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Merge pull request #2994 from Fredrik81/hyperopt-table

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Added dynamic print table function to hyperopt
This commit is contained in:
hroff-1902
2020-03-04 23:44:53 +03:00
committed by GitHub
parent 33c1c8f726 090d1e8a70
commit 57523d58df
3 changed files with 164 additions and 46 deletions
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2
freqtrade/commands/hyperopt_commands.py
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@@ -51,7 +51,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
try:
Hyperopt.print_result_table(config, trials, total_epochs,
not filteroptions['only_best'], print_colorized)
not filteroptions['only_best'], print_colorized, 0)
except KeyboardInterrupt:
print('User interrupted..')

77
freqtrade/optimize/hyperopt.py
View File

@@ -22,7 +22,7 @@ from colorama import init as colorama_init
from joblib import (Parallel, cpu_count, delayed, dump, load,
wrap_non_picklable_objects)
from pandas import DataFrame, json_normalize, isna
from tabulate import tabulate
import tabulate
from freqtrade.data.converter import trim_dataframe
from freqtrade.data.history import get_timerange
@@ -117,6 +117,7 @@ class Hyperopt:
self.config['ask_strategy']['use_sell_signal'] = True
self.print_all = self.config.get('print_all', False)
self.hyperopt_table_header = 0
self.print_colorized = self.config.get('print_colorized', False)
self.print_json = self.config.get('print_json', False)
@@ -154,7 +155,7 @@ class Hyperopt:
"""
num_trials = len(self.trials)
if num_trials > self.num_trials_saved:
logger.info(f"Saving {num_trials} {plural(num_trials, 'epoch')}.")
logger.debug(f"Saving {num_trials} {plural(num_trials, 'epoch')}.")
dump(self.trials, self.trials_file)
self.num_trials_saved = num_trials
if final:
@@ -273,8 +274,10 @@ class Hyperopt:
if not self.print_all:
# Separate the results explanation string from dots
print("\n")
self.print_results_explanation(results, self.total_epochs, self.print_all,
self.print_colorized)
self.print_result_table(self.config, results, self.total_epochs,
self.print_all, self.print_colorized,
self.hyperopt_table_header)
self.hyperopt_table_header = 2
@staticmethod
def print_results_explanation(results, total_epochs, highlight_best: bool,
@@ -300,13 +303,15 @@ class Hyperopt:
@staticmethod
def print_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool,
print_colorized: bool) -> None:
print_colorized: bool, remove_header: int) -> None:
"""
Log result table
"""
if not results:
return
tabulate.PRESERVE_WHITESPACE = True
trials = json_normalize(results, max_level=1)
trials['Best'] = ''
trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count',
@@ -318,35 +323,63 @@ class Hyperopt:
trials['is_profit'] = False
trials.loc[trials['is_initial_point'], 'Best'] = '*'
trials.loc[trials['is_best'], 'Best'] = 'Best'
trials['Objective'] = trials['Objective'].astype(str)
trials.loc[trials['Total profit'] > 0, 'is_profit'] = True
trials['Trades'] = trials['Trades'].astype(str)
trials['Epoch'] = trials['Epoch'].apply(
lambda x: "{}/{}".format(x, total_epochs))
lambda x: '{}/{}'.format(str(x).rjust(len(str(total_epochs)), ' '), total_epochs)
)
trials['Avg profit'] = trials['Avg profit'].apply(
lambda x: '{:,.2f}%'.format(x) if not isna(x) else x)
trials['Profit'] = trials['Profit'].apply(
lambda x: '{:,.2f}%'.format(x) if not isna(x) else x)
trials['Total profit'] = trials['Total profit'].apply(
lambda x: '{: 11.8f} '.format(x) + config['stake_currency'] if not isna(x) else x)
lambda x: ('{:,.2f}%'.format(x)).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
)
trials['Avg duration'] = trials['Avg duration'].apply(
lambda x: '{:,.1f}m'.format(x) if not isna(x) else x)
lambda x: ('{:,.1f} m'.format(x)).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
)
trials['Objective'] = trials['Objective'].apply(
lambda x: '{:,.5f}'.format(x).rjust(8, ' ') if x != 100000 else "N/A".rjust(8, ' ')
)
trials['Profit'] = trials.apply(
lambda x: '{:,.8f} {} {}'.format(
x['Total profit'], config['stake_currency'],
'({:,.2f}%)'.format(x['Profit']).rjust(10, ' ')
).rjust(25+len(config['stake_currency']))
if x['Total profit'] != 0.0 else '--'.rjust(25+len(config['stake_currency'])),
axis=1
)
trials = trials.drop(columns=['Total profit'])
if print_colorized:
for i in range(len(trials)):
if trials.loc[i]['is_profit']:
for z in range(len(trials.loc[i])-3):
trials.iat[i, z] = "{}{}{}".format(Fore.GREEN,
str(trials.loc[i][z]), Fore.RESET)
for j in range(len(trials.loc[i])-3):
trials.iat[i, j] = "{}{}{}".format(Fore.GREEN,
str(trials.loc[i][j]), Fore.RESET)
if trials.loc[i]['is_best'] and highlight_best:
for z in range(len(trials.loc[i])-3):
trials.iat[i, z] = "{}{}{}".format(Style.BRIGHT,
str(trials.loc[i][z]), Style.RESET_ALL)
for j in range(len(trials.loc[i])-3):
trials.iat[i, j] = "{}{}{}".format(Style.BRIGHT,
str(trials.loc[i][j]), Style.RESET_ALL)
trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit'])
if remove_header > 0:
table = tabulate.tabulate(
trials.to_dict(orient='list'), tablefmt='orgtbl',
headers='keys', stralign="right"
)
print(tabulate(trials.to_dict(orient='list'), headers='keys', tablefmt='psql',
stralign="right"))
table = table.split("\n", remove_header)[remove_header]
elif remove_header < 0:
table = tabulate.tabulate(
trials.to_dict(orient='list'), tablefmt='psql',
headers='keys', stralign="right"
)
table = "\n".join(table.split("\n")[0:remove_header])
else:
table = tabulate.tabulate(
trials.to_dict(orient='list'), tablefmt='psql',
headers='keys', stralign="right"
)
print(table)
def has_space(self, space: str) -> bool:
"""
@@ -534,7 +567,7 @@ class Hyperopt:
def start(self) -> None:
self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None))
logger.info(f"Using optimizer random state: {self.random_state}")
self.hyperopt_table_header = -1
data, timerange = self.backtesting.load_bt_data()
preprocessed = self.backtesting.strategy.tickerdata_to_dataframe(data)