import datetime import shutil from pathlib import Path import pytest from freqtrade.exceptions import OperationalException from tests.freqai.conftest import get_patched_data_kitchen, make_data_dictionary from tests.conftest import log_has_re @pytest.mark.parametrize( "timerange, train_period_days, expected_result", [ ("20220101-20220201", 30, "20211202-20220201"), ("20220301-20220401", 15, "20220214-20220401"), ], ) def test_create_fulltimerange( timerange, train_period_days, expected_result, freqai_conf, mocker, caplog ): dk = get_patched_data_kitchen(mocker, freqai_conf) assert dk.create_fulltimerange(timerange, train_period_days) == expected_result shutil.rmtree(Path(dk.full_path)) def test_create_fulltimerange_incorrect_backtest_period(mocker, freqai_conf): dk = get_patched_data_kitchen(mocker, freqai_conf) with pytest.raises(OperationalException, match=r"backtest_period_days must be an integer"): dk.create_fulltimerange("20220101-20220201", 0.5) with pytest.raises(OperationalException, match=r"backtest_period_days must be positive"): dk.create_fulltimerange("20220101-20220201", -1) shutil.rmtree(Path(dk.full_path)) @pytest.mark.parametrize( "timerange, train_period_days, backtest_period_days, expected_result", [ ("20220101-20220201", 30, 7, 9), ("20220101-20220201", 30, 0.5, 120), ("20220101-20220201", 10, 1, 80), ], ) def test_split_timerange( mocker, freqai_conf, timerange, train_period_days, backtest_period_days, expected_result ): freqai_conf.update({"timerange": "20220101-20220401"}) dk = get_patched_data_kitchen(mocker, freqai_conf) tr_list, bt_list = dk.split_timerange(timerange, train_period_days, backtest_period_days) assert len(tr_list) == len(bt_list) == expected_result with pytest.raises( OperationalException, match=r"train_period_days must be an integer greater than 0." ): dk.split_timerange("20220101-20220201", -1, 0.5) shutil.rmtree(Path(dk.full_path)) @pytest.mark.parametrize( "timestamp, expected", [ (datetime.datetime.now(tz=datetime.timezone.utc).timestamp() - 7200, True), (datetime.datetime.now(tz=datetime.timezone.utc).timestamp(), False), ], ) def test_check_if_model_expired(mocker, freqai_conf, timestamp, expected): dk = get_patched_data_kitchen(mocker, freqai_conf) assert dk.check_if_model_expired(timestamp) == expected shutil.rmtree(Path(dk.full_path)) def test_use_DBSCAN_to_remove_outliers(mocker, freqai_conf, caplog): freqai = make_data_dictionary(mocker, freqai_conf) # freqai_conf['freqai']['feature_parameters'].update({"outlier_protection_percentage": 1}) freqai.dk.use_DBSCAN_to_remove_outliers(predict=False) assert log_has_re( "DBSCAN found eps of 2.42.", caplog, ) def test_compute_distances(mocker, freqai_conf): freqai = make_data_dictionary(mocker, freqai_conf) freqai_conf['freqai']['feature_parameters'].update({"DI_threshold": 1}) avg_mean_dist = freqai.dk.compute_distances() assert round(avg_mean_dist, 2) == 2.56 def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf, caplog): freqai = make_data_dictionary(mocker, freqai_conf) freqai_conf['freqai']['feature_parameters'].update({"outlier_protection_percentage": 0.1}) freqai.dk.use_SVM_to_remove_outliers(predict=False) assert log_has_re( "SVM detected 8.46%", caplog, )