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%)

0.95 hits per line

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84.62

/freqtrade/optimize/hyperopt_loss/hyperopt_loss_max_drawdown.py

"""
MaxDrawDownHyperOptLoss

This module defines the alternative HyperOptLoss class which can be used for
Hyperoptimization.
"""
from datetime import datetime

from pandas import DataFrame

from freqtrade.data.metrics import calculate_max_drawdown
from freqtrade.optimize.hyperopt import IHyperOptLoss


class MaxDrawDownHyperOptLoss(IHyperOptLoss):

    """
    Defines the loss function for hyperopt.

    This implementation optimizes for max draw down and profit
    Less max drawdown more profit -> Lower return value
    """

    @staticmethod
    def hyperopt_loss_function(results: DataFrame, trade_count: int,
                               min_date: datetime, max_date: datetime,
                               *args, **kwargs) -> float:

        """
        Objective function.

        Uses profit ratio weighted max_drawdown when drawdown is available.
        Otherwise directly optimizes profit ratio.
        """
        total_profit = results['profit_abs'].sum()
        try:
            max_drawdown = calculate_max_drawdown(results, value_col='profit_abs')
        except ValueError:
            # No losing trade, therefore no drawdown.
            return -total_profit
        return -total_profit / max_drawdown[0]

1	"""
2	MaxDrawDownHyperOptLoss
3
4	This module defines the alternative HyperOptLoss class which can be used for
5	Hyperoptimization.
6	"""
7	from datetime import datetime	1✔
8
9	from pandas import DataFrame	1✔
10
11	from freqtrade.data.metrics import calculate_max_drawdown	1✔
12	from freqtrade.optimize.hyperopt import IHyperOptLoss	1✔
13
14
15	class MaxDrawDownHyperOptLoss(IHyperOptLoss):	1✔
16
17	"""
18	Defines the loss function for hyperopt.
19
20	This implementation optimizes for max draw down and profit
21	Less max drawdown more profit -> Lower return value
22	"""
23
24	@staticmethod	1✔
25	def hyperopt_loss_function(results: DataFrame, trade_count: int,	1✔
26	min_date: datetime, max_date: datetime,
27	args, *kwargs) -> float:
28
29	"""
30	Objective function.
31
32	Uses profit ratio weighted max_drawdown when drawdown is available.
33	Otherwise directly optimizes profit ratio.
34	"""
35	total_profit = results['profit_abs'].sum()	1✔
36	try:	1✔
37	max_drawdown = calculate_max_drawdown(results, value_col='profit_abs')	1✔
38	except ValueError:	×
39	# No losing trade, therefore no drawdown.
40	return -total_profit	×
41	return -total_profit / max_drawdown[0]	1✔

freqtrade / freqtrade / 9394559170

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