9394559170

Committed 26 Apr 2024 06:36AM UTC coverage: 94.656% (-0.02%) from 94.674%

Build # 9394559170

Build Type

push

github

Committed by

xmatthias

Commit Message

Loader should be passed as kwarg for clarity

Run Details

20280 of 21425 relevant lines covered (94.66%)

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98.31

/freqtrade/optimize/hyperopt_epoch_filters.py

import logging
from typing import List

from freqtrade.exceptions import OperationalException


logger = logging.getLogger(__name__)


def hyperopt_filter_epochs(epochs: List, filteroptions: dict, log: bool = True) -> List:
    """
    Filter our items from the list of hyperopt results
    """
    if filteroptions['only_best']:
        epochs = [x for x in epochs if x['is_best']]
    if filteroptions['only_profitable']:
        epochs = [x for x in epochs
                  if x['results_metrics'].get('profit_total', 0) > 0]

    epochs = _hyperopt_filter_epochs_trade_count(epochs, filteroptions)

    epochs = _hyperopt_filter_epochs_duration(epochs, filteroptions)

    epochs = _hyperopt_filter_epochs_profit(epochs, filteroptions)

    epochs = _hyperopt_filter_epochs_objective(epochs, filteroptions)
    if log:
        logger.info(f"{len(epochs)} " +
                    ("best " if filteroptions['only_best'] else "") +
                    ("profitable " if filteroptions['only_profitable'] else "") +
                    "epochs found.")
    return epochs


def _hyperopt_filter_epochs_trade(epochs: List, trade_count: int):
    """
    Filter epochs with trade-counts > trades
    """
    return [
        x for x in epochs if x['results_metrics'].get('total_trades', 0) > trade_count
    ]


def _hyperopt_filter_epochs_trade_count(epochs: List, filteroptions: dict) -> List:

    if filteroptions['filter_min_trades'] > 0:
        epochs = _hyperopt_filter_epochs_trade(epochs, filteroptions['filter_min_trades'])

    if filteroptions['filter_max_trades'] > 0:
        epochs = [
            x for x in epochs
            if x['results_metrics'].get('total_trades') < filteroptions['filter_max_trades']
        ]
    return epochs


def _hyperopt_filter_epochs_duration(epochs: List, filteroptions: dict) -> List:

    def get_duration_value(x):
        # Duration in minutes ...
        if 'holding_avg_s' in x['results_metrics']:
            avg = x['results_metrics']['holding_avg_s']
            return avg // 60
        raise OperationalException(
            "Holding-average not available. Please omit the filter on average time, "
            "or rerun hyperopt with this version")

    if filteroptions['filter_min_avg_time'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)
        epochs = [
            x for x in epochs
            if get_duration_value(x) > filteroptions['filter_min_avg_time']
        ]
    if filteroptions['filter_max_avg_time'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)
        epochs = [
            x for x in epochs
            if get_duration_value(x) < filteroptions['filter_max_avg_time']
        ]

    return epochs


def _hyperopt_filter_epochs_profit(epochs: List, filteroptions: dict) -> List:

    if filteroptions['filter_min_avg_profit'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)
        epochs = [
            x for x in epochs
            if x['results_metrics'].get('profit_mean', 0) * 100
            > filteroptions['filter_min_avg_profit']
        ]
    if filteroptions['filter_max_avg_profit'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)
        epochs = [
            x for x in epochs
            if x['results_metrics'].get('profit_mean', 0) * 100
            < filteroptions['filter_max_avg_profit']
        ]
    if filteroptions['filter_min_total_profit'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)
        epochs = [
            x for x in epochs
            if x['results_metrics'].get('profit_total_abs', 0)
            > filteroptions['filter_min_total_profit']
        ]
    if filteroptions['filter_max_total_profit'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)
        epochs = [
            x for x in epochs
            if x['results_metrics'].get('profit_total_abs', 0)
            < filteroptions['filter_max_total_profit']
        ]
    return epochs


def _hyperopt_filter_epochs_objective(epochs: List, filteroptions: dict) -> List:

    if filteroptions['filter_min_objective'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)

        epochs = [x for x in epochs if x['loss'] < filteroptions['filter_min_objective']]
    if filteroptions['filter_max_objective'] is not None:
        epochs = _hyperopt_filter_epochs_trade(epochs, 0)

        epochs = [x for x in epochs if x['loss'] > filteroptions['filter_max_objective']]

    return epochs

1	import logging	1✔
2	from typing import List	1✔
3
4	from freqtrade.exceptions import OperationalException	1✔
5
6
7	logger = logging.getLogger(__name__)	1✔
8
9
10	def hyperopt_filter_epochs(epochs: List, filteroptions: dict, log: bool = True) -> List:	1✔
11	"""
12	Filter our items from the list of hyperopt results
13	"""
14	if filteroptions['only_best']:	1✔
15	epochs = [x for x in epochs if x['is_best']]	1✔
16	if filteroptions['only_profitable']:	1✔
17	epochs = [x for x in epochs	1✔
18	if x['results_metrics'].get('profit_total', 0) > 0]
19
20	epochs = _hyperopt_filter_epochs_trade_count(epochs, filteroptions)	1✔
21
22	epochs = _hyperopt_filter_epochs_duration(epochs, filteroptions)	1✔
23
24	epochs = _hyperopt_filter_epochs_profit(epochs, filteroptions)	1✔
25
26	epochs = _hyperopt_filter_epochs_objective(epochs, filteroptions)	1✔
27	if log:	1✔
28	logger.info(f"{len(epochs)} " +	1✔
29	("best " if filteroptions['only_best'] else "") +
30	("profitable " if filteroptions['only_profitable'] else "") +
31	"epochs found.")
32	return epochs	1✔
33
34
35	def _hyperopt_filter_epochs_trade(epochs: List, trade_count: int):	1✔
36	"""
37	Filter epochs with trade-counts > trades
38	"""
39	return [	1✔
40	x for x in epochs if x['results_metrics'].get('total_trades', 0) > trade_count
41	]
42
43
44	def _hyperopt_filter_epochs_trade_count(epochs: List, filteroptions: dict) -> List:	1✔
45
46	if filteroptions['filter_min_trades'] > 0:	1✔
47	epochs = _hyperopt_filter_epochs_trade(epochs, filteroptions['filter_min_trades'])	1✔
48
49	if filteroptions['filter_max_trades'] > 0:	1✔
50	epochs = [	1✔
51	x for x in epochs
52	if x['results_metrics'].get('total_trades') < filteroptions['filter_max_trades']
53	]
54	return epochs	1✔
55
56
57	def _hyperopt_filter_epochs_duration(epochs: List, filteroptions: dict) -> List:	1✔
58
59	def get_duration_value(x):	1✔
60	# Duration in minutes ...
61	if 'holding_avg_s' in x['results_metrics']:	1✔
62	avg = x['results_metrics']['holding_avg_s']	1✔
63	return avg // 60	1✔
64	raise OperationalException(	×
65	"Holding-average not available. Please omit the filter on average time, "
66	"or rerun hyperopt with this version")
67
68	if filteroptions['filter_min_avg_time'] is not None:	1✔
69	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
70	epochs = [	1✔
71	x for x in epochs
72	if get_duration_value(x) > filteroptions['filter_min_avg_time']
73	]
74	if filteroptions['filter_max_avg_time'] is not None:	1✔
75	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
76	epochs = [	1✔
77	x for x in epochs
78	if get_duration_value(x) < filteroptions['filter_max_avg_time']
79	]
80
81	return epochs	1✔
82
83
84	def _hyperopt_filter_epochs_profit(epochs: List, filteroptions: dict) -> List:	1✔
85
86	if filteroptions['filter_min_avg_profit'] is not None:	1✔
87	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
88	epochs = [	1✔
89	x for x in epochs
90	if x['results_metrics'].get('profit_mean', 0) * 100
91	> filteroptions['filter_min_avg_profit']
92	]
93	if filteroptions['filter_max_avg_profit'] is not None:	1✔
94	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
95	epochs = [	1✔
96	x for x in epochs
97	if x['results_metrics'].get('profit_mean', 0) * 100
98	< filteroptions['filter_max_avg_profit']
99	]
100	if filteroptions['filter_min_total_profit'] is not None:	1✔
101	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
102	epochs = [	1✔
103	x for x in epochs
104	if x['results_metrics'].get('profit_total_abs', 0)
105	> filteroptions['filter_min_total_profit']
106	]
107	if filteroptions['filter_max_total_profit'] is not None:	1✔
108	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
109	epochs = [	1✔
110	x for x in epochs
111	if x['results_metrics'].get('profit_total_abs', 0)
112	< filteroptions['filter_max_total_profit']
113	]
114	return epochs	1✔
115
116
117	def _hyperopt_filter_epochs_objective(epochs: List, filteroptions: dict) -> List:	1✔
118
119	if filteroptions['filter_min_objective'] is not None:	1✔
120	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
121
122	epochs = [x for x in epochs if x['loss'] < filteroptions['filter_min_objective']]	1✔
123	if filteroptions['filter_max_objective'] is not None:	1✔
124	epochs = _hyperopt_filter_epochs_trade(epochs, 0)	1✔
125
126	epochs = [x for x in epochs if x['loss'] > filteroptions['filter_max_objective']]	1✔
127
128	return epochs	1✔

freqtrade / freqtrade / 9394559170

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