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Creating fake column for legacy mode on max drawdown

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This commit is contained in:
Bruno Gouvea 2021-06-08 02:42:55 -03:00
parent 4595db39aa
commit 816bb531b3
1 changed files with 14 additions and 8 deletions
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18
freqtrade/optimize/hyperopt_tools.py
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@ -222,6 +222,11 @@ class HyperoptTools():
# Ensure compatibility with older versions of hyperopt results
trials['results_metrics.winsdrawslosses'] = 'N/A'
if 'results_metrics.max_drawdown_abs' not in trials.columns:
# Ensure compatibility with older versions of hyperopt results
trials['results_metrics.max_drawdown_abs'] = None
trials['results_metrics.max_drawdown'] = None
legacy_mode = True
if 'results_metrics.total_trades' in trials:
@ -237,20 +242,18 @@ class HyperoptTools():
'results_metrics.max_drawdown', 'results_metrics.max_drawdown_abs',
'loss', 'is_initial_point', 'is_best']]
trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
'Total profit', 'Profit', 'Avg duration', 'Max Drawdown',
'max_drawdown_abs', 'Objective', 'is_initial_point', 'is_best']
else:
# Legacy mode
trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count',
'results_metrics.winsdrawslosses', 'results_metrics.avg_profit',
'results_metrics.total_profit', 'results_metrics.profit',
'results_metrics.duration', 'loss', 'is_initial_point',
'results_metrics.duration', 'results_metrics.max_drawdown',
'results_metrics.max_drawdown_abs', 'loss', 'is_initial_point',
'is_best']]
trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
'Total profit', 'Profit', 'Avg duration', 'Objective',
'is_initial_point', 'is_best']
'Total profit', 'Profit', 'Avg duration', 'Max Drawdown',
'max_drawdown_abs', 'Objective', 'is_initial_point', 'is_best']
trials['is_profit'] = False
trials.loc[trials['is_initial_point'], 'Best'] = '* '
@ -284,6 +287,9 @@ class HyperoptTools():
if x['Max Drawdown'] != 0.0 else '--'.rjust(25 + len(stake_currency)),
axis=1
)
else:
trials = trials.drop(columns=['Max Drawdown'])
trials = trials.drop(columns=['max_drawdown_abs'])
trials['Profit'] = trials.apply(