freqtrade_origin/freqtrade/tests/optimize/test_backtest_detail.py
2018-11-01 13:16:10 +01:00

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# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
import logging
from unittest.mock import MagicMock
from pandas import DataFrame
import pytest
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.strategy.interface import SellType
from freqtrade.tests.optimize import (BTrade, BTContainer, _build_backtest_dataframe,
_get_frame_time_from_offset)
from freqtrade.tests.conftest import patch_exchange
# Test 0 Minus 8% Close
# Test with Stop-loss at 1%
# TC1: Stop-Loss Triggered 1% loss
tc0 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
[2, 4987, 5012, 4600, 4600, 6172, 0, 0], # exit with stoploss hit
[3, 4975, 5000, 4980, 4977, 6172, 0, 0],
[4, 4977, 4987, 4977, 4995, 6172, 0, 0],
[5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
stop_loss=-0.01, roi=1, profit_perc=-0.01,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
# Test 1 Minus 4% Low, minus 1% close
# Test with Stop-Loss at 3%
# TC2: Stop-Loss Triggered 3% Loss
tc1 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
[2, 4987, 5012, 4962, 4975, 6172, 0, 0],
[3, 4975, 5000, 4800, 4962, 6172, 0, 0], # exit with stoploss hit
[4, 4962, 4987, 4937, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.03, roi=1, profit_perc=-0.03,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=3)]
)
# Test 3 Candle drops 4%, Recovers 1%.
# Entry Criteria Met
# Candle drops 20%
# Candle Data for test 3
# Test with Stop-Loss at 2%
# TC3: Trade-A: Stop-Loss Triggered 2% Loss
# Trade-B: Stop-Loss Triggered 2% Loss
tc2 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
[2, 4987, 5012, 4800, 4975, 6172, 0, 0], # exit with stoploss hit
[3, 4975, 5000, 4950, 4962, 6172, 1, 0],
[4, 4975, 5000, 4950, 4962, 6172, 0, 0], # enter trade 2 (signal on last candle)
[5, 4962, 4987, 4000, 4000, 6172, 0, 0], # exit with stoploss hit
[6, 4950, 4975, 4975, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=1, profit_perc=-0.04,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2),
BTrade(sell_reason=SellType.STOP_LOSS, open_tick=4, close_tick=5)]
)
# Test 4 Minus 3% / recovery +15%
# Candle Data for test 3 Candle drops 3% Closed 15% up
# Test with Stop-loss at 2% ROI 6%
# TC4: Stop-Loss Triggered 2% Loss
tc3 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
[2, 4987, 5750, 4850, 5750, 6172, 0, 0], # Exit with stoploss hit
[3, 4975, 5000, 4950, 4962, 6172, 0, 0],
[4, 4962, 4987, 4937, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=0.06, profit_perc=-0.02,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
# Test 4 / Drops 0.5% Closes +20%
# Set stop-loss at 1% ROI 3%
# TC5: ROI triggers 3% Gain
tc4 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4980, 4987, 6172, 1, 0],
[1, 5000, 5025, 4980, 4987, 6172, 0, 0], # enter trade (signal on last candle)
[2, 4987, 5025, 4975, 4987, 6172, 0, 0],
[3, 4975, 6000, 4975, 6000, 6172, 0, 0], # ROI
[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.01, roi=0.03, profit_perc=0.03,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
)
# Test 6 / Drops 3% / Recovers 6% Positive / Closes 1% positve
# Candle Data for test 6
# Set stop-loss at 2% ROI at 5%
# TC6: Stop-Loss triggers 2% Loss
tc5 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
[2, 4987, 5300, 4850, 5050, 6172, 0, 0], # Exit with stoploss
[3, 4975, 5000, 4950, 4962, 6172, 0, 0],
[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=0.05, profit_perc=-0.02,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
# Test 7 - 6% Positive / 1% Negative / Close 1% Positve
# Candle Data for test 7
# Set stop-loss at 2% ROI at 3%
# TC7: ROI Triggers 3% Gain
tc6 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0],
[2, 4987, 5300, 4950, 5050, 6172, 0, 0],
[3, 4975, 5000, 4950, 4962, 6172, 0, 0],
[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=0.03, profit_perc=0.03,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
)
TESTS = [
tc0,
tc1,
tc2,
tc3,
tc4,
tc5,
tc6,
]
@pytest.mark.parametrize("data", TESTS)
def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
"""
run functional tests
"""
default_conf["stoploss"] = data.stop_loss
default_conf["minimal_roi"] = {"0": data.roi}
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0))
patch_exchange(mocker)
frame = _build_backtest_dataframe(data.data)
backtesting = Backtesting(default_conf)
backtesting.advise_buy = lambda a, m: frame
backtesting.advise_sell = lambda a, m: frame
caplog.set_level(logging.DEBUG)
pair = 'UNITTEST/BTC'
# Dummy data as we mock the analyze functions
data_processed = {pair: DataFrame()}
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
}
)
print(results.T)
assert len(results) == len(data.trades)
assert round(results["profit_percent"].sum(), 3) == round(data.profit_perc, 3)
# if data.sell_r == SellType.STOP_LOSS:
# assert log_has("Stop loss hit.", caplog.record_tuples)
# else:
# assert not log_has("Stop loss hit.", caplog.record_tuples)
# log_test = (f'Force_selling still open trade UNITTEST/BTC with '
# f'{results.iloc[-1].profit_percent} perc - {results.iloc[-1].profit_abs}')
# if data.sell_r == SellType.FORCE_SELL:
# assert log_has(log_test,
# caplog.record_tuples)
# else:
# assert not log_has(log_test,
# caplog.record_tuples)
for c, trade in enumerate(data.trades):
res = results.iloc[c]
assert res.sell_reason == trade.sell_reason
assert res.open_time == _get_frame_time_from_offset(trade.open_tick)
assert res.close_time == _get_frame_time_from_offset(trade.close_tick)