Print non-optimized parameters (also stop / roi)
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@@ -23,7 +23,7 @@ from pandas import DataFrame
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from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
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from freqtrade.data.converter import trim_dataframes
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from freqtrade.data.history import get_timerange
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from freqtrade.misc import file_dump_json, plural
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from freqtrade.misc import deep_merge_dicts, file_dump_json, plural
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from freqtrade.optimize.backtesting import Backtesting
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# Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
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from freqtrade.optimize.hyperopt_auto import HyperOptAuto
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@@ -201,6 +201,25 @@ class Hyperopt:
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return result
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def _get_no_optimize_details(self) -> Dict[str, Any]:
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"""
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Get non-optimized parameters
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"""
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result: Dict[str, Any] = {}
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strategy = self.backtesting.strategy
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if not HyperoptTools.has_space(self.config, 'roi'):
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result['roi'] = strategy.minimal_roi
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if not HyperoptTools.has_space(self.config, 'stoploss'):
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result['stoploss'] = strategy.stoploss
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if not HyperoptTools.has_space(self.config, 'trailing'):
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result['trailing'] = {
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'trailing_stop': strategy.trailing_stop,
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'trailing_stop_positive': strategy.trailing_stop_positive,
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'trailing_stop_positive_offset': strategy.trailing_stop_positive_offset,
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'trailing_only_offset_is_reached': strategy.trailing_only_offset_is_reached,
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}
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return result
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def print_results(self, results) -> None:
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"""
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Log results if it is better than any previous evaluation
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@@ -311,6 +330,7 @@ class Hyperopt:
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strat_stats, self.config['stake_currency'])
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not_optimized = self.backtesting.strategy.get_no_optimize_params()
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not_optimized = deep_merge_dicts(not_optimized, self._get_no_optimize_details())
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trade_count = strat_stats['total_trades']
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total_profit = strat_stats['profit_total']
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