stable/tests/freqai/test_freqai_datakitchen.py
2022-09-05 00:52:26 +02:00

97 lines
3.5 KiB
Python

import datetime
import shutil
from pathlib import Path
import pytest
from freqtrade.exceptions import OperationalException
from tests.conftest import log_has_re
from tests.freqai.conftest import get_patched_data_kitchen, make_data_dictionary
@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 2.36.",
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) == 2.54
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 8.09%",
caplog,
)