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*BREAKING CHANGE* remove unnecessary arguments from populate_any_indicators(), accommodate tests

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This commit is contained in:
robcaulk
2022-07-31 17:05:29 +02:00
parent 153336d424
commit d830105605
5 changed files with 35 additions and 22 deletions
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31
freqtrade/templates/FreqaiExampleStrategy.py
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@@ -65,7 +65,7 @@ class FreqaiExampleStrategy(IStrategy):
return informative_pairs
def populate_any_indicators(
self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False
self, pair, df, tf, informative=None, set_generalized_indicators=False
):
"""
Function designed to automatically generate, name and merge features
@@ -78,9 +78,10 @@ class FreqaiExampleStrategy(IStrategy):
:param df: strategy dataframe which will receive merges from informatives
:param tf: timeframe of the dataframe which will modify the feature names
:param informative: the dataframe associated with the informative pair
:param coin: the name of the coin which will modify the feature names.
"""
coin = pair.split('/')[0]
with self.freqai.lock:
if informative is None:
informative = self.dp.get_pair_dataframe(pair, tf)
@@ -92,11 +93,8 @@ class FreqaiExampleStrategy(IStrategy):
informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t)
informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t)
informative[f"{coin}20sma-period_{t}"] = ta.SMA(informative, timeperiod=t)
informative[f"{coin}21ema-period_{t}"] = ta.EMA(informative, timeperiod=t)
informative[f"%-{coin}close_over_20sma-period_{t}"] = (
informative["close"] / informative[f"{coin}20sma-period_{t}"]
)
informative[f"{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t)
informative[f"{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t)
informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
@@ -148,8 +146,6 @@ class FreqaiExampleStrategy(IStrategy):
df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25
# user adds targets here by prepending them with &- (see convention below)
# If user wishes to use multiple targets, a multioutput prediction model
# needs to be used such as templates/CatboostPredictionMultiModel.py
df["&-s_close"] = (
df["close"]
.shift(-self.freqai_info["feature_parameters"]["label_period_candles"])
@@ -159,6 +155,23 @@ class FreqaiExampleStrategy(IStrategy):
- 1
)
# If user wishes to use multiple targets, they can add more by
# appending more columns with '&'. User should keep in mind that multi targets
# requires a multioutput prediction model such as
# templates/CatboostPredictionMultiModel.py,
# df["&-s_range"] = (
# df["close"]
# .shift(-self.freqai_info["feature_parameters"]["label_period_candles"])
# .rolling(self.freqai_info["feature_parameters"]["label_period_candles"])
# .max()
# -
# df["close"]
# .shift(-self.freqai_info["feature_parameters"]["label_period_candles"])
# .rolling(self.freqai_info["feature_parameters"]["label_period_candles"])
# .min()
# )
return df
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: