Extract analysis to separate method
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@ -406,6 +406,14 @@ class Hyperopt:
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def _set_random_state(self, random_state: Optional[int]) -> int:
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def _set_random_state(self, random_state: Optional[int]) -> int:
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return random_state or random.randint(1, 2**16 - 1)
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return random_state or random.randint(1, 2**16 - 1)
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def advise_and_trim(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
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preprocessed = self.backtesting.strategy.advise_all_indicators(data)
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# Trim startup period from analyzed dataframe to get correct dates for output.
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processed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup)
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self.min_date, self.max_date = get_timerange(processed)
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return processed
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def prepare_hyperopt_data(self) -> None:
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def prepare_hyperopt_data(self) -> None:
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data, timerange = self.backtesting.load_bt_data()
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data, timerange = self.backtesting.load_bt_data()
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self.backtesting.load_bt_data_detail()
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self.backtesting.load_bt_data_detail()
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@ -413,9 +421,7 @@ class Hyperopt:
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preprocessed = self.backtesting.strategy.advise_all_indicators(data)
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preprocessed = self.backtesting.strategy.advise_all_indicators(data)
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# Trim startup period from analyzed dataframe to get correct dates for output.
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preprocessed = self.advise_and_trim(data)
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processed = trim_dataframes(preprocessed, timerange, self.backtesting.required_startup)
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self.min_date, self.max_date = get_timerange(processed)
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logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} '
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logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} '
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f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} '
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f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} '
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