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Fix output of % for new format

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This commit is contained in:
Matthias 2021-05-01 13:32:53 +02:00
parent 881cba336a
commit ecdfb6e5ed
1 changed files with 6 additions and 4 deletions
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10
freqtrade/optimize/hyperopt_tools.py
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@ -157,7 +157,7 @@ class HyperoptTools():
f"Avg profit {results_metrics['profit_mean'] * 100: 6.2f}%. " f"Avg profit {results_metrics['profit_mean'] * 100: 6.2f}%. "
f"Median profit {results_metrics['profit_median'] * 100: 6.2f}%. " f"Median profit {results_metrics['profit_median'] * 100: 6.2f}%. "
f"Total profit {results_metrics['profit_total_abs']: 11.8f} {stake_currency} " f"Total profit {results_metrics['profit_total_abs']: 11.8f} {stake_currency} "
f"({results_metrics['profit_total']: 7.2f}\N{GREEK CAPITAL LETTER SIGMA}%). " f"({results_metrics['profit_total'] * 100: 7.2f}\N{GREEK CAPITAL LETTER SIGMA}%). "
f"Avg duration {results_metrics['holding_avg']} min." f"Avg duration {results_metrics['holding_avg']} min."
).encode(locale.getpreferredencoding(), 'replace').decode('utf-8') ).encode(locale.getpreferredencoding(), 'replace').decode('utf-8')
@ -184,8 +184,10 @@ class HyperoptTools():
if 'results_metrics.winsdrawslosses' not in trials.columns: if 'results_metrics.winsdrawslosses' not in trials.columns:
# Ensure compatibility with older versions of hyperopt results # Ensure compatibility with older versions of hyperopt results
trials['results_metrics.winsdrawslosses'] = 'N/A' trials['results_metrics.winsdrawslosses'] = 'N/A'
legacy_mode = True
if 'results_metrics.total_trades' in trials: if 'results_metrics.total_trades' in trials:
legacy_mode = False
# New mode, using backtest result for metrics # New mode, using backtest result for metrics
trials['results_metrics.winsdrawslosses'] = trials.apply( trials['results_metrics.winsdrawslosses'] = trials.apply(
lambda x: f"{x['results_metrics.wins']} {x['results_metrics.draws']:>4} " lambda x: f"{x['results_metrics.wins']} {x['results_metrics.draws']:>4} "
@ -212,12 +214,12 @@ class HyperoptTools():
trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best' trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best'
trials.loc[trials['Total profit'] > 0, 'is_profit'] = True trials.loc[trials['Total profit'] > 0, 'is_profit'] = True
trials['Trades'] = trials['Trades'].astype(str) trials['Trades'] = trials['Trades'].astype(str)
perc_multi = 1 if legacy_mode else 100
trials['Epoch'] = trials['Epoch'].apply( trials['Epoch'] = trials['Epoch'].apply(
lambda x: '{}/{}'.format(str(x).rjust(len(str(total_epochs)), ' '), total_epochs) lambda x: '{}/{}'.format(str(x).rjust(len(str(total_epochs)), ' '), total_epochs)
) )
trials['Avg profit'] = trials['Avg profit'].apply( trials['Avg profit'] = trials['Avg profit'].apply(
lambda x: f'{x:,.2f}%'.rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ') lambda x: f'{x * perc_multi:,.2f}%'.rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
) )
trials['Avg duration'] = trials['Avg duration'].apply( trials['Avg duration'] = trials['Avg duration'].apply(
lambda x: f'{x:,.1f} m'.rjust(7, ' ') if isinstance(x, float) else f"{x}" lambda x: f'{x:,.1f} m'.rjust(7, ' ') if isinstance(x, float) else f"{x}"
@ -231,7 +233,7 @@ class HyperoptTools():
trials['Profit'] = trials.apply( trials['Profit'] = trials.apply(
lambda x: '{} {}'.format( lambda x: '{} {}'.format(
round_coin_value(x['Total profit'], stake_currency), round_coin_value(x['Total profit'], stake_currency),
'({:,.2f}%)'.format(x['Profit']).rjust(10, ' ') '({:,.2f}%)'.format(x['Profit'] * perc_multi).rjust(10, ' ')
).rjust(25+len(stake_currency)) ).rjust(25+len(stake_currency))
if x['Total profit'] != 0.0 else '--'.rjust(25+len(stake_currency)), if x['Total profit'] != 0.0 else '--'.rjust(25+len(stake_currency)),
axis=1 axis=1