stable/freqtrade/commands/hyperopt_commands.py
2020-03-11 22:30:36 +01:00

185 lines
7.3 KiB
Python
Executable File

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