add search space for ROI table
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0b24fb50c0
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@ -225,11 +225,22 @@ def calculate_loss(total_profit: float, trade_count: int, trade_duration: float)
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return trade_loss + profit_loss + duration_loss
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def hyperopt_space() -> List[Dict]:
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def roi_space() -> List[Dict]:
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return {
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'roi_t1': hp.quniform('roi_t1', 10, 220, 10),
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'roi_t2': hp.quniform('roi_t2', 10, 120, 10),
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'roi_t3': hp.quniform('roi_t3', 10, 120, 10),
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'roi_p1': hp.quniform('roi_p1', 1, 5, 1),
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'roi_p2': hp.quniform('roi_p2', 1, 5, 1),
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'roi_p3': hp.quniform('roi_p3', 1, 10, 1),
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}
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def indicator_space() -> List[Dict]:
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"""
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Define your Hyperopt space for searching strategy parameters
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"""
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space = {
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return {
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'macd_below_zero': hp.choice('macd_below_zero', [
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{'enabled': False},
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{'enabled': True}
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@ -284,7 +295,10 @@ def hyperopt_space() -> List[Dict]:
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]),
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'stoploss': hp.uniform('stoploss', -0.5, -0.02),
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}
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return space
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def hyperopt_space() -> List[Dict]:
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return {**indicator_space(), **roi_space()}
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def buy_strategy_generator(params) -> None:
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@ -125,6 +125,12 @@ def test_fmin_best_results(mocker, caplog):
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"uptrend_short_ema": 0,
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"uptrend_sma": 0,
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"stoploss": -0.1,
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"roi_t1": 1,
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"roi_t2": 2,
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"roi_t3": 3,
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"roi_p1": 1,
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"roi_p2": 2,
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"roi_p3": 3,
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}
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mocker.patch('freqtrade.optimize.hyperopt.MongoTrials', return_value=create_trials(mocker))
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