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freqtrade_origin/freqtrade/tests/optimize/test_hyperopt.py

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# pragma pylint: disable=missing-docstring,W0212,C0103
import json
import os
from copy import deepcopy
from unittest.mock import MagicMock
import pandas as pd
from freqtrade.optimize.__init__ import load_tickerdata_file
from freqtrade.optimize.hyperopt import Hyperopt, start
from freqtrade.strategy.resolver import StrategyResolver
from freqtrade.tests.conftest import default_conf, log_has
from freqtrade.tests.optimize.test_backtesting import get_args
# Avoid to reinit the same object again and again
_HYPEROPT = Hyperopt(default_conf())
# Functions for recurrent object patching
def create_trials(mocker) -> None:
"""
When creating trials, mock the hyperopt Trials so that *by default*
- we don't create any pickle'd files in the filesystem
- we might have a pickle'd file so make sure that we return
false when looking for it
"""
_HYPEROPT.trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=False)
mocker.patch('freqtrade.optimize.hyperopt.os.path.getsize', return_value=1)
mocker.patch('freqtrade.optimize.hyperopt.os.remove', return_value=True)
mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
return mocker.Mock(
results=[
{
'loss': 1,
'result': 'foo',
'status': 'ok'
}
],
best_trial={'misc': {'vals': {'adx': 999}}}
)
# Unit tests
def test_start(mocker, default_conf, caplog) -> None:
"""
Test start() function
"""
start_mock = MagicMock()
mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(default_conf)
))
args = [
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
'hyperopt',
'--epochs', '5'
]
args = get_args(args)
StrategyResolver({'strategy': 'DefaultStrategy'})
start(args)
import pprint
pprint.pprint(caplog.record_tuples)
assert log_has(
'Starting freqtrade in Hyperopt mode',
caplog.record_tuples
)
assert start_mock.call_count == 1
def test_loss_calculation_prefer_correct_trade_count() -> None:
"""
Test Hyperopt.calculate_loss()
"""
hyperopt = _HYPEROPT
StrategyResolver({'strategy': 'DefaultStrategy'})
correct = hyperopt.calculate_loss(1, hyperopt.target_trades, 20)
over = hyperopt.calculate_loss(1, hyperopt.target_trades + 100, 20)
under = hyperopt.calculate_loss(1, hyperopt.target_trades - 100, 20)
assert over > correct
assert under > correct
def test_loss_calculation_prefer_shorter_trades() -> None:
"""
Test Hyperopt.calculate_loss()
"""
hyperopt = _HYPEROPT
shorter = hyperopt.calculate_loss(1, 100, 20)
longer = hyperopt.calculate_loss(1, 100, 30)
assert shorter < longer
def test_loss_calculation_has_limited_profit() -> None:
hyperopt = _HYPEROPT
correct = hyperopt.calculate_loss(hyperopt.expected_max_profit, hyperopt.target_trades, 20)
over = hyperopt.calculate_loss(hyperopt.expected_max_profit * 2, hyperopt.target_trades, 20)
under = hyperopt.calculate_loss(hyperopt.expected_max_profit / 2, hyperopt.target_trades, 20)
assert over == correct
assert under > correct
def test_log_results_if_loss_improves(caplog) -> None:
hyperopt = _HYPEROPT
hyperopt.current_best_loss = 2
hyperopt.log_results(
{
'loss': 1,
'current_tries': 1,
'total_tries': 2,
'result': 'foo'
}
)
assert log_has(' 1/2: foo. Loss 1.00000', caplog.record_tuples)
def test_no_log_if_loss_does_not_improve(caplog) -> None:
hyperopt = _HYPEROPT
hyperopt.current_best_loss = 2
hyperopt.log_results(
{
'loss': 3,
}
)
assert caplog.record_tuples == []
def test_fmin_best_results(mocker, default_conf, caplog) -> None:
fmin_result = {
"macd_below_zero": 0,
"adx": 1,
"adx-value": 15.0,
"fastd": 1,
"fastd-value": 40.0,
"green_candle": 1,
"mfi": 0,
"over_sar": 0,
"rsi": 1,
"rsi-value": 37.0,
"trigger": 2,
"uptrend_long_ema": 1,
"uptrend_short_ema": 0,
"uptrend_sma": 0,
"stoploss": -0.1,
"roi_t1": 1,
"roi_t2": 2,
"roi_t3": 3,
"roi_p1": 1,
"roi_p2": 2,
"roi_p3": 3,
}
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
hyperopt = Hyperopt(conf)
hyperopt.trials = create_trials(mocker)
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
exists = [
'Best parameters:',
'"adx": {\n "enabled": true,\n "value": 15.0\n },',
'"fastd": {\n "enabled": true,\n "value": 40.0\n },',
'"green_candle": {\n "enabled": true\n },',
'"macd_below_zero": {\n "enabled": false\n },',
'"mfi": {\n "enabled": false\n },',
'"over_sar": {\n "enabled": false\n },',
'"roi_p1": 1.0,',
'"roi_p2": 2.0,',
'"roi_p3": 3.0,',
'"roi_t1": 1.0,',
'"roi_t2": 2.0,',
'"roi_t3": 3.0,',
'"rsi": {\n "enabled": true,\n "value": 37.0\n },',
'"stoploss": -0.1,',
'"trigger": {\n "type": "faststoch10"\n },',
'"uptrend_long_ema": {\n "enabled": true\n },',
'"uptrend_short_ema": {\n "enabled": false\n },',
'"uptrend_sma": {\n "enabled": false\n }',
'ROI table:\n{0: 6.0, 3.0: 3.0, 5.0: 1.0, 6.0: 0}',
'Best Result:\nfoo'
]
for line in exists:
assert line in caplog.text
def test_fmin_throw_value_error(mocker, default_conf, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', side_effect=ValueError())
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
hyperopt = Hyperopt(conf)
hyperopt.trials = create_trials(mocker)
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
exists = [
'Best Result:',
'Sorry, Hyperopt was not able to find good parameters. Please try with more epochs '
'(param: -e).',
]
for line in exists:
assert line in caplog.text
def test_resuming_previous_hyperopt_results_succeeds(mocker, default_conf) -> None:
trials = create_trials(mocker)
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=True)
mocker.patch('freqtrade.optimize.hyperopt.len', return_value=len(trials.results))
mock_read = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.read_trials',
return_value=trials
)
mock_save = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.save_trials',
return_value=None
)
mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
hyperopt = Hyperopt(conf)
hyperopt.trials = trials
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
mock_read.assert_called_once()
mock_save.assert_called_once()
current_tries = hyperopt.current_tries
total_tries = hyperopt.total_tries
assert current_tries == len(trials.results)
assert total_tries == (current_tries + len(trials.results))
def test_save_trials_saves_trials(mocker, caplog) -> None:
create_trials(mocker)
mock_dump = mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
hyperopt = _HYPEROPT
mocker.patch('freqtrade.optimize.hyperopt.open', return_value=hyperopt.trials_file)
hyperopt.save_trials()
assert log_has(
'Saving Trials to \'freqtrade/tests/optimize/ut_trials.pickle\'',
caplog.record_tuples
)
mock_dump.assert_called_once()
def test_read_trials_returns_trials_file(mocker, caplog) -> None:
trials = create_trials(mocker)
mock_load = mocker.patch('freqtrade.optimize.hyperopt.pickle.load', return_value=trials)
mock_open = mocker.patch('freqtrade.optimize.hyperopt.open', return_value=mock_load)
hyperopt = _HYPEROPT
hyperopt_trial = hyperopt.read_trials()
assert log_has(
'Reading Trials from \'freqtrade/tests/optimize/ut_trials.pickle\'',
caplog.record_tuples
)
assert hyperopt_trial == trials
mock_open.assert_called_once()
mock_load.assert_called_once()
def test_roi_table_generation() -> None:
params = {
'roi_t1': 5,
'roi_t2': 10,
'roi_t3': 15,
'roi_p1': 1,
'roi_p2': 2,
'roi_p3': 3,
}
hyperopt = _HYPEROPT
assert hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
def test_start_calls_fmin(mocker, default_conf) -> None:
trials = create_trials(mocker)
mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
hyperopt = Hyperopt(conf)
hyperopt.trials = trials
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
mock_fmin.assert_called_once()
def test_start_uses_mongotrials(mocker, default_conf) -> None:
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
mock_mongotrials = mocker.patch(
'freqtrade.optimize.hyperopt.MongoTrials',
return_value=create_trials(mocker)
)
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': True})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
hyperopt = Hyperopt(conf)
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
mock_mongotrials.assert_called_once()
mock_fmin.assert_called_once()
# test log_trials_result
# test buy_strategy_generator def populate_buy_trend
# test optimizer if 'ro_t1' in params
def test_format_results():
"""
Test Hyperopt.format_results()
"""
trades = [
('BTC_ETH', 2, 2, 123),
('BTC_LTC', 1, 1, 123),
('BTC_XRP', -1, -2, -246)
]
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
df = pd.DataFrame.from_records(trades, columns=labels)
x = Hyperopt.format_results(df)
assert x.find(' 66.67%')
def test_signal_handler(mocker):
"""
Test Hyperopt.signal_handler()
"""
m = MagicMock()
mocker.patch('sys.exit', m)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.save_trials', m)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.log_trials_result', m)
hyperopt = _HYPEROPT
hyperopt.signal_handler(9, None)
assert m.call_count == 3
def test_has_space():
"""
Test Hyperopt.has_space() method
"""
_HYPEROPT.config.update({'spaces': ['buy', 'roi']})
assert _HYPEROPT.has_space('roi')
assert _HYPEROPT.has_space('buy')
assert not _HYPEROPT.has_space('stoploss')
_HYPEROPT.config.update({'spaces': ['all']})
assert _HYPEROPT.has_space('buy')
def test_populate_indicators() -> None:
"""
Test Hyperopt.populate_indicators()
"""
tick = load_tickerdata_file(None, 'BTC_UNITEST', 1)
tickerlist = {'BTC_UNITEST': tick}
dataframes = _HYPEROPT.tickerdata_to_dataframe(tickerlist)
dataframe = _HYPEROPT.populate_indicators(dataframes['BTC_UNITEST'])
# Check if some indicators are generated. We will not test all of them
assert 'adx' in dataframe
assert 'ao' in dataframe
assert 'cci' in dataframe
def test_buy_strategy_generator() -> None:
"""
Test Hyperopt.buy_strategy_generator()
"""
tick = load_tickerdata_file(None, 'BTC_UNITEST', 1)
tickerlist = {'BTC_UNITEST': tick}
dataframes = _HYPEROPT.tickerdata_to_dataframe(tickerlist)
dataframe = _HYPEROPT.populate_indicators(dataframes['BTC_UNITEST'])
populate_buy_trend = _HYPEROPT.buy_strategy_generator(
{
'uptrend_long_ema': {
'enabled': True
},
'macd_below_zero': {
'enabled': True
},
'uptrend_short_ema': {
'enabled': True
},
'mfi': {
'enabled': True,
'value': 20
},
'fastd': {
'enabled': True,
'value': 20
},
'adx': {
'enabled': True,
'value': 20
},
'rsi': {
'enabled': True,
'value': 20
},
'over_sar': {
'enabled': True,
},
'green_candle': {
'enabled': True,
},
'uptrend_sma': {
'enabled': True,
},
'trigger': {
'type': 'lower_bb'
}
}
)
result = populate_buy_trend(dataframe)
# Check if some indicators are generated. We will not test all of them
assert 'buy' in result
assert 1 in result['buy']
def test_generate_optimizer(mocker, default_conf) -> None:
"""
Test Hyperopt.generate_optimizer() function
"""
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
trades = [
('BTC_POWR', 0.023117, 0.000233, 100)
]
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
backtest_result = pd.DataFrame.from_records(trades, columns=labels)
mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.backtest',
MagicMock(return_value=backtest_result)
)
optimizer_param = {
'adx': {'enabled': False},
'fastd': {'enabled': True, 'value': 35.0},
'green_candle': {'enabled': True},
'macd_below_zero': {'enabled': True},
'mfi': {'enabled': False},
'over_sar': {'enabled': False},
'roi_p1': 0.01,
'roi_p2': 0.01,
'roi_p3': 0.1,
'roi_t1': 60.0,
'roi_t2': 30.0,
'roi_t3': 20.0,
'rsi': {'enabled': False},
'stoploss': -0.4,
'trigger': {'type': 'macd_cross_signal'},
'uptrend_long_ema': {'enabled': False},
'uptrend_short_ema': {'enabled': True},
'uptrend_sma': {'enabled': True}
}
response_expected = {
'loss': 1.9840569076926293,
'result': ' 1 trades. Avg profit 2.31%. Total profit 0.00023300 BTC '
'(0.0231Σ%). Avg duration 100.0 mins.',
'status': 'ok'
}
hyperopt = Hyperopt(conf)
generate_optimizer_value = hyperopt.generate_optimizer(optimizer_param)
assert generate_optimizer_value == response_expected
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