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merge develop into feat/freqai-rl-dev

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This commit is contained in:
robcaulk
2022-10-30 10:13:03 +01:00
parent 8d7adfabe9 5c14aeddc6
commit d1a0874683
129 changed files with 2648 additions and 1004 deletions
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2
tests/freqai/conftest.py
View File

@@ -131,6 +131,8 @@ def make_unfiltered_dataframe(mocker, freqai_conf):
unfiltered_dataframe = freqai.dk.use_strategy_to_populate_indicators(
strategy, corr_dataframes, base_dataframes, freqai.dk.pair
)
for i in range(5):
unfiltered_dataframe[f'constant_{i}'] = i
unfiltered_dataframe = freqai.dk.slice_dataframe(new_timerange, unfiltered_dataframe)

2
tests/freqai/test_freqai_backtesting.py
View File

@@ -26,7 +26,7 @@ def test_freqai_backtest_start_backtest_list(freqai_conf, mocker, testdatadir, c
'--config', 'config.json',
'--datadir', str(testdatadir),
'--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
'--timeframe', '1h',
'--timeframe', '1m',
'--strategy-list', CURRENT_TEST_STRATEGY
]
args = get_args(args)

3
tests/freqai/test_freqai_datakitchen.py
View File

@@ -125,7 +125,8 @@ def test_normalize_data(mocker, freqai_conf):
freqai = make_data_dictionary(mocker, freqai_conf)
data_dict = freqai.dk.data_dictionary
freqai.dk.normalize_data(data_dict)
assert len(freqai.dk.data) == 32
assert any('_max' in entry for entry in freqai.dk.data.keys())
assert any('_min' in entry for entry in freqai.dk.data.keys())
def test_filter_features(mocker, freqai_conf):

27
tests/freqai/test_freqai_interface.py
View File

@@ -30,6 +30,7 @@ def is_mac() -> bool:
@pytest.mark.parametrize('model', [
'LightGBMRegressor',
'XGBoostRegressor',
'XGBoostRFRegressor',
'CatboostRegressor',
'ReinforcementLearner',
'ReinforcementLearner_multiproc',
@@ -69,10 +70,17 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model):
data_load_timerange = TimeRange.parse_timerange("20180125-20180130")
new_timerange = TimeRange.parse_timerange("20180127-20180130")
freqai.dk.set_paths('ADA/BTC', None)
freqai.train_timer("start", "ADA/BTC")
freqai.extract_data_and_train_model(
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
freqai.train_timer("stop", "ADA/BTC")
freqai.dd.save_metric_tracker_to_disk()
freqai.dd.save_drawer_to_disk()
assert Path(freqai.dk.full_path / "metric_tracker.json").is_file()
assert Path(freqai.dk.full_path / "pair_dictionary.json").is_file()
assert Path(freqai.dk.data_path /
f"{freqai.dk.model_filename}_model.{model_save_ext}").is_file()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file()
@@ -107,6 +115,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model):
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
new_timerange = TimeRange.parse_timerange("20180120-20180130")
freqai.dk.set_paths('ADA/BTC', None)
freqai.extract_data_and_train_model(
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
@@ -125,6 +134,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model):
'LightGBMClassifier',
'CatboostClassifier',
'XGBoostClassifier',
'XGBoostRFClassifier',
])
def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
if is_arm() and model == 'CatboostClassifier':
@@ -148,6 +158,7 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
new_timerange = TimeRange.parse_timerange("20180120-20180130")
freqai.dk.set_paths('ADA/BTC', None)
freqai.extract_data_and_train_model(new_timerange, "ADA/BTC",
strategy, freqai.dk, data_load_timerange)
@@ -172,7 +183,7 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
("CatboostClassifier", 6, "freqai_test_classifier")
],
)
def test_start_backtesting(mocker, freqai_conf, model, num_files, strat):
def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog):
freqai_conf.get("freqai", {}).update({"save_backtest_models": True})
freqai_conf['runmode'] = RunMode.BACKTEST
if is_arm() and "Catboost" in model:
@@ -205,6 +216,9 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat):
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")
for i in range(5):
df[f'%-constant_{i}'] = i
# df.loc[:, f'%-constant_{i}'] = i
metadata = {"pair": "LTC/BTC"}
freqai.start_backtesting(df, metadata, freqai.dk)
@@ -212,6 +226,14 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat):
assert len(model_folders) == num_files
Trade.use_db = True
assert log_has_re(
"Removed features ",
caplog,
)
assert log_has_re(
"Removed 5 features from prediction features, ",
caplog,
)
Backtesting.cleanup()
shutil.rmtree(Path(freqai.dk.full_path))
@@ -237,6 +259,7 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf):
metadata = {"pair": "LTC/BTC"}
freqai.start_backtesting(df, metadata, freqai.dk)
model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
assert len(model_folders) == 9
shutil.rmtree(Path(freqai.dk.full_path))
@@ -281,6 +304,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, 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")
freqai.start_backtesting(df, metadata, freqai.dk)
assert log_has_re(
@@ -337,6 +361,7 @@ def test_follow_mode(mocker, freqai_conf):
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
df = strategy.dp.get_pair_dataframe('ADA/BTC', '5m')
freqai.start_live(df, metadata, strategy, freqai.dk)
assert len(freqai.dk.return_dataframe.index) == 5702