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hyperopt print colorized results

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This commit is contained in:
hroff-1902
2019-08-03 19:09:42 +03:00
parent b3e6e710d8
commit f200f52a16
6 changed files with 43 additions and 3 deletions
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18
freqtrade/optimize/hyperopt.py
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@@ -20,6 +20,7 @@ from skopt.space import Dimension
from freqtrade.configuration import Arguments
from freqtrade.data.history import load_data, get_timeframe
from freqtrade.misc import green, red, bold
from freqtrade.optimize.backtesting import Backtesting
# Import IHyperOptLoss to allow users import from this file
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F4
@@ -153,8 +154,19 @@ class Hyperopt(Backtesting):
Log results if it is better than any previous evaluation
"""
print_all = self.config.get('print_all', False)
if print_all or results['loss'] < self.current_best_loss:
is_best_loss = results['loss'] < self.current_best_loss
if print_all or is_best_loss:
if is_best_loss:
self.current_best_loss = results['loss']
log_str = self.format_results_logstring(results)
# Colorize output
if self.config.get('print_colorized', False):
if results['total_profit'] > 0:
log_str = bold(log_str)
if results['loss'] >= MAX_LOSS:
log_str = red(log_str)
elif is_best_loss:
log_str = green(log_str)
if print_all:
print(log_str)
else:
@@ -169,7 +181,6 @@ class Hyperopt(Backtesting):
total = self.total_epochs
res = results['results_explanation']
loss = results['loss']
self.current_best_loss = results['loss']
log_str = f'{current:5d}/{total}: {res} Objective: {loss:.5f}'
log_str = f'*{log_str}' if results['is_initial_point'] else f' {log_str}'
return log_str
@@ -237,6 +248,7 @@ class Hyperopt(Backtesting):
results_explanation = self.format_results(results)
trade_count = len(results.index)
total_profit = results.profit_abs.sum()
# If this evaluation contains too short amount of trades to be
# interesting -- consider it as 'bad' (assigned max. loss value)
@@ -247,6 +259,7 @@ class Hyperopt(Backtesting):
'loss': MAX_LOSS,
'params': params,
'results_explanation': results_explanation,
'total_profit': total_profit,
}
loss = self.calculate_loss(results=results, trade_count=trade_count,
@@ -256,6 +269,7 @@ class Hyperopt(Backtesting):
'loss': loss,
'params': params,
'results_explanation': results_explanation,
'total_profit': total_profit,
}
def format_results(self, results: DataFrame) -> str: