fix corr_pairs startup candle count bug

This commit is contained in:
Wagner Costa 2023-01-04 14:21:37 -03:00
parent ed2b1b1ed1
commit ed99e7f857
2 changed files with 7 additions and 7 deletions

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@ -67,6 +67,12 @@ Backtesting mode requires [downloading the necessary data](#downloading-data-to-
*want* to retrain a new model with the same config file, you should simply change the `identifier`.
This way, you can return to using any model you wish by simply specifying the `identifier`.
!!! Note
Backtesting calls the `set_freqai_targets()` function for every window defined in `backtest_period_days` parameter
to better simulate the dry/run live behavior, but it's analyzes the whole time-range at once in `feature_engineering_*()` for performance reasons.
Because of this, strategy authors need to make sure that strategies do not look-ahead into the future at `feature_engineering_*()` functions.
Strategy authors should carefully read the [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies)
---
### Saving prediction data

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@ -313,14 +313,8 @@ class IFreqaiModel(ABC):
dk.append_predictions(append_df)
else:
if populate_indicators:
tr_from_main_df = (f'{dataframe["date"].min().strftime("%Y%m%d")}'
f'-{dataframe["date"].max().strftime("%Y%m%d")}')
timerange = TimeRange.parse_timerange(tr_from_main_df)
self.dd.load_all_pair_histories(timerange, self.dk)
corr_df, base_df = self.dd.get_base_and_corr_dataframes(timerange, pair, dk)
dataframe = self.dk.use_strategy_to_populate_indicators(
strategy, prediction_dataframe=dataframe, pair=metadata["pair"],
corr_dataframes=corr_df, base_dataframes=base_df
strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
)
populate_indicators = False