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Dynamicly generated timeframes

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This commit is contained in:
Masoud Azizi
2021-05-19 10:40:00 +04:30
committed by GitHub
parent 26aa19c4ae
commit 46ae26afa2
1 changed files with 13 additions and 9 deletions
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user_data/strategies/MultiMa.py
+13 -9
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@@ -42,19 +42,19 @@ class MultiMa(IStrategy):
timeframe = '4h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# SMA - Simple Moving Average
for i in range(1, self.buy_ma_count.value+1):
dataframe[f'buy-ma-{i}'] = ta.SMA(dataframe,
timeperiod=int(i * self.buy_ma_gap.value))
for i in range(1, self.sell_ma_count.value+1):
dataframe[f'sell-ma-{i}'] = ta.SMA(dataframe,
timeperiod=int(i * self.sell_ma_gap.value))
# We shoud dinamicly generate indicators
# cuz this method just run one time in hyperopts
# if you have static timeframes you can move first loop of buy and sell trends populators inside this method
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
for i in range(1, self.buy_ma_count.value+1):
dataframe[f'buy-ma-{i}'] = ta.SMA(dataframe,
timeperiod=int(i * self.buy_ma_gap.value))
conditions = []
for i in range(1, self.buy_ma_count.value):
@@ -73,6 +73,10 @@ class MultiMa(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
for i in range(1, self.sell_ma_count.value+1):
dataframe[f'sell-ma-{i}'] = ta.SMA(dataframe,
timeperiod=int(i * self.sell_ma_gap.value))
conditions = []
for i in range(1, self.sell_ma_count.value):