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Merge branch 'develop' into add-inlier-metric

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This commit is contained in:
Robert Caulk
2022-09-06 20:40:21 +02:00
committed by GitHub
parent d44296783e dc4a4bdf09
commit d7585161b2
38 changed files with 664 additions and 349 deletions
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23
tests/freqai/test_freqai_datakitchen.py
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@@ -1,5 +1,5 @@
import datetime
import shutil
from datetime import datetime, timedelta, timezone
from pathlib import Path
import pytest
@@ -57,16 +57,13 @@ def test_split_timerange(
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):
def test_check_if_model_expired(mocker, freqai_conf):
dk = get_patched_data_kitchen(mocker, freqai_conf)
assert dk.check_if_model_expired(timestamp) == expected
now = datetime.now(tz=timezone.utc).timestamp()
assert dk.check_if_model_expired(now) is False
now = (datetime.now(tz=timezone.utc) - timedelta(hours=2)).timestamp()
assert dk.check_if_model_expired(now) is True
shutil.rmtree(Path(dk.full_path))
@@ -75,7 +72,7 @@ def test_use_DBSCAN_to_remove_outliers(mocker, freqai_conf, caplog):
# 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.",
"DBSCAN found eps of 2.36.",
caplog,
)
@@ -84,7 +81,7 @@ 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
assert round(avg_mean_dist, 2) == 2.54
def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf, caplog):
@@ -92,7 +89,7 @@ def test_use_SVM_to_remove_outliers_and_outlier_protection(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%",
"SVM detected 8.09%",
caplog,
)