ -38,25 +38,10 @@ class freqai_rl_test_strat(IStrategy):
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startup_candle_count: int = 30
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can_short = False
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def informative_pairs(self):
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whitelist_pairs = self.dp.current_whitelist()
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corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
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informative_pairs = []
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for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
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for pair in whitelist_pairs:
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informative_pairs.append((pair, tf))
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for pair in corr_pairs:
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if pair in whitelist_pairs:
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continue # avoid duplication
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informative_pairs.append((pair, tf))
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return informative_pairs
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def populate_any_indicators(
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self, pair, df, tf, informative=None, set_generalized_indicators=False
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):
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coin = pair.split('/')[0]
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if informative is None:
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informative = self.dp.get_pair_dataframe(pair, tf)
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@ -64,16 +49,16 @@ class freqai_rl_test_strat(IStrategy):
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for t in self.freqai_info["feature_parameters"]["indicator_periods_candles"]:
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t = int(t)
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informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t)
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informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
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informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t)
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informative[f"%-{pair}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t)
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informative[f"%-{pair}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
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informative[f"%-{pair}adx-period_{t}"] = ta.ADX(informative, window=t)
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# FIXME: add these outside the user strategy?
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# The following columns are necessary for RL models.
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informative[f"%-{coin}raw_close"] = informative["close"]
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informative[f"%-{coin}raw_open"] = informative["open"]
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informative[f"%-{coin}raw_high"] = informative["high"]
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informative[f"%-{coin}raw_low"] = informative["low"]
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informative[f"%-{pair}raw_close"] = informative["close"]
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informative[f"%-{pair}raw_open"] = informative["open"]
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informative[f"%-{pair}raw_high"] = informative["high"]
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informative[f"%-{pair}raw_low"] = informative["low"]
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indicators = [col for col in informative if col.startswith("%")]
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# This loop duplicates and shifts all indicators to add a sense of recency to data
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