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Parametrize regressor tests

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This commit is contained in:
Matthias 2022-09-10 20:06:52 +02:00
parent f97f1dc5c3
commit 88892ba663
1 changed files with 11 additions and 65 deletions
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76
tests/freqai/test_freqai_interface.py
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@ -17,8 +17,18 @@ def is_arm() -> bool:
return "arm" in machine or "aarch64" in machine return "arm" in machine or "aarch64" in machine
def test_extract_data_and_train_model_LightGBM(mocker, freqai_conf): @pytest.mark.parametrize('model', [
'LightGBMRegressor',
'XGBoostRegressor',
'CatboostRegressor',
])
def test_extract_data_and_train_model_Regressors(mocker, freqai_conf, model):
if is_arm() and model == 'CatboostRegressor':
pytest.skip("CatBoost is not supported on ARM")
freqai_conf.update({"freqaimodel": model})
freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"timerange": "20180110-20180130"})
freqai_conf.update({"strategy": "freqai_test_strat"})
strategy = get_patched_freqai_strategy(mocker, freqai_conf) strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf)
@ -86,39 +96,6 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model):
shutil.rmtree(Path(freqai.dk.full_path)) shutil.rmtree(Path(freqai.dk.full_path))
@pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...")
def test_extract_data_and_train_model_Catboost(mocker, freqai_conf):
freqai_conf.update({"timerange": "20180110-20180130"})
freqai_conf.update({"freqaimodel": "CatboostRegressor"})
# freqai_conf.get('freqai', {}).update(
# {'model_training_parameters': {"n_estimators": 100, "verbose": 0}})
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)
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.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}_model.joblib").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))
@pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...") @pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...")
def test_extract_data_and_train_model_CatboostClassifier(mocker, freqai_conf): def test_extract_data_and_train_model_CatboostClassifier(mocker, freqai_conf):
freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"timerange": "20180110-20180130"})
@ -182,37 +159,6 @@ def test_extract_data_and_train_model_LightGBMClassifier(mocker, freqai_conf):
shutil.rmtree(Path(freqai.dk.full_path)) shutil.rmtree(Path(freqai.dk.full_path))
def test_extract_data_and_train_model_XGBoostRegressor(mocker, freqai_conf):
freqai_conf.update({"timerange": "20180110-20180130"})
freqai_conf.update({"freqaimodel": "XGBoostRegressor"})
freqai_conf.update({"strategy": "freqai_test_strat"})
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)
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.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}_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()
shutil.rmtree(Path(freqai.dk.full_path))
def test_start_backtesting(mocker, freqai_conf): def test_start_backtesting(mocker, freqai_conf):
freqai_conf.update({"timerange": "20180120-20180130"}) freqai_conf.update({"timerange": "20180120-20180130"})
freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) freqai_conf.get("freqai", {}).update({"save_backtest_models": True})