mohammadian7/freqtrade
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

bring classifier/rl up to new paradigm. ensure tests pass. remove old code. add documentation, add new example transform

Browse Source
This commit is contained in:
robcaulk
2023-05-29 13:33:29 +02:00
parent 31e19add27
commit e572653616
18 changed files with 390 additions and 754 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/freqai/test_freqai_interface.py
+1 -43
View File
@@ -74,6 +74,7 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
freqai_conf = make_rl_config(freqai_conf)
# test the RL guardrails
freqai_conf['freqai']['feature_parameters'].update({"use_SVM_to_remove_outliers": True})
freqai_conf['freqai']['feature_parameters'].update({"DI_threshold": 2})
freqai_conf['freqai']['data_split_parameters'].update({'shuffle': True})
if 'test_3ac' in model or 'test_4ac' in model:
@@ -162,7 +163,6 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, s
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").is_file()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").is_file()
assert len(freqai.dk.data['training_features_list']) == 14
shutil.rmtree(Path(freqai.dk.full_path))
@@ -218,7 +218,6 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
f"{freqai.dk.model_filename}_model{model_file_extension}").exists()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").exists()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").exists()
shutil.rmtree(Path(freqai.dk.full_path))
@@ -283,9 +282,6 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog)
_, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
df = base_df[freqai_conf["timeframe"]]
for i in range(5):
df[f'%-constant_{i}'] = i
metadata = {"pair": "LTC/BTC"}
freqai.dk.set_paths('LTC/BTC', None)
freqai.start_backtesting(df, metadata, freqai.dk, strategy)
@@ -293,14 +289,6 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog)
assert len(model_folders) == num_files
Trade.use_db = True
assert log_has_re(
"Removed features ",
caplog,
)
assert log_has_re(
"Removed 5 features from prediction features, ",
caplog,
)
Backtesting.cleanup()
shutil.rmtree(Path(freqai.dk.full_path))
@@ -425,36 +413,6 @@ def test_backtesting_fit_live_predictions(mocker, freqai_conf, caplog):
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.dk.live = True
timerange = TimeRange.parse_timerange("20180110-20180130")
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
freqai.dd.pair_dict = MagicMock()
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
new_timerange = TimeRange.parse_timerange("20180120-20180130")
freqai.dk.set_paths('ADA/BTC', None)
freqai.extract_data_and_train_model(
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))
def test_plot_feature_importance(mocker, freqai_conf):
from freqtrade.freqai.utils import plot_feature_importance