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compare full dataframe instead of only last row

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Stefano
2025-08-17 16:05:22 +09:00
parent 5d4edb5ec0
commit 5e5137edc1
1 changed files with 29 additions and 28 deletions
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27
freqtrade/optimize/analysis/lookahead.py
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@@ -25,7 +25,7 @@ class Analysis:
self.total_signals = 0
self.false_entry_signals = 0
self.false_exit_signals = 0
self.false_indicators: list[str] = []
self.false_indicators: set[str] = set()
self.has_bias = False
@@ -70,17 +70,12 @@ class LookaheadAnalysis(BaseAnalysis):
cut_df: DataFrame = cut_vars.indicators[current_pair]
full_df: DataFrame = full_vars.indicators[current_pair]
# cut longer dataframe to length of the shorter
full_df_cut = full_df[(full_df.date == cut_vars.compared_dt)].reset_index(drop=True)
cut_df_cut = cut_df[(cut_df.date == cut_vars.compared_dt)].reset_index(drop=True)
# check if dataframes are not empty
if full_df_cut.shape[0] != 0 and cut_df_cut.shape[0] != 0:
# compare dataframes
compare_df = full_df_cut.compare(cut_df_cut)
# trim full_df to the same index and length as cut_df
cut_full_df = full_df.loc[cut_df.index]
compare_df = cut_full_df.compare(cut_df)
if compare_df.shape[0] > 0:
for col_name, values in compare_df.items():
for col_name in compare_df:
col_idx = compare_df.columns.get_loc(col_name)
compare_df_row = compare_df.iloc[0]
# compare_df now comprises tuples with [1] having either 'self' or 'other'
@@ -92,9 +87,9 @@ class LookaheadAnalysis(BaseAnalysis):
# output differences
if self_value != other_value:
if not self.current_analysis.false_indicators.__contains__(col_name[0]):
self.current_analysis.false_indicators.append(col_name[0])
self.current_analysis.false_indicators.add(col_name[0])
logger.info(
f"=> found look ahead bias in indicator "
f"=> found look ahead bias in column "
f"{col_name[0]}. "
f"{str(self_value)} != {str(other_value)}"
)
@@ -132,7 +127,13 @@ class LookaheadAnalysis(BaseAnalysis):
varholder.data, varholder.timerange = backtesting.load_bt_data()
varholder.timeframe = backtesting.timeframe
varholder.indicators = backtesting.strategy.advise_all_indicators(varholder.data)
temp_indicators = backtesting.strategy.advise_all_indicators(varholder.data)
filled_indicators = dict()
for pair, dataframe in temp_indicators.items():
filled_indicators[pair] = backtesting.strategy.ft_advise_signals(
dataframe, {"pair": pair}
)
varholder.indicators = filled_indicators
varholder.result = self.get_result(backtesting, varholder.indicators)
def fill_entry_and_exit_varHolders(self, result_row):