Fix HybridExample formatting
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@ -1,13 +1,13 @@
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import logging
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from typing import Optional
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import numpy as np
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import pandas as pd
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import talib.abstract as ta
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from freqtrade.strategy import (DecimalParameter, IntParameter, IStrategy,
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merge_informative_pair)
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from pandas import DataFrame
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from freqtrade.strategy import IntParameter, IStrategy, merge_informative_pair
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logger = logging.getLogger(__name__)
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@ -100,7 +100,7 @@ class FreqaiExampleHybridStrategy(IStrategy):
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sell_p2 = IntParameter(7, 21, default=10)
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sell_p3 = IntParameter(7, 21, default=10)
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# FreqAI required function, leave as is or add you additional informatives to existing structure.
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# FreqAI required function, leave as is or add additional informatives to existing structure.
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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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@ -120,7 +120,7 @@ class FreqaiExampleHybridStrategy(IStrategy):
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self, pair, df, tf, informative=None, set_generalized_indicators=False
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):
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"""
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User feeds these indicators to FreqAI to train a classifier to decide
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User feeds these indicators to FreqAI to train a classifier to decide
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if the market will go up or down.
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:param pair: pair to be used as informative
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@ -177,6 +177,7 @@ class FreqaiExampleHybridStrategy(IStrategy):
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return df
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# flake8: noqa: C901
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# User creates their own custom strat here. Present example is a supertrend
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@ -280,12 +281,6 @@ class FreqaiExampleHybridStrategy(IStrategy):
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return True
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def leverage(self, pair: str, current_time: datetime, current_rate: float,
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proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str,
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**kwargs) -> float:
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return 1
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"""
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Supertrend Indicator; adapted for freqtrade, optimized by the math genius.
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from: Perkmeister#2394
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@ -312,10 +307,10 @@ class FreqaiExampleHybridStrategy(IStrategy):
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# Compute final upper and lower bands
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for i in range(period, last_row + 1):
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FINAL_UB[i] = BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i -
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1] or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1]
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FINAL_LB[i] = BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i -
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1] or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1]
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FINAL_UB[i] = (BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i - 1]
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or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1])
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FINAL_LB[i] = (BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i - 1]
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or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1])
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# Set the Supertrend value
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for i in range(period, last_row + 1):
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