performance improvevemnts - backtest freqai from saved predictions

This commit is contained in:
Wagner Costa 2022-12-01 12:53:19 -03:00
parent 95651fcd5a
commit 77dc2c92a7
2 changed files with 13 additions and 11 deletions

View File

@ -462,10 +462,10 @@ class FreqaiDataKitchen:
:param df: Dataframe containing all candles to run the entire backtest. Here
it is sliced down to just the present training period.
"""
df = df.loc[df["date"] >= timerange.startdt, :]
if not self.live:
df = df.loc[df["date"] < timerange.stopdt, :]
df = df.loc[(df["date"] >= timerange.startdt) & (df["date"] < timerange.stopdt), :]
else:
df = df.loc[df["date"] >= timerange.startdt, :]
return df

View File

@ -282,10 +282,10 @@ class IFreqaiModel(ABC):
train_it += 1
total_trains = len(dk.backtesting_timeranges)
self.training_timerange = tr_train
dataframe_train = dk.slice_dataframe(tr_train, dataframe)
dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe)
len_backtest_df = len(dataframe.loc[(dataframe["date"] >= tr_backtest.startdt) & (
dataframe["date"] < tr_backtest.stopdt), :])
if not self.ensure_data_exists(dataframe_backtest, tr_backtest, pair):
if not self.ensure_data_exists(len_backtest_df, tr_backtest, pair):
continue
self.log_backtesting_progress(tr_train, pair, train_it, total_trains)
@ -298,13 +298,15 @@ class IFreqaiModel(ABC):
dk.set_new_model_names(pair, timestamp_model_id)
if dk.check_if_backtest_prediction_is_valid(len(dataframe_backtest)):
if dk.check_if_backtest_prediction_is_valid(len_backtest_df):
self.dd.load_metadata(dk)
dk.find_features(dataframe_train)
dk.find_features(dataframe)
self.check_if_feature_list_matches_strategy(dk)
append_df = dk.get_backtesting_prediction()
dk.append_predictions(append_df)
else:
dataframe_train = dk.slice_dataframe(tr_train, dataframe)
dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe)
if not self.model_exists(dk):
dk.find_features(dataframe_train)
dk.find_labels(dataframe_train)
@ -804,16 +806,16 @@ class IFreqaiModel(ABC):
self.pair_it = 1
self.current_candle = self.dd.current_candle
def ensure_data_exists(self, dataframe_backtest: DataFrame,
def ensure_data_exists(self, len_dataframe_backtest: int,
tr_backtest: TimeRange, pair: str) -> bool:
"""
Check if the dataframe is empty, if not, report useful information to user.
:param dataframe_backtest: the backtesting dataframe, maybe empty.
:param len_dataframe_backtest: the len of backtesting dataframe
:param tr_backtest: current backtesting timerange.
:param pair: current pair
:return: if the data exists or not
"""
if self.config.get("freqai_backtest_live_models", False) and len(dataframe_backtest) == 0:
if self.config.get("freqai_backtest_live_models", False) and len_dataframe_backtest == 0:
logger.info(f"No data found for pair {pair} from "
f"from { tr_backtest.start_fmt} to {tr_backtest.stop_fmt}. "
"Probably more than one training within the same candle period.")