Add --analyze-per-epoch - moving populate_analysis to the epoch process
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Matthias
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09f8904545
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bc359675a2
@ -40,7 +40,8 @@ pip install -r requirements-hyperopt.txt
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```
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usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
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[--userdir PATH] [-s NAME] [--strategy-path PATH]
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[--recursive-strategy-search] [-i TIMEFRAME]
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[--recursive-strategy-search] [--freqaimodel NAME]
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[--freqaimodel-path PATH] [-i TIMEFRAME]
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[--timerange TIMERANGE]
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[--data-format-ohlcv {json,jsongz,hdf5}]
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[--max-open-trades INT]
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@ -53,7 +54,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
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[--print-all] [--no-color] [--print-json] [-j JOBS]
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[--random-state INT] [--min-trades INT]
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[--hyperopt-loss NAME] [--disable-param-export]
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[--ignore-missing-spaces]
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[--ignore-missing-spaces] [--analyze-per-epoch]
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optional arguments:
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-h, --help show this help message and exit
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@ -129,6 +130,7 @@ optional arguments:
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--ignore-missing-spaces, --ignore-unparameterized-spaces
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Suppress errors for any requested Hyperopt spaces that
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do not contain any parameters.
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--analyze-per-epoch Run populate_indicators once per epoch.
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Common arguments:
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-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
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@ -154,6 +156,10 @@ Strategy arguments:
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--recursive-strategy-search
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Recursively search for a strategy in the strategies
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folder.
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--freqaimodel NAME Specify a custom freqaimodels.
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--freqaimodel-path PATH
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Specify additional lookup path for freqaimodels.
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```
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### Hyperopt checklist
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@ -34,7 +34,7 @@ ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
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"print_colorized", "print_json", "hyperopt_jobs",
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"hyperopt_random_state", "hyperopt_min_trades",
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"hyperopt_loss", "disableparamexport",
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"hyperopt_ignore_missing_space"]
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"hyperopt_ignore_missing_space", "analyze_per_epoch"]
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ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
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@ -255,6 +255,13 @@ AVAILABLE_CLI_OPTIONS = {
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nargs='+',
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default='default',
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),
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"analyze_per_epoch": Arg(
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'--analyze-per-epoch',
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help='Run populate_indicators once per epoch.',
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action='store_true',
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default=False,
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),
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"print_all": Arg(
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'--print-all',
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help='Print all results, not only the best ones.',
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@ -302,6 +302,9 @@ class Configuration:
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self._args_to_config(config, argname='spaces',
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logstring='Parameter -s/--spaces detected: {}')
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self._args_to_config(config, argname='analyze_per_epoch',
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logstring='Parameter --analyze-per-epoch detected.')
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self._args_to_config(config, argname='print_all',
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logstring='Parameter --print-all detected ...')
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@ -24,13 +24,15 @@ from pandas import DataFrame
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from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, 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.enums import HyperoptState
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from freqtrade.exceptions import OperationalException
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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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from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
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from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
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from freqtrade.optimize.hyperopt_tools import (HyperoptStateContainer, HyperoptTools,
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hyperopt_serializer)
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from freqtrade.optimize.optimize_reports import generate_strategy_stats
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from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
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@ -74,10 +76,14 @@ class Hyperopt:
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self.dimensions: List[Dimension] = []
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self.config = config
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self.min_date: datetime
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self.max_date: datetime
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self.backtesting = Backtesting(self.config)
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self.pairlist = self.backtesting.pairlists.whitelist
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self.custom_hyperopt: HyperOptAuto
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self.analyze_per_epoch = self.config.get('analyze_per_epoch', False)
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HyperoptStateContainer.set_state(HyperoptState.STARTUP)
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if not self.config.get('hyperopt'):
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self.custom_hyperopt = HyperOptAuto(self.config)
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@ -290,6 +296,7 @@ class Hyperopt:
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Called once per epoch to optimize whatever is configured.
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Keep this function as optimized as possible!
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"""
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HyperoptStateContainer.set_state(HyperoptState.OPTIMIZE)
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backtest_start_time = datetime.now(timezone.utc)
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params_dict = self._get_params_dict(self.dimensions, raw_params)
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@ -321,6 +328,10 @@ class Hyperopt:
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with self.data_pickle_file.open('rb') as f:
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processed = load(f, mmap_mode='r')
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if self.analyze_per_epoch:
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# Data is not yet analyzed, rerun populate_indicators.
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processed = self.advise_and_trim(processed)
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bt_results = self.backtesting.backtest(
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processed=processed,
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start_date=self.min_date,
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@ -415,19 +426,24 @@ class Hyperopt:
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return processed
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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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HyperoptStateContainer.set_state(HyperoptState.DATALOAD)
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data, self.timerange = self.backtesting.load_bt_data()
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self.backtesting.load_bt_data_detail()
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logger.info("Dataload complete. Calculating indicators")
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preprocessed = self.backtesting.strategy.advise_all_indicators(data)
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if not self.analyze_per_epoch:
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HyperoptStateContainer.set_state(HyperoptState.INDICATORS)
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preprocessed = self.advise_and_trim(data)
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preprocessed = self.advise_and_trim(data)
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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'({(self.max_date - self.min_date).days} days)..')
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# Store non-trimmed data - will be trimmed after signal generation.
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dump(preprocessed, self.data_pickle_file)
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logger.info(f'Hyperopting with data from '
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f'{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'({(self.max_date - self.min_date).days} days)..')
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# Store non-trimmed data - will be trimmed after signal generation.
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dump(preprocessed, self.data_pickle_file)
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else:
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dump(data, self.data_pickle_file)
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def get_asked_points(self, n_points: int) -> Tuple[List[List[Any]], List[bool]]:
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"""
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@ -7,6 +7,9 @@ from abc import ABC, abstractmethod
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from contextlib import suppress
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from typing import Any, Optional, Sequence, Union
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from freqtrade.enums.hyperoptstate import HyperoptState
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from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer
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with suppress(ImportError):
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from skopt.space import Integer, Real, Categorical
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@ -61,6 +64,7 @@ class BaseParameter(ABC):
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return (
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self.in_space
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and self.optimize
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and HyperoptStateContainer.state != HyperoptState.OPTIMIZE
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)
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