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Merge pull request #2994 from Fredrik81/hyperopt-table 

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
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 164 additions and 46 deletions
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2
freqtrade/commands/hyperopt_commands.py
View File

@ -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)

131
tests/optimize/test_hyperopt.py
View File

@ -426,17 +426,27 @@ def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results)
def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
hyperopt.current_best_loss = 2
hyperopt.total_epochs = 2
hyperopt.print_results(
{
'is_best': True,
'loss': 1,
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
},
'total_profit': 0,
'current_epoch': 2, # This starts from 1 (in a human-friendly manner)
'results_explanation': 'foo.',
'is_initial_point': False
'is_initial_point': False,
'is_best': True
}
)
out, err = capsys.readouterr()
assert ' 2/2: foo. Objective: 1.00000' in out
assert all(x in out
for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC (1.00%)", "20.0 m"])
def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
@ -458,13 +468,11 @@ def test_save_trials_saves_trials(mocker, hyperopt, testdatadir, caplog) -> None
hyperopt.trials = trials
hyperopt.save_trials(final=True)
assert log_has("Saving 1 epoch.", caplog)
assert log_has(f"1 epoch saved to '{trials_file}'.", caplog)
mock_dump.assert_called_once()
hyperopt.trials = trials + trials
hyperopt.save_trials(final=True)
assert log_has("Saving 2 epochs.", caplog)
assert log_has(f"2 epochs saved to '{trials_file}'.", caplog)
@ -502,8 +510,18 @@ def test_start_calls_optimizer(mocker, default_conf, caplog, capsys) -> None:
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{'loss': 1, 'results_explanation': 'foo result',
'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0}}])
MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result',
'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0},
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
},
}])
)
patch_exchange(mocker)
# Co-test loading ticker-interval from strategy
@ -797,11 +815,23 @@ def test_print_json_spaces_all(mocker, default_conf, caplog, capsys) -> None:
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{'loss': 1, 'results_explanation': 'foo result', 'params': {},
'params_details': {'buy': {'mfi-value': None},
'sell': {'sell-mfi-value': None},
'roi': {}, 'stoploss': {'stoploss': None},
'trailing': {'trailing_stop': None}}}])
MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
'params_details': {
'buy': {'mfi-value': None},
'sell': {'sell-mfi-value': None},
'roi': {}, 'stoploss': {'stoploss': None},
'trailing': {'trailing_stop': None}
},
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
}
}])
)
patch_exchange(mocker)
@ -823,7 +853,11 @@ def test_print_json_spaces_all(mocker, default_conf, caplog, capsys) -> None:
parallel.assert_called_once()
out, err = capsys.readouterr()
assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null,"trailing_stop":null}' in out # noqa: E501
result_str = (
'{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi"'
':{},"stoploss":null,"trailing_stop":null}'
)
assert result_str in out # noqa: E501
assert dumper.called
# Should be called twice, once for tickerdata, once to save evaluations
assert dumper.call_count == 2
@ -840,10 +874,22 @@ def test_print_json_spaces_default(mocker, default_conf, caplog, capsys) -> None
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{'loss': 1, 'results_explanation': 'foo result', 'params': {},
'params_details': {'buy': {'mfi-value': None},
'sell': {'sell-mfi-value': None},
'roi': {}, 'stoploss': {'stoploss': None}}}])
MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
'params_details': {
'buy': {'mfi-value': None},
'sell': {'sell-mfi-value': None},
'roi': {}, 'stoploss': {'stoploss': None}
},
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
}
}])
)
patch_exchange(mocker)
@ -882,8 +928,18 @@ def test_print_json_spaces_roi_stoploss(mocker, default_conf, caplog, capsys) ->
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{'loss': 1, 'results_explanation': 'foo result', 'params': {},
'params_details': {'roi': {}, 'stoploss': {'stoploss': None}}}])
MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
'params_details': {'roi': {}, 'stoploss': {'stoploss': None}},
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
}
}])
)
patch_exchange(mocker)
@ -923,7 +979,16 @@ def test_simplified_interface_roi_stoploss(mocker, default_conf, caplog, capsys)
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {'stoploss': 0.0}}])
'loss': 1, 'results_explanation': 'foo result', 'params': {'stoploss': 0.0},
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
}
}])
)
patch_exchange(mocker)
@ -1001,7 +1066,17 @@ def test_simplified_interface_buy(mocker, default_conf, caplog, capsys) -> None:
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{'loss': 1, 'results_explanation': 'foo result', 'params': {}}])
MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
}
}])
)
patch_exchange(mocker)
@ -1048,7 +1123,17 @@ def test_simplified_interface_sell(mocker, default_conf, caplog, capsys) -> None
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{'loss': 1, 'results_explanation': 'foo result', 'params': {}}])
MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
'results_metrics':
{
'trade_count': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 1.0,
'duration': 20.0
}
}])
)
patch_exchange(mocker)