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ruff format: update more tests

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Matthias
2024-05-12 16:04:01 +02:00
parent 40e161a5b9
commit 02075b15e3
4 changed files with 524 additions and 499 deletions
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109
tests/optimize/test_hyperoptloss.py
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@@ -9,96 +9,103 @@ from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
def test_hyperoptlossresolver_noname(default_conf):
with pytest.raises(OperationalException,
match="No Hyperopt loss set. Please use `--hyperopt-loss` to specify "
"the Hyperopt-Loss class to use."):
with pytest.raises(
OperationalException,
match="No Hyperopt loss set. Please use `--hyperopt-loss` to specify "
"the Hyperopt-Loss class to use.",
):
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_hyperoptlossresolver(mocker, default_conf) -> None:
hl = ShortTradeDurHyperOptLoss
mocker.patch(
'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver.load_object',
MagicMock(return_value=hl())
"freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver.load_object",
MagicMock(return_value=hl()),
)
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
default_conf.update({"hyperopt_loss": "SharpeHyperOptLossDaily"})
x = HyperOptLossResolver.load_hyperoptloss(default_conf)
assert hasattr(x, "hyperopt_loss_function")
def test_hyperoptlossresolver_wrongname(default_conf) -> None:
default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
default_conf.update({"hyperopt_loss": "NonExistingLossClass"})
with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'):
with pytest.raises(OperationalException, match=r"Impossible to load HyperoptLoss.*"):
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_loss_calculation_prefer_correct_trade_count(hyperopt_conf, hyperopt_results) -> None:
hyperopt_conf.update({'hyperopt_loss': "ShortTradeDurHyperOptLoss"})
hyperopt_conf.update({"hyperopt_loss": "ShortTradeDurHyperOptLoss"})
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
correct = hl.hyperopt_loss_function(
hyperopt_results, 600, datetime(2019, 1, 1), datetime(2019, 5, 1)
)
over = hl.hyperopt_loss_function(
hyperopt_results, 600 + 100, datetime(2019, 1, 1), datetime(2019, 5, 1)
)
under = hl.hyperopt_loss_function(
hyperopt_results, 600 - 100, datetime(2019, 1, 1), datetime(2019, 5, 1)
)
assert over > correct
assert under > correct
def test_loss_calculation_prefer_shorter_trades(hyperopt_conf, hyperopt_results) -> None:
resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20
resultsb.loc[1, "trade_duration"] = 20
hyperopt_conf.update({'hyperopt_loss': "ShortTradeDurHyperOptLoss"})
hyperopt_conf.update({"hyperopt_loss": "ShortTradeDurHyperOptLoss"})
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
longer = hl.hyperopt_loss_function(hyperopt_results, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
shorter = hl.hyperopt_loss_function(resultsb, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
longer = hl.hyperopt_loss_function(
hyperopt_results, 100, datetime(2019, 1, 1), datetime(2019, 5, 1)
)
shorter = hl.hyperopt_loss_function(resultsb, 100, datetime(2019, 1, 1), datetime(2019, 5, 1))
assert shorter < longer
def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_over["profit_ratio"] = hyperopt_results["profit_ratio"] * 2
results_under = hyperopt_results.copy()
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
results_under["profit_ratio"] = hyperopt_results["profit_ratio"] / 2
hyperopt_conf.update({'hyperopt_loss': "ShortTradeDurHyperOptLoss"})
hyperopt_conf.update({"hyperopt_loss": "ShortTradeDurHyperOptLoss"})
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
correct = hl.hyperopt_loss_function(
hyperopt_results, 600, datetime(2019, 1, 1), datetime(2019, 5, 1)
)
over = hl.hyperopt_loss_function(results_over, 600, datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(
results_under, 600, datetime(2019, 1, 1), datetime(2019, 5, 1)
)
assert over < correct
assert under > correct
@pytest.mark.parametrize('lossfunction', [
"OnlyProfitHyperOptLoss",
"SortinoHyperOptLoss",
"SortinoHyperOptLossDaily",
"SharpeHyperOptLoss",
"SharpeHyperOptLossDaily",
"MaxDrawDownHyperOptLoss",
"MaxDrawDownRelativeHyperOptLoss",
"CalmarHyperOptLoss",
"ProfitDrawDownHyperOptLoss",
])
@pytest.mark.parametrize(
"lossfunction",
[
"OnlyProfitHyperOptLoss",
"SortinoHyperOptLoss",
"SortinoHyperOptLossDaily",
"SharpeHyperOptLoss",
"SharpeHyperOptLossDaily",
"MaxDrawDownHyperOptLoss",
"MaxDrawDownRelativeHyperOptLoss",
"CalmarHyperOptLoss",
"ProfitDrawDownHyperOptLoss",
],
)
def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunction) -> None:
results_over = hyperopt_results.copy()
results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2 + 0.2
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_over["profit_abs"] = hyperopt_results["profit_abs"] * 2 + 0.2
results_over["profit_ratio"] = hyperopt_results["profit_ratio"] * 2
results_under = hyperopt_results.copy()
results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2 - 0.2
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
results_under["profit_abs"] = hyperopt_results["profit_abs"] / 2 - 0.2
results_under["profit_ratio"] = hyperopt_results["profit_ratio"] / 2
default_conf.update({'hyperopt_loss': lossfunction})
default_conf.update({"hyperopt_loss": lossfunction})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(
hyperopt_results,
@@ -107,7 +114,7 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
max_date=datetime(2019, 5, 1),
config=default_conf,
processed=None,
backtest_stats={'profit_total': hyperopt_results['profit_abs'].sum()}
backtest_stats={"profit_total": hyperopt_results["profit_abs"].sum()},
)
over = hl.hyperopt_loss_function(
results_over,
@@ -116,7 +123,7 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
max_date=datetime(2019, 5, 1),
config=default_conf,
processed=None,
backtest_stats={'profit_total': results_over['profit_abs'].sum()}
backtest_stats={"profit_total": results_over["profit_abs"].sum()},
)
under = hl.hyperopt_loss_function(
results_under,
@@ -125,7 +132,7 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
max_date=datetime(2019, 5, 1),
config=default_conf,
processed=None,
backtest_stats={'profit_total': results_under['profit_abs'].sum()}
backtest_stats={"profit_total": results_under["profit_abs"].sum()},
)
assert over < correct
assert under > correct