Remove constant labels from prediction

This commit is contained in:
th0rntwig 2022-10-06 19:26:33 +02:00
parent edb942f662
commit a9d5e04a43
4 changed files with 26 additions and 0 deletions

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@ -460,6 +460,18 @@ class FreqaiDataKitchen:
return df
def check_pred_labels(self, df_predictions: DataFrame) -> None:
"""
Check that prediction feature labels match training feature labels.
:params:
:df_predictions: incoming predictions
"""
train_labels = self.data_dictionary["train_features"].columns
pred_labels = df_predictions.columns
if len(train_labels.difference(pred_labels)) != 0:
self.data_dictionary["prediction_features"] = df_predictions[train_labels]
return
def principal_component_analysis(self) -> None:
"""
Performs Principal Component Analysis on the data for dimensionality reduction

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@ -492,6 +492,8 @@ class IFreqaiModel(ABC):
# ensure user is feeding the correct indicators to the model
self.check_if_feature_list_matches_strategy(dk)
dk.check_pred_labels(dk.data_dictionary['prediction_features'])
if ft_params.get('inlier_metric_window', 0):
dk.compute_inlier_metric(set_='predict')

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@ -107,6 +107,8 @@ def make_unfiltered_dataframe(mocker, freqai_conf):
unfiltered_dataframe = freqai.dk.use_strategy_to_populate_indicators(
strategy, corr_dataframes, base_dataframes, freqai.dk.pair
)
for i in range(5):
unfiltered_dataframe[f'constant_{i}'] = i
unfiltered_dataframe = freqai.dk.slice_dataframe(new_timerange, unfiltered_dataframe)

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@ -181,6 +181,8 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat):
corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
for i in range(5):
df[f'constant_{i}'] = i
metadata = {"pair": "LTC/BTC"}
freqai.start_backtesting(df, metadata, freqai.dk)
@ -208,6 +210,8 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf):
corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
for i in range(5):
df[f'constant_{i}'] = i
metadata = {"pair": "LTC/BTC"}
freqai.start_backtesting(df, metadata, freqai.dk)
@ -233,6 +237,8 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog):
corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
for i in range(5):
df[f'constant_{i}'] = i
metadata = {"pair": "ADA/BTC"}
freqai.start_backtesting(df, metadata, freqai.dk)
@ -256,6 +262,8 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog):
corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
for i in range(5):
df[f'constant_{i}'] = i
freqai.start_backtesting(df, metadata, freqai.dk)
assert log_has_re(
@ -312,6 +320,8 @@ def test_follow_mode(mocker, freqai_conf):
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
df = strategy.dp.get_pair_dataframe('ADA/BTC', '5m')
for i in range(5):
df[f'constant_{i}'] = i
freqai.start_live(df, metadata, strategy, freqai.dk)
assert len(freqai.dk.return_dataframe.index) == 5702