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Convert hyperoptloss resolver to static loader

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This commit is contained in:
Matthias
2019-12-23 10:09:08 +01:00
parent 248ef5a0ea
commit 6d5aca4f32
3 changed files with 22 additions and 20 deletions
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14
tests/optimize/test_hyperopt.py
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@@ -198,7 +198,7 @@ def test_hyperoptlossresolver(mocker, default_conf, caplog) -> None:
'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver._load_hyperoptloss',
MagicMock(return_value=hl)
)
x = HyperOptLossResolver(default_conf).hyperoptloss
x = HyperOptLossResolver.load_hyperoptloss(default_conf)
assert hasattr(x, "hyperopt_loss_function")
@@ -206,7 +206,7 @@ def test_hyperoptlossresolver_wrongname(mocker, default_conf, caplog) -> None:
default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'):
HyperOptLossResolver(default_conf).hyperopt
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_start_not_installed(mocker, default_conf, caplog, import_fails) -> None:
@@ -286,7 +286,7 @@ def test_start_filelock(mocker, default_conf, caplog) -> None:
def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None:
hl = HyperOptLossResolver(default_conf).hyperoptloss
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100)
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100)
@@ -298,7 +298,7 @@ def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results)
resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20
hl = HyperOptLossResolver(default_conf).hyperoptloss
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
longer = hl.hyperopt_loss_function(hyperopt_results, 100)
shorter = hl.hyperopt_loss_function(resultsb, 100)
assert shorter < longer
@@ -310,7 +310,7 @@ def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) ->
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
hl = HyperOptLossResolver(default_conf).hyperoptloss
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(results_over, 600)
under = hl.hyperopt_loss_function(results_under, 600)
@@ -325,7 +325,7 @@ def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> N
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
hl = HyperOptLossResolver(default_conf).hyperoptloss
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),
@@ -343,7 +343,7 @@ def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results)
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
hl = HyperOptLossResolver(default_conf).hyperoptloss
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),