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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
View File

@ -65,7 +65,6 @@ class IFreqaiModel(ABC):
self.data_split_parameters = config.get("freqai", {}).get("data_split_parameters")
self.model_training_parameters = config.get("freqai", {}).get("model_training_parameters")
self.feature_parameters = config.get("freqai", {}).get("feature_parameters")
self.model = None
self.retrain = False
self.first = True
self.set_full_path()
@ -372,8 +371,8 @@ class IFreqaiModel(ABC):
"""
Base data cleaning method for train
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
of how outlier data points are dropped from the dataframe used for training.
based on user decided logic. See FreqaiDataKitchen::use_SVM_to_remove_outliers() for an
example of how outlier data points are dropped from the dataframe used for training.
"""
if self.freqai_info.get("feature_parameters", {}).get(

7
freqtrade/freqai/prediction_models/BaseRegressionModel.py
View File

@ -1,6 +1,7 @@
import logging
from typing import Tuple
from typing import Any, Tuple
import numpy.typing as npt
from pandas import DataFrame
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
@ -28,7 +29,7 @@ class BaseRegressionModel(IFreqaiModel):
def train(
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
for storing, saving, loading, and analyzing the data.
@ -83,7 +84,7 @@ class BaseRegressionModel(IFreqaiModel):
def predict(
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.
: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
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))