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Merge pull request #5651 from freqtrade/simplify_loss_Tests

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Combine most hyperopt-loss tests to one
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Matthias 2021-10-02 14:44:46 +02:00 committed by GitHub
commit 66e19f5775
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2 changed files with 23 additions and 82 deletions
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13
tests/optimize/conftest.py
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@ -39,16 +39,17 @@ def hyperopt(hyperopt_conf, mocker):
def hyperopt_results():
return pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_ratio': [-0.1, 0.2, 0.3],
'profit_abs': [-0.2, 0.4, 0.6],
'trade_duration': [10, 30, 10],
'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI],
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_ratio': [-0.1, 0.2, -0.1, 0.3],
'profit_abs': [-0.2, 0.4, -0.2, 0.6],
'trade_duration': [10, 30, 10, 10],
'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.STOP_LOSS, SellType.ROI],
'close_date':
[
datetime(2019, 1, 1, 9, 26, 3, 478039),
datetime(2019, 2, 1, 9, 26, 3, 478039),
datetime(2019, 3, 1, 9, 26, 3, 478039)
datetime(2019, 3, 1, 9, 26, 3, 478039),
datetime(2019, 4, 1, 9, 26, 3, 478039),
]
}
)

92
tests/optimize/test_hyperoptloss.py
View File

@ -35,6 +35,7 @@ def test_hyperoptlossresolver_wrongname(default_conf) -> None:
def test_loss_calculation_prefer_correct_trade_count(hyperopt_conf, hyperopt_results) -> None:
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))
@ -50,6 +51,7 @@ def test_loss_calculation_prefer_shorter_trades(hyperopt_conf, hyperopt_results)
resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20
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))
@ -64,6 +66,7 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
results_under = hyperopt_results.copy()
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
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))
@ -75,91 +78,28 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
assert under > correct
def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sortino_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
default_conf.update({'hyperopt_loss': 'SortinoHyperOptLoss'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
default_conf.update({'hyperopt_loss': 'SortinoHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
@pytest.mark.parametrize('lossfunction', [
"OnlyProfitHyperOptLoss",
"SortinoHyperOptLoss",
"SortinoHyperOptLossDaily",
"SharpeHyperOptLoss",
"SharpeHyperOptLossDaily",
])
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
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
default_conf.update({'hyperopt_loss': lossfunction})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
over = hl.hyperopt_loss_function(results_over, len(results_over),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
under = hl.hyperopt_loss_function(results_under, len(results_under),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct