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dataframe -> df_analyzed in backtesting and edge

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hroff-1902
2020-03-13 03:54:56 +03:00
parent 3208faf7ed
commit ebb0187f40
2 changed files with 12 additions and 12 deletions
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14
freqtrade/edge/edge_positioning.py
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@@ -137,10 +137,10 @@ class Edge:
pair_data = pair_data.sort_values(by=['date']) pair_data = pair_data.sort_values(by=['date'])
pair_data = pair_data.reset_index(drop=True) pair_data = pair_data.reset_index(drop=True)
dataframe = self.strategy.advise_sell( df_analyzed = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy() self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
trades += self._find_trades_for_stoploss_range(dataframe, pair, self._stoploss_range) trades += self._find_trades_for_stoploss_range(df_analyzed, pair, self._stoploss_range)
# If no trade found then exit # If no trade found then exit
if len(trades) == 0: if len(trades) == 0:
@@ -359,11 +359,11 @@ class Edge:
# Returning a list of pairs in order of "expectancy" # Returning a list of pairs in order of "expectancy"
return final return final
def _find_trades_for_stoploss_range(self, dataframe, pair, stoploss_range): def _find_trades_for_stoploss_range(self, df, pair, stoploss_range):
buy_column = dataframe['buy'].values buy_column = df['buy'].values
sell_column = dataframe['sell'].values sell_column = df['sell'].values
date_column = dataframe['date'].values date_column = df['date'].values
ohlc_columns = dataframe[['open', 'high', 'low', 'close']].values ohlc_columns = df[['open', 'high', 'low', 'close']].values
result: list = [] result: list = []
for stoploss in stoploss_range: for stoploss in stoploss_range:

10
freqtrade/optimize/backtesting.py
View File

@@ -164,19 +164,19 @@ class Backtesting:
pair_data.loc[:, 'buy'] = 0 # cleanup from previous run pair_data.loc[:, 'buy'] = 0 # cleanup from previous run
pair_data.loc[:, 'sell'] = 0 # cleanup from previous run pair_data.loc[:, 'sell'] = 0 # cleanup from previous run
dataframe = self.strategy.advise_sell( df_analyzed = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy() self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
# To avoid using data from future, we use buy/sell signals shifted # To avoid using data from future, we use buy/sell signals shifted
# from the previous candle # from the previous candle
dataframe.loc[:, 'buy'] = dataframe['buy'].shift(1) df_analyzed.loc[:, 'buy'] = df_analyzed['buy'].shift(1)
dataframe.loc[:, 'sell'] = dataframe['sell'].shift(1) df_analyzed.loc[:, 'sell'] = df_analyzed['sell'].shift(1)
dataframe.drop(dataframe.head(1).index, inplace=True) df_analyzed.drop(df_analyzed.head(1).index, inplace=True)
# Convert from Pandas to list for performance reasons # Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.) # (Looping Pandas is slow.)
data[pair] = [x for x in dataframe.itertuples()] data[pair] = [x for x in df_analyzed.itertuples()]
return data return data
def _get_close_rate(self, sell_row, trade: Trade, sell: SellCheckTuple, def _get_close_rate(self, sell_row, trade: Trade, sell: SellCheckTuple,