80 lines
2.3 KiB
Python
80 lines
2.3 KiB
Python
# pragma pylint: disable=missing-docstring,W0212,C0103
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from freqtrade.optimize.hyperopt import calculate_loss, TARGET_TRADES, EXPECTED_MAX_PROFIT, start, \
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log_results
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def test_loss_calculation_prefer_correct_trade_count():
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correct = calculate_loss(1, TARGET_TRADES)
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over = calculate_loss(1, TARGET_TRADES + 100)
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under = calculate_loss(1, TARGET_TRADES - 100)
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assert over > correct
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assert under > correct
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def test_loss_calculation_has_limited_profit():
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correct = calculate_loss(EXPECTED_MAX_PROFIT, TARGET_TRADES)
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over = calculate_loss(EXPECTED_MAX_PROFIT * 2, TARGET_TRADES)
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under = calculate_loss(EXPECTED_MAX_PROFIT / 2, TARGET_TRADES)
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assert over == correct
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assert under > correct
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def create_trials(mocker):
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return mocker.Mock(
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results=[{
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'loss': 1,
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'result': 'foo'
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}]
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)
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def test_start_calls_fmin(mocker):
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mocker.patch('freqtrade.optimize.hyperopt.Trials', return_value=create_trials(mocker))
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mocker.patch('freqtrade.optimize.preprocess')
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mocker.patch('freqtrade.optimize.load_data')
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mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
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args = mocker.Mock(epochs=1, config='config.json.example', mongodb=False)
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start(args)
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mock_fmin.assert_called_once()
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def test_start_uses_mongotrials(mocker):
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mock_mongotrials = mocker.patch('freqtrade.optimize.hyperopt.MongoTrials',
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return_value=create_trials(mocker))
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mocker.patch('freqtrade.optimize.preprocess')
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mocker.patch('freqtrade.optimize.load_data')
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mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
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args = mocker.Mock(epochs=1, config='config.json.example', mongodb=True)
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start(args)
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mock_mongotrials.assert_called_once()
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def test_log_results_if_loss_improves(mocker):
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logger = mocker.patch('freqtrade.optimize.hyperopt.logger.info')
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global CURRENT_BEST_LOSS
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CURRENT_BEST_LOSS = 2
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log_results({
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'loss': 1,
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'current_tries': 1,
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'total_tries': 2,
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'result': 'foo'
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})
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logger.assert_called_once()
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def test_no_log_if_loss_does_not_improve(mocker):
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logger = mocker.patch('freqtrade.optimize.hyperopt.logger.info')
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global CURRENT_BEST_LOSS
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CURRENT_BEST_LOSS = 2
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log_results({
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'loss': 3,
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})
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assert not logger.called
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