def start_hyperopt_show(args: Dict[str, Any]) -> None:
"""
Show details of a hyperopt epoch previously evaluated
"""
from freqtrade.optimize.hyperopt_tools import HyperoptTools
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
print_json = config.get('print_json', False)
no_header = config.get('hyperopt_show_no_header', False)
results_file = get_latest_hyperopt_file(
config['user_data_dir'] / 'hyperopt_results',
config.get('hyperoptexportfilename'))
n = config.get('hyperopt_show_index', -1)
# Previous evaluations
epochs, total_epochs = HyperoptTools.load_filtered_results(
results_file, config)
filtered_epochs = len(epochs)
if n > filtered_epochs:
raise OperationalException(
f"The index of the epoch to show should be less than {filtered_epochs + 1}."
)
if n < -filtered_epochs:
raise OperationalException(
f"The index of the epoch to show should be greater than {-filtered_epochs - 1}."
)
# Translate epoch index from human-readable format to pythonic
if n > 0:
n -= 1
if epochs:
val = epochs[n]
metrics = val['results_metrics']
if 'strategy_name' in metrics:
strategy_name = metrics['strategy_name']
show_backtest_result(strategy_name, metrics,
metrics['stake_currency'],
config.get('backtest_breakdown', []))
HyperoptTools.try_export_params(config, strategy_name, val)
HyperoptTools.show_epoch_details(val,
total_epochs,
print_json,
no_header,
header_str="Epoch details")
def test_try_export_params(default_conf, tmpdir, caplog, mocker):
default_conf['disableparamexport'] = False
export_mock = mocker.patch("freqtrade.optimize.hyperopt_tools.HyperoptTools.export_params")
filename = Path(tmpdir) / f"{CURRENT_TEST_STRATEGY}.json"
assert not filename.is_file()
params = {
"params_details": {
"buy": {
"buy_rsi": 30
},
"sell": {
"sell_rsi": 70
},
"roi": {
"0": 0.528,
"346": 0.08499,
"507": 0.049,
"1595": 0
}
},
"params_not_optimized": {
"stoploss": -0.05,
"trailing": {
"trailing_stop": False,
"trailing_stop_positive": 0.05,
"trailing_stop_positive_offset": 0.1,
"trailing_only_offset_is_reached": True
},
},
FTHYPT_FILEVERSION: 2,
}
HyperoptTools.try_export_params(default_conf, "StrategyTestVXXX", params)
assert log_has("Strategy not found, not exporting parameter file.", caplog)
assert export_mock.call_count == 0
caplog.clear()
HyperoptTools.try_export_params(default_conf, CURRENT_TEST_STRATEGY, params)
assert export_mock.call_count == 1
assert export_mock.call_args_list[0][0][1] == CURRENT_TEST_STRATEGY
assert export_mock.call_args_list[0][0][2].name == 'strategy_test_v3.json'
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
# Initialize spaces ...
self.init_spaces()
self.prepare_hyperopt_data()
# We don't need exchange instance anymore while running hyperopt
self.backtesting.exchange.close()
self.backtesting.exchange._api = None # type: ignore
self.backtesting.exchange._api_async = None # type: ignore
# self.backtesting.exchange = None # type: ignore
self.backtesting.pairlists = None # type: ignore
cpus = cpu_count()
logger.info(f"Found {cpus} CPU cores. Let's make them scream!")
config_jobs = self.config.get('hyperopt_jobs', -1)
logger.info(f'Number of parallel jobs set as: {config_jobs}')
self.opt = self.get_optimizer(self.dimensions, config_jobs)
if self.print_colorized:
colorama_init(autoreset=True)
try:
with Parallel(n_jobs=config_jobs) as parallel:
jobs = parallel._effective_n_jobs()
logger.info(
f'Effective number of parallel workers used: {jobs}')
# Define progressbar
if self.print_colorized:
widgets = [
' [Epoch ',
progressbar.Counter(),
' of ',
str(self.total_epochs),
' (',
progressbar.Percentage(),
')] ',
progressbar.Bar(marker=progressbar.AnimatedMarker(
fill='\N{FULL BLOCK}',
fill_wrap=Fore.GREEN + '{}' + Fore.RESET,
marker_wrap=Style.BRIGHT + '{}' + Style.RESET_ALL,
)),
' [',
progressbar.ETA(),
', ',
progressbar.Timer(),
']',
]
else:
widgets = [
' [Epoch ',
progressbar.Counter(),
' of ',
str(self.total_epochs),
' (',
progressbar.Percentage(),
')] ',
progressbar.Bar(marker=progressbar.AnimatedMarker(
fill='\N{FULL BLOCK}', )),
' [',
progressbar.ETA(),
', ',
progressbar.Timer(),
']',
]
with progressbar.ProgressBar(max_value=self.total_epochs,
redirect_stdout=False,
redirect_stderr=False,
widgets=widgets) as pbar:
EVALS = ceil(self.total_epochs / jobs)
for i in range(EVALS):
# Correct the number of epochs to be processed for the last
# iteration (should not exceed self.total_epochs in total)
n_rest = (i + 1) * jobs - self.total_epochs
current_jobs = jobs - n_rest if n_rest > 0 else jobs
asked = self.opt.ask(n_points=current_jobs)
f_val = self.run_optimizer_parallel(parallel, asked, i)
self.opt.tell(asked, [v['loss'] for v in f_val])
# Calculate progressbar outputs
for j, val in enumerate(f_val):
# Use human-friendly indexes here (starting from 1)
current = i * jobs + j + 1
val['current_epoch'] = current
val['is_initial_point'] = current <= INITIAL_POINTS
logger.debug(f"Optimizer epoch evaluated: {val}")
is_best = HyperoptTools.is_best_loss(
val, self.current_best_loss)
# This value is assigned here and not in the optimization method
# to keep proper order in the list of results. That's because
# evaluations can take different time. Here they are aligned in the
# order they will be shown to the user.
val['is_best'] = is_best
self.print_results(val)
if is_best:
self.current_best_loss = val['loss']
self.current_best_epoch = val
self._save_result(val)
pbar.update(current)
except KeyboardInterrupt:
print('User interrupted..')
logger.info(
f"{self.num_epochs_saved} {plural(self.num_epochs_saved, 'epoch')} "
f"saved to '{self.results_file}'.")
if self.current_best_epoch:
HyperoptTools.try_export_params(
self.config, self.backtesting.strategy.get_strategy_name(),
self.current_best_epoch)
HyperoptTools.show_epoch_details(self.current_best_epoch,
self.total_epochs,
self.print_json)
else:
# This is printed when Ctrl+C is pressed quickly, before first epochs have
# a chance to be evaluated.
print("No epochs evaluated yet, no best result.")