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Merge branch 'develop' into pr/Antreasgr/4838

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Matthias
2021-05-27 14:58:19 +02:00
parent 3014bc3467 cf39dd2163
commit a89364aa98
95 changed files with 2815 additions and 1369 deletions
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318
tests/optimize/test_hyperopt.py
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@@ -4,7 +4,7 @@ import re
from datetime import datetime
from pathlib import Path
from typing import Dict, List
from unittest.mock import MagicMock
from unittest.mock import ANY, MagicMock
import pandas as pd
import pytest
@@ -17,10 +17,12 @@ from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt import Hyperopt
from freqtrade.optimize.hyperopt_auto import HyperOptAuto
from freqtrade.optimize.hyperopt_tools import HyperoptTools
from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.optimize.space import SKDecimal
from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
from freqtrade.state import RunMode
from freqtrade.strategy.hyper import IntParameter
from freqtrade.strategy.interface import SellType
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
patched_configuration_load_config_file)
@@ -28,23 +30,7 @@ from .hyperopts.default_hyperopt import DefaultHyperOpt
# Functions for recurrent object patching
def create_results(mocker, hyperopt, testdatadir) -> List[Dict]:
"""
When creating results, mock the hyperopt 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.results_file = testdatadir / 'optimize/ut_results.pickle'
mocker.patch.object(Path, "is_file", MagicMock(return_value=False))
stat_mock = MagicMock()
stat_mock.st_size = 1
mocker.patch.object(Path, "stat", MagicMock(return_value=stat_mock))
mocker.patch.object(Path, "unlink", MagicMock(return_value=True))
mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
def create_results() -> List[Dict]:
return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}]
@@ -318,54 +304,49 @@ def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
assert caplog.record_tuples == []
def test_save_results_saves_epochs(mocker, hyperopt, testdatadir, caplog) -> None:
epochs = create_results(mocker, hyperopt, testdatadir)
mock_dump = mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
mock_dump_json = mocker.patch('freqtrade.optimize.hyperopt.file_dump_json', return_value=None)
results_file = testdatadir / 'optimize' / 'ut_results.pickle'
def test_save_results_saves_epochs(mocker, hyperopt, tmpdir, caplog) -> None:
# Test writing to temp dir and reading again
epochs = create_results()
hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt')
caplog.set_level(logging.DEBUG)
hyperopt.epochs = epochs
hyperopt._save_results()
assert log_has(f"1 epoch saved to '{results_file}'.", caplog)
mock_dump.assert_called_once()
mock_dump_json.assert_called_once()
for epoch in epochs:
hyperopt._save_result(epoch)
assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog)
hyperopt.epochs = epochs + epochs
hyperopt._save_results()
assert log_has(f"2 epochs saved to '{results_file}'.", caplog)
hyperopt._save_result(epochs[0])
assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog)
hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file)
assert len(hyperopt_epochs) == 2
def test_read_results_returns_epochs(mocker, hyperopt, testdatadir, caplog) -> None:
epochs = create_results(mocker, hyperopt, testdatadir)
mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs)
results_file = testdatadir / 'optimize' / 'ut_results.pickle'
hyperopt_epochs = HyperoptTools._read_results(results_file)
assert log_has(f"Reading epochs from '{results_file}'", caplog)
assert hyperopt_epochs == epochs
mock_load.assert_called_once()
def test_load_previous_results(testdatadir, caplog) -> None:
def test_load_previous_results(mocker, hyperopt, testdatadir, caplog) -> None:
epochs = create_results(mocker, hyperopt, testdatadir)
mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs)
mocker.patch.object(Path, 'is_file', MagicMock(return_value=True))
statmock = MagicMock()
statmock.st_size = 5
# mocker.patch.object(Path, 'stat', MagicMock(return_value=statmock))
results_file = testdatadir / 'optimize' / 'ut_results.pickle'
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert hyperopt_epochs == epochs
mock_load.assert_called_once()
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading pickled epochs from .*", caplog)
del epochs[0]['is_best']
mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs)
caplog.clear()
with pytest.raises(OperationalException):
# Modern version
results_file = testdatadir / 'strategy_SampleStrategy.fthypt'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading epochs from .*", caplog)
def test_load_previous_results2(mocker, testdatadir, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt_tools.HyperoptTools._read_results_pickle',
return_value=[{'asdf': '222'}])
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
with pytest.raises(OperationalException, match=r"The file .* incompatible.*"):
HyperoptTools.load_previous_results(results_file)
@@ -383,7 +364,8 @@ def test_roi_table_generation(hyperopt) -> None:
def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
@@ -422,9 +404,9 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -432,18 +414,42 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
assert hasattr(hyperopt, "position_stacking")
def test_format_results(hyperopt):
# Test with BTC as stake_currency
trades = [
('ETH/BTC', 2, 2, 123),
('LTC/BTC', 1, 1, 123),
('XPR/BTC', -1, -2, -246)
]
labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration']
df = pd.DataFrame.from_records(trades, columns=labels)
results_metrics = hyperopt._calculate_results_metrics(df)
results_explanation = hyperopt._format_results_explanation_string(results_metrics)
total_profit = results_metrics['total_profit']
def test_hyperopt_format_results(hyperopt):
bt_result = {
'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
}),
'config': hyperopt.config,
'locks': [],
'final_balance': 0.02,
'rejected_signals': 2,
'backtest_start_time': 1619718665,
'backtest_end_time': 1619718665,
}
results_metrics = generate_strategy_stats({'XRP/BTC': None}, '', bt_result,
Arrow(2017, 11, 14, 19, 32, 00),
Arrow(2017, 12, 14, 19, 32, 00), market_change=0)
results_explanation = HyperoptTools.format_results_explanation_string(results_metrics, 'BTC')
total_profit = results_metrics['profit_total_abs']
results = {
'loss': 0.0,
@@ -457,21 +463,9 @@ def test_format_results(hyperopt):
}
result = HyperoptTools._format_explanation_string(results, 1)
assert result.find(' 66.67%')
assert result.find('Total profit 1.00000000 BTC')
assert result.find('2.0000Σ %')
# Test with EUR as stake_currency
trades = [
('ETH/EUR', 2, 2, 123),
('LTC/EUR', 1, 1, 123),
('XPR/EUR', -1, -2, -246)
]
df = pd.DataFrame.from_records(trades, columns=labels)
results_metrics = hyperopt._calculate_results_metrics(df)
results['total_profit'] = results_metrics['total_profit']
result = HyperoptTools._format_explanation_string(results, 1)
assert result.find('Total profit 1.00000000 EUR')
assert ' 0.71%' in result
assert 'Total profit 0.00003100 BTC' in result
assert '0:50:00 min' in result
@pytest.mark.parametrize("spaces, expected_results", [
@@ -502,10 +496,10 @@ def test_format_results(hyperopt):
(['default', 'buy'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
])
def test_has_space(hyperopt, spaces, expected_results):
def test_has_space(hyperopt_conf, spaces, expected_results):
for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
hyperopt.config.update({'spaces': spaces})
assert hyperopt.has_space(s) == expected_results[s]
hyperopt_conf.update({'spaces': spaces})
assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s]
def test_populate_indicators(hyperopt, testdatadir) -> None:
@@ -576,22 +570,39 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'hyperopt_min_trades': 1,
})
trades = [
('TRX/BTC', 0.023117, 0.000233, 100)
]
labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration']
backtest_result = pd.DataFrame.from_records(trades, columns=labels)
backtest_result = {
'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
}),
'config': hyperopt_conf,
'locks': [],
'rejected_signals': 20,
'final_balance': 1000,
}
mocker.patch(
'freqtrade.optimize.hyperopt.Backtesting.backtest',
MagicMock(return_value=backtest_result)
)
mocker.patch(
'freqtrade.optimize.hyperopt.get_timerange',
MagicMock(return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
)
mocker.patch('freqtrade.optimize.hyperopt.Backtesting.backtest', return_value=backtest_result)
mocker.patch('freqtrade.optimize.hyperopt.get_timerange',
return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())
mocker.patch.object(Path, 'open')
mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})
optimizer_param = {
'adx-value': 0,
@@ -625,11 +636,11 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'trailing_only_offset_is_reached': False,
}
response_expected = {
'loss': 1.9840569076926293,
'results_explanation': (' 1 trades. 1/0/0 Wins/Draws/Losses. '
'Avg profit 2.31%. Median profit 2.31%. Total profit '
'0.00023300 BTC ( 2.31%). '
'Avg duration 100.0 min.'
'loss': 1.9147239021396234,
'results_explanation': (' 4 trades. 4/0/0 Wins/Draws/Losses. '
'Avg profit 0.77%. Median profit 0.71%. Total profit '
'0.00003100 BTC ( 0.00%). '
'Avg duration 0:50:00 min.'
),
'params_details': {'buy': {'adx-enabled': False,
'adx-value': 0,
@@ -640,10 +651,10 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'rsi-enabled': False,
'rsi-value': 0,
'trigger': 'macd_cross_signal'},
'roi': {0: 0.12000000000000001,
20.0: 0.02,
50.0: 0.01,
110.0: 0},
'roi': {"0": 0.12000000000000001,
"20.0": 0.02,
"50.0": 0.01,
"110.0": 0},
'sell': {'sell-adx-enabled': False,
'sell-adx-value': 0,
'sell-fastd-enabled': True,
@@ -659,21 +670,16 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'trailing_stop_positive': 0.02,
'trailing_stop_positive_offset': 0.07}},
'params_dict': optimizer_param,
'results_metrics': {'avg_profit': 2.3117,
'draws': 0,
'duration': 100.0,
'losses': 0,
'winsdrawslosses': ' 1 0 0',
'median_profit': 2.3117,
'profit': 2.3117,
'total_profit': 0.000233,
'trade_count': 1,
'wins': 1},
'total_profit': 0.00023300
'params_not_optimized': {'buy': {}, 'sell': {}},
'results_metrics': ANY,
'total_profit': 3.1e-08
}
hyperopt = Hyperopt(hyperopt_conf)
hyperopt.dimensions = hyperopt.hyperopt_space()
hyperopt.min_date = Arrow(2017, 12, 10)
hyperopt.max_date = Arrow(2017, 12, 13)
hyperopt.init_spaces()
hyperopt.dimensions = hyperopt.dimensions
generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
assert generate_optimizer_value == response_expected
@@ -690,7 +696,8 @@ def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
@@ -741,13 +748,14 @@ def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
':{},"stoploss":null,"trailing_stop":null}'
)
assert result_str in out # noqa: E501
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -789,13 +797,14 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out # noqa: E501
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -836,13 +845,14 @@ def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert '{"minimal_roi":{},"stoploss":null}' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -884,9 +894,9 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -922,7 +932,8 @@ def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None:
def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -965,8 +976,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -975,7 +986,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -1018,8 +1030,8 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -1107,7 +1119,7 @@ def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
assert hyperopt.backtesting.strategy.buy_rsi.hyperopt is True
assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
assert hyperopt.backtesting.strategy.buy_rsi.value == 35
buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
assert isinstance(buy_rsi_range, range)
@@ -1132,3 +1144,17 @@ def test_SKDecimal():
assert space.transform([2.0]) == [200]
assert space.transform([1.0]) == [100]
assert space.transform([1.5, 1.6]) == [150, 160]
def test___pprint():
params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'}
non_params = {'buy_notoptimied': 55}
x = HyperoptTools._pprint(params, non_params)
assert x == """{
"buy_std": 1.2,
"buy_rsi": 31,
"buy_enable": True,
"buy_what": "asdf",
"buy_notoptimied": 55, # value loaded from strategy
}"""