237 lines
9.2 KiB
Python
Executable File
237 lines
9.2 KiB
Python
Executable File
import logging
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from operator import itemgetter
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from typing import Any, Dict, List
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from colorama import init as colorama_init
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from freqtrade.configuration import setup_utils_configuration
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from freqtrade.data.btanalysis import get_latest_hyperopt_file
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from freqtrade.exceptions import OperationalException
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from freqtrade.optimize.optimize_reports import show_backtest_result
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from freqtrade.state import RunMode
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logger = logging.getLogger(__name__)
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def start_hyperopt_list(args: Dict[str, Any]) -> None:
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"""
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List hyperopt epochs previously evaluated
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"""
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from freqtrade.optimize.hyperopt_tools import HyperoptTools
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config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
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print_colorized = config.get('print_colorized', False)
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print_json = config.get('print_json', False)
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export_csv = config.get('export_csv', None)
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no_details = config.get('hyperopt_list_no_details', False)
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no_header = False
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filteroptions = {
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'only_best': config.get('hyperopt_list_best', False),
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'only_profitable': config.get('hyperopt_list_profitable', False),
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'filter_min_trades': config.get('hyperopt_list_min_trades', 0),
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'filter_max_trades': config.get('hyperopt_list_max_trades', 0),
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'filter_min_avg_time': config.get('hyperopt_list_min_avg_time', None),
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'filter_max_avg_time': config.get('hyperopt_list_max_avg_time', None),
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'filter_min_avg_profit': config.get('hyperopt_list_min_avg_profit', None),
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'filter_max_avg_profit': config.get('hyperopt_list_max_avg_profit', None),
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'filter_min_total_profit': config.get('hyperopt_list_min_total_profit', None),
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'filter_max_total_profit': config.get('hyperopt_list_max_total_profit', None),
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'filter_min_objective': config.get('hyperopt_list_min_objective', None),
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'filter_max_objective': config.get('hyperopt_list_max_objective', None),
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}
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results_file = get_latest_hyperopt_file(
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config['user_data_dir'] / 'hyperopt_results',
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config.get('hyperoptexportfilename'))
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# Previous evaluations
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epochs = HyperoptTools.load_previous_results(results_file)
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total_epochs = len(epochs)
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epochs = hyperopt_filter_epochs(epochs, filteroptions)
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if print_colorized:
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colorama_init(autoreset=True)
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if not export_csv:
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try:
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print(HyperoptTools.get_result_table(config, epochs, total_epochs,
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not filteroptions['only_best'],
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print_colorized, 0))
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except KeyboardInterrupt:
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print('User interrupted..')
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if epochs and not no_details:
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sorted_epochs = sorted(epochs, key=itemgetter('loss'))
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results = sorted_epochs[0]
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HyperoptTools.print_epoch_details(results, total_epochs, print_json, no_header)
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if epochs and export_csv:
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HyperoptTools.export_csv_file(
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config, epochs, total_epochs, not filteroptions['only_best'], export_csv
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)
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def start_hyperopt_show(args: Dict[str, Any]) -> None:
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"""
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Show details of a hyperopt epoch previously evaluated
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"""
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from freqtrade.optimize.hyperopt_tools import HyperoptTools
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config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
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print_json = config.get('print_json', False)
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no_header = config.get('hyperopt_show_no_header', False)
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results_file = get_latest_hyperopt_file(
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config['user_data_dir'] / 'hyperopt_results',
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config.get('hyperoptexportfilename'))
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n = config.get('hyperopt_show_index', -1)
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filteroptions = {
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'only_best': config.get('hyperopt_list_best', False),
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'only_profitable': config.get('hyperopt_list_profitable', False),
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'filter_min_trades': config.get('hyperopt_list_min_trades', 0),
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'filter_max_trades': config.get('hyperopt_list_max_trades', 0),
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'filter_min_avg_time': config.get('hyperopt_list_min_avg_time', None),
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'filter_max_avg_time': config.get('hyperopt_list_max_avg_time', None),
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'filter_min_avg_profit': config.get('hyperopt_list_min_avg_profit', None),
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'filter_max_avg_profit': config.get('hyperopt_list_max_avg_profit', None),
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'filter_min_total_profit': config.get('hyperopt_list_min_total_profit', None),
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'filter_max_total_profit': config.get('hyperopt_list_max_total_profit', None),
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'filter_min_objective': config.get('hyperopt_list_min_objective', None),
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'filter_max_objective': config.get('hyperopt_list_max_objective', None)
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}
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# Previous evaluations
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epochs = HyperoptTools.load_previous_results(results_file)
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total_epochs = len(epochs)
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epochs = hyperopt_filter_epochs(epochs, filteroptions)
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filtered_epochs = len(epochs)
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if n > filtered_epochs:
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raise OperationalException(
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f"The index of the epoch to show should be less than {filtered_epochs + 1}.")
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if n < -filtered_epochs:
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raise OperationalException(
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f"The index of the epoch to show should be greater than {-filtered_epochs - 1}.")
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# Translate epoch index from human-readable format to pythonic
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if n > 0:
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n -= 1
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if epochs:
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val = epochs[n]
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metrics = val['results_metrics']
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if 'strategy_name' in metrics:
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show_backtest_result(metrics['strategy_name'], metrics,
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metrics['stake_currency'])
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HyperoptTools.print_epoch_details(val, total_epochs, print_json, no_header,
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header_str="Epoch details")
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def hyperopt_filter_epochs(epochs: List, filteroptions: dict) -> List:
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"""
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Filter our items from the list of hyperopt results
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"""
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if filteroptions['only_best']:
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epochs = [x for x in epochs if x['is_best']]
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if filteroptions['only_profitable']:
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epochs = [x for x in epochs if x['results_metrics']['profit'] > 0]
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epochs = _hyperopt_filter_epochs_trade_count(epochs, filteroptions)
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epochs = _hyperopt_filter_epochs_duration(epochs, filteroptions)
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epochs = _hyperopt_filter_epochs_profit(epochs, filteroptions)
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epochs = _hyperopt_filter_epochs_objective(epochs, filteroptions)
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logger.info(f"{len(epochs)} " +
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("best " if filteroptions['only_best'] else "") +
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("profitable " if filteroptions['only_profitable'] else "") +
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"epochs found.")
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return epochs
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def _hyperopt_filter_epochs_trade_count(epochs: List, filteroptions: dict) -> List:
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if filteroptions['filter_min_trades'] > 0:
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epochs = [
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x for x in epochs
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if x['results_metrics']['trade_count'] > filteroptions['filter_min_trades']
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]
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if filteroptions['filter_max_trades'] > 0:
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epochs = [
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x for x in epochs
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if x['results_metrics']['trade_count'] < filteroptions['filter_max_trades']
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]
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return epochs
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def _hyperopt_filter_epochs_duration(epochs: List, filteroptions: dict) -> List:
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if filteroptions['filter_min_avg_time'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [
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x for x in epochs
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if x['results_metrics']['duration'] > filteroptions['filter_min_avg_time']
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]
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if filteroptions['filter_max_avg_time'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [
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x for x in epochs
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if x['results_metrics']['duration'] < filteroptions['filter_max_avg_time']
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]
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return epochs
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def _hyperopt_filter_epochs_profit(epochs: List, filteroptions: dict) -> List:
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if filteroptions['filter_min_avg_profit'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [
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x for x in epochs
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if x['results_metrics']['avg_profit'] > filteroptions['filter_min_avg_profit']
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]
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if filteroptions['filter_max_avg_profit'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [
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x for x in epochs
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if x['results_metrics']['avg_profit'] < filteroptions['filter_max_avg_profit']
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]
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if filteroptions['filter_min_total_profit'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [
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x for x in epochs
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if x['results_metrics']['profit'] > filteroptions['filter_min_total_profit']
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]
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if filteroptions['filter_max_total_profit'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [
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x for x in epochs
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if x['results_metrics']['profit'] < filteroptions['filter_max_total_profit']
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]
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return epochs
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def _hyperopt_filter_epochs_objective(epochs: List, filteroptions: dict) -> List:
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if filteroptions['filter_min_objective'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [x for x in epochs if x['loss'] < filteroptions['filter_min_objective']]
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if filteroptions['filter_max_objective'] is not None:
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epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
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epochs = [x for x in epochs if x['loss'] > filteroptions['filter_max_objective']]
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return epochs
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