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fix mypy error and add test for principal component analysis

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This commit is contained in:
Robert Caulk 2022-07-25 11:46:59 +02:00
parent 4abc26b582
commit 7b105532d1
3 changed files with 33 additions and 6 deletions
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5
freqtrade/freqai/freqai_interface.py
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@ -65,7 +65,6 @@ class IFreqaiModel(ABC):
self.data_split_parameters = config.get("freqai", {}).get("data_split_parameters") self.data_split_parameters = config.get("freqai", {}).get("data_split_parameters")
self.model_training_parameters = config.get("freqai", {}).get("model_training_parameters") self.model_training_parameters = config.get("freqai", {}).get("model_training_parameters")
self.feature_parameters = config.get("freqai", {}).get("feature_parameters") self.feature_parameters = config.get("freqai", {}).get("feature_parameters")
self.model = None
self.retrain = False self.retrain = False
self.first = True self.first = True
self.set_full_path() self.set_full_path()
@ -372,8 +371,8 @@ class IFreqaiModel(ABC):
""" """
Base data cleaning method for train Base data cleaning method for train
Any function inside this method should drop training data points from the filtered_dataframe Any function inside this method should drop training data points from the filtered_dataframe
based on user decided logic. See FreqaiDataKitchen::remove_outliers() for an example based on user decided logic. See FreqaiDataKitchen::use_SVM_to_remove_outliers() for an
of how outlier data points are dropped from the dataframe used for training. example of how outlier data points are dropped from the dataframe used for training.
""" """
if self.freqai_info.get("feature_parameters", {}).get( if self.freqai_info.get("feature_parameters", {}).get(

7
freqtrade/freqai/prediction_models/BaseRegressionModel.py
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@ -1,6 +1,7 @@
import logging import logging
from typing import Tuple from typing import Any, Tuple
import numpy.typing as npt
from pandas import DataFrame from pandas import DataFrame
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
@ -28,7 +29,7 @@ class BaseRegressionModel(IFreqaiModel):
def train( def train(
self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen
) -> Tuple[DataFrame, DataFrame]: ) -> Any:
""" """
Filter the training data and train a model to it. Train makes heavy use of the datakitchen Filter the training data and train a model to it. Train makes heavy use of the datakitchen
for storing, saving, loading, and analyzing the data. for storing, saving, loading, and analyzing the data.
@ -83,7 +84,7 @@ class BaseRegressionModel(IFreqaiModel):
def predict( def predict(
self, unfiltered_dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False self, unfiltered_dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False
) -> Tuple[DataFrame, DataFrame]: ) -> Tuple[DataFrame, npt.ArrayLike]:
""" """
Filter the prediction features data and predict with it. Filter the prediction features data and predict with it.
:param: unfiltered_dataframe: Full dataframe for the current backtest period. :param: unfiltered_dataframe: Full dataframe for the current backtest period.

27
tests/freqai/test_freqai_interface.py
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@ -194,3 +194,30 @@ def test_follow_mode(mocker, freqai_conf):
assert len(freqai.dk.return_dataframe.index) == 5702 assert len(freqai.dk.return_dataframe.index) == 5702
shutil.rmtree(Path(freqai.dk.full_path)) shutil.rmtree(Path(freqai.dk.full_path))
def test_principal_component_analysis(mocker, freqai_conf):
freqai_conf.update({"timerange": "20180110-20180130"})
freqai_conf.get("freqai", {}).get("feature_parameters", {}).update(
{"princpial_component_analysis": "true"})
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
strategy.freqai_info = freqai_conf.get("freqai", {})
freqai = strategy.freqai
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqai_conf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180130")
freqai.dk.load_all_pair_histories(timerange)
freqai.dd.pair_dict = MagicMock()
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
new_timerange = TimeRange.parse_timerange("20180120-20180130")
freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_pca_object.pkl")
shutil.rmtree(Path(freqai.dk.full_path))