merge develop into feat/freqai-rl-dev

tests/freqai/test_freqai_interface.py

@@ -27,16 +27,16 @@ def is_mac() -> bool:
     return "Darwin" in machine
 
 
-@pytest.mark.parametrize('model', [
-    'LightGBMRegressor',
-    'XGBoostRegressor',
-    'XGBoostRFRegressor',
-    'CatboostRegressor',
-    'ReinforcementLearner',
-    'ReinforcementLearner_multiproc',
-    'ReinforcementLearner_test_4ac'
+@pytest.mark.parametrize('model, pca, dbscan', [
+    ('LightGBMRegressor', True, False),
+    ('XGBoostRegressor', False, True),
+    ('XGBoostRFRegressor', False, False),
+    ('CatboostRegressor', False, False),
+    ('ReinforcementLearner', False, False),
+    ('ReinforcementLearner_multiproc', False, False),
+    ('ReinforcementLearner_test_4ac', False, False)
     ])
-def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model):
+def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca, dbscan):
     if is_arm() and model == 'CatboostRegressor':
         pytest.skip("CatBoost is not supported on ARM")
 
@@ -47,6 +47,8 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model):
     freqai_conf.update({"freqaimodel": model})
     freqai_conf.update({"timerange": "20180110-20180130"})
     freqai_conf.update({"strategy": "freqai_test_strat"})
+    freqai_conf['freqai']['feature_parameters'].update({"principal_component_analysis": pca})
+    freqai_conf['freqai']['feature_parameters'].update({"use_DBSCAN_to_remove_outliers": dbscan})
 
     if 'ReinforcementLearner' in model:
         model_save_ext = 'zip'
@@ -89,17 +91,19 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model):
     shutil.rmtree(Path(freqai.dk.full_path))
 
 
-@pytest.mark.parametrize('model', [
-    'LightGBMRegressorMultiTarget',
-    'XGBoostRegressorMultiTarget',
-    'CatboostRegressorMultiTarget',
+@pytest.mark.parametrize('model, strat', [
+    ('LightGBMRegressorMultiTarget', "freqai_test_multimodel_strat"),
+    ('XGBoostRegressorMultiTarget', "freqai_test_multimodel_strat"),
+    ('CatboostRegressorMultiTarget', "freqai_test_multimodel_strat"),
+    ('LightGBMClassifierMultiTarget', "freqai_test_multimodel_classifier_strat"),
+    ('CatboostClassifierMultiTarget', "freqai_test_multimodel_classifier_strat")
     ])
-def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model):
-    if is_arm() and model == 'CatboostRegressorMultiTarget':
+def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, strat):
+    if is_arm() and 'Catboost' in model:
         pytest.skip("CatBoost is not supported on ARM")
 
     freqai_conf.update({"timerange": "20180110-20180130"})
-    freqai_conf.update({"strategy": "freqai_test_multimodel_strat"})
+    freqai_conf.update({"strategy": strat})
     freqai_conf.update({"freqaimodel": model})
     strategy = get_patched_freqai_strategy(mocker, freqai_conf)
     exchange = get_patched_exchange(mocker, freqai_conf)
@@ -216,6 +220,7 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog)
     corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
 
     df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
+    df = freqai.cache_corr_pairlist_dfs(df, freqai.dk)
     for i in range(5):
         df[f'%-constant_{i}'] = i
         # df.loc[:, f'%-constant_{i}'] = i
@@ -362,6 +367,7 @@ def test_follow_mode(mocker, freqai_conf):
 
     df = strategy.dp.get_pair_dataframe('ADA/BTC', '5m')
 
+    freqai.dk.pair = "ADA/BTC"
     freqai.start_live(df, metadata, strategy, freqai.dk)
 
     assert len(freqai.dk.return_dataframe.index) == 5702