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

Source File
Press 'n' to go to next uncovered line, 'b' for previous

82.35

/freqtrade/optimize/hyperopt_loss/hyperopt_loss_max_drawdown_relative.py

"""
MaxDrawDownRelativeHyperOptLoss

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

from freqtrade.constants import Config
from freqtrade.data.metrics import calculate_underwater
from freqtrade.optimize.hyperopt import IHyperOptLoss


class MaxDrawDownRelativeHyperOptLoss(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, config: Config,
                               *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:
            drawdown_df = calculate_underwater(
                results,
                value_col='profit_abs',
                starting_balance=config['dry_run_wallet']
            )
            max_drawdown = abs(min(drawdown_df['drawdown']))
            relative_drawdown = max(drawdown_df['drawdown_relative'])
            if max_drawdown == 0:
                return -total_profit
            return -total_profit / max_drawdown / relative_drawdown
        except (Exception, ValueError):
            return -total_profit

1	"""
2	MaxDrawDownRelativeHyperOptLoss
3
4	This module defines the alternative HyperOptLoss class which can be used for
5	Hyperoptimization.
6	"""
7	from pandas import DataFrame	1✔
8
9	from freqtrade.constants import Config	1✔
10	from freqtrade.data.metrics import calculate_underwater	1✔
11	from freqtrade.optimize.hyperopt import IHyperOptLoss	1✔
12
13
14	class MaxDrawDownRelativeHyperOptLoss(IHyperOptLoss):	1✔
15
16	"""
17	Defines the loss function for hyperopt.
18
19	This implementation optimizes for max draw down and profit
20	Less max drawdown more profit -> Lower return value
21	"""
22
23	@staticmethod	1✔
24	def hyperopt_loss_function(results: DataFrame, config: Config,	1✔
25	args, *kwargs) -> float:
26
27	"""
28	Objective function.
29
30	Uses profit ratio weighted max_drawdown when drawdown is available.
31	Otherwise directly optimizes profit ratio.
32	"""
33	total_profit = results['profit_abs'].sum()	1✔
34	try:	1✔
35	drawdown_df = calculate_underwater(	1✔
36	results,
37	value_col='profit_abs',
38	starting_balance=config['dry_run_wallet']
39	)
40	max_drawdown = abs(min(drawdown_df['drawdown']))	1✔
41	relative_drawdown = max(drawdown_df['drawdown_relative'])	1✔
42	if max_drawdown == 0:	1✔
43	return -total_profit	×
44	return -total_profit / max_drawdown / relative_drawdown	1✔
45	except (Exception, ValueError):	×
46	return -total_profit	×

freqtrade / freqtrade / 9394559170

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous