Refactor Hyperopt-list and hyperopt-show to reduce some duplicate code
This commit is contained in:
Matthias
parent
7eaadb2630
commit
0ae4eccea5
@ -1,6 +1,6 @@
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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 typing import Any, Dict
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from colorama import init as colorama_init
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@ -28,30 +28,12 @@ def start_hyperopt_list(args: Dict[str, Any]) -> 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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epochs, total_epochs = HyperoptTools.load_filtered_results(results_file, config)
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if print_colorized:
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colorama_init(autoreset=True)
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@ -59,7 +41,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
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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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not config.get('hyperopt_list_best', False),
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print_colorized, 0))
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except KeyboardInterrupt:
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print('User interrupted..')
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@ -71,7 +53,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
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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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config, epochs, total_epochs, not config.get('hyperopt_list_best', False), export_csv
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)
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@ -91,26 +73,9 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
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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, total_epochs = HyperoptTools.load_filtered_results(results_file, config)
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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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@ -137,138 +102,3 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
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HyperoptTools.show_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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TODO: after 2021.5 remove all "legacy" mode queries.
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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'].get(
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'profit', x['results_metrics'].get('profit_total', 0)) > 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(epochs: List, trade_count: int):
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"""
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Filter epochs with trade-counts > trades
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"""
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return [
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x for x in epochs
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if x['results_metrics'].get(
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'trade_count', x['results_metrics'].get('total_trades', 0)
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) > trade_count
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]
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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 = _hyperopt_filter_epochs_trade(epochs, filteroptions['filter_min_trades'])
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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'].get(
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'trade_count', x['results_metrics'].get('total_trades')
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) < 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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def get_duration_value(x):
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# Duration in minutes ...
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if 'duration' in x['results_metrics']:
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return x['results_metrics']['duration']
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else:
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# New mode
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if 'holding_avg_s' in x['results_metrics']:
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avg = x['results_metrics']['holding_avg_s']
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return avg // 60
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raise OperationalException(
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"Holding-average not available. Please omit the filter on average time, "
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"or rerun hyperopt with this version")
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if filteroptions['filter_min_avg_time'] is not None:
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epochs = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if get_duration_value(x) > 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if get_duration_value(x) < 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'avg_profit', x['results_metrics'].get('profit_mean', 0) * 100
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) > 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'avg_profit', x['results_metrics'].get('profit_mean', 0) * 100
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) < 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'profit', x['results_metrics'].get('profit_total_abs', 0)
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) > 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'profit', x['results_metrics'].get('profit_total_abs', 0)
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) < 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 = _hyperopt_filter_epochs_trade(epochs, 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 = _hyperopt_filter_epochs_trade(epochs, 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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142
freqtrade/optimize/hyperopt_epoch_filters.py
Normal file
142
freqtrade/optimize/hyperopt_epoch_filters.py
Normal file
@ -0,0 +1,142 @@
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import logging
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from typing import List
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from freqtrade.exceptions import OperationalException
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logger = logging.getLogger(__name__)
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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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TODO: after 2021.5 remove all "legacy" mode queries.
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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'].get(
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'profit', x['results_metrics'].get('profit_total', 0)) > 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(epochs: List, trade_count: int):
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"""
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Filter epochs with trade-counts > trades
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"""
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return [
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x for x in epochs
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if x['results_metrics'].get(
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'trade_count', x['results_metrics'].get('total_trades', 0)
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) > trade_count
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]
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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 = _hyperopt_filter_epochs_trade(epochs, filteroptions['filter_min_trades'])
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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'].get(
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'trade_count', x['results_metrics'].get('total_trades')
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) < 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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def get_duration_value(x):
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# Duration in minutes ...
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if 'duration' in x['results_metrics']:
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return x['results_metrics']['duration']
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else:
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# New mode
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if 'holding_avg_s' in x['results_metrics']:
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avg = x['results_metrics']['holding_avg_s']
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return avg // 60
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raise OperationalException(
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"Holding-average not available. Please omit the filter on average time, "
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"or rerun hyperopt with this version")
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if filteroptions['filter_min_avg_time'] is not None:
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epochs = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if get_duration_value(x) > 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if get_duration_value(x) < 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'avg_profit', x['results_metrics'].get('profit_mean', 0) * 100
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) > 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'avg_profit', x['results_metrics'].get('profit_mean', 0) * 100
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) < 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'profit', x['results_metrics'].get('profit_total_abs', 0)
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) > 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 = _hyperopt_filter_epochs_trade(epochs, 0)
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epochs = [
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x for x in epochs
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if x['results_metrics'].get(
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'profit', x['results_metrics'].get('profit_total_abs', 0)
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) < 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 = _hyperopt_filter_epochs_trade(epochs, 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 = _hyperopt_filter_epochs_trade(epochs, 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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@ -4,7 +4,7 @@ import logging
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from copy import deepcopy
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from typing import Any, Dict, List, Optional, Tuple
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import numpy as np
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import rapidjson
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@ -15,6 +15,7 @@ from pandas import isna, json_normalize
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from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES
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from freqtrade.exceptions import OperationalException
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from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2
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from freqtrade.optimize.hyperopt_epoch_filters import hyperopt_filter_epochs
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logger = logging.getLogger(__name__)
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@ -130,6 +131,31 @@ class HyperoptTools():
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logger.info(f"Loaded {len(epochs)} previous evaluations from disk.")
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return epochs
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@staticmethod
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def load_filtered_results(results_file: Path, config: Dict[str, Any]) -> Tuple[List, int]:
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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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return epochs, total_epochs
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@staticmethod
|
||||
def show_epoch_details(results, total_epochs: int, print_json: bool,
|
||||
no_header: bool = False, header_str: str = None) -> None:
|
||||
|
||||
Loading…
Reference in New Issue
Block a user