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Correctly handle identical timerame merges

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Matthias
2020-09-04 20:09:02 +02:00
parent 7bc8927914
commit cc684c5141
3 changed files with 40 additions and 7 deletions
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docs/strategy-customization.md
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@@ -518,10 +518,10 @@ class SampleStrategy(IStrategy):
# Use the helper function merge_informative_pair to safely merge the pair
# Automatically renames the columns and merges a shorter timeframe dataframe and a longer timeframe informative pair
# FFill to have the 1d value available in every row throughout the day.
# Without this, comparisons would only work once per day.
# use ffill to have the 1d value available in every row throughout the day.
# Without this, comparisons between columns of the original and the informative pair would only work once per day.
# Full documentation of this method, see below
dataframe = merge_informative_pair(dataframe, informative_pairs, inf_tf, ffill=True)
dataframe = merge_informative_pair(dataframe, informative_pairs, self.timeframe, inf_tf, ffill=True)
# Calculate rsi of the original dataframe (5m timeframe)
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
@@ -589,6 +589,7 @@ All columns of the informative dataframe will be available on the returning data
# This is necessary since the data is always the "open date"
# and a 15m candle starting at 12:15 should not know the close of the 1h candle from 12:00 to 13:00
minutes = timeframe_to_minutes(inf_tf)
# Only do this if the timeframes are different:
informative['date_merge'] = informative["date"] + pd.to_timedelta(minutes, 'm')
# Combine the 2 dataframes