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Test open / close time - small refactorings

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This commit is contained in:
Matthias 2018-10-30 19:33:32 +01:00
parent 9065e79f53
commit b383113d6c
1 changed files with 63 additions and 56 deletions
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119
freqtrade/tests/optimize/test_backtest_detail.py
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@ -17,6 +17,12 @@ ticker_start_time = arrow.get(2018, 10, 3)
ticker_interval_in_minute = 60
class BTrade(NamedTuple):
sell_r: SellType
open_tick: int
close_tick: int
class BTContainer(NamedTuple):
"""
NamedTuple Defining BacktestResults inputs.
@ -24,71 +30,56 @@ class BTContainer(NamedTuple):
data: List[float]
stop_loss: float
roi: float
trades: int
trades: List[BTrade]
profit_perc: float
sell_r: SellType
def _get_frame_time(offset):
return ticker_start_time.shift(
minutes=(offset * ticker_interval_in_minute)).datetime
def _build_dataframe(ticker_with_signals):
columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
frame = DataFrame.from_records(ticker_with_signals, columns=columns)
frame['date'] = frame['date'].apply(lambda x: ticker_start_time.shift(
minutes=(x * ticker_interval_in_minute)).datetime)
frame['date'] = frame['date'].apply(_get_frame_time)
# Ensure floats are in place
for column in ['open', 'high', 'low', 'close', 'volume']:
frame[column] = frame[column].astype('float64')
return frame
data_profit = [
[0, 0.0009910, 0.001011, 0.00098618, 0.001000, 12345, 1, 0],
[1, 0.001000, 0.001010, 0.0009900, 0.0009900, 12345, 0, 0],
[2, 0.0009900, 0.001011, 0.00091618, 0.0009900, 12345, 0, 0],
[3, 0.001000, 0.001011, 0.00098618, 0.001100, 12345, 0, 1],
[4, 0.001000, 0.001011, 0.00098618, 0.0009900, 12345, 0, 0]]
tc_profit1 = BTContainer(data=data_profit, stop_loss=-0.01, roi=1, trades=1,
profit_perc=0.10557, sell_r=SellType.STOP_LOSS) # should be stoploss - drops 8%
tc_profit2 = BTContainer(data=data_profit, stop_loss=-0.10, roi=1,
trades=1, profit_perc=0.10557, sell_r=SellType.STOP_LOSS)
tc_loss0 = BTContainer(data=[
[0, 0.0009910, 0.001011, 0.00098618, 0.001000, 12345, 1, 0],
[1, 0.001000, 0.001010, 0.0009900, 0.001000, 12345, 0, 0],
[2, 0.001000, 0.001011, 0.0010618, 0.00091618, 12345, 0, 0],
[3, 0.001000, 0.001011, 0.00098618, 0.00091618, 12345, 0, 0],
[4, 0.001000, 0.001011, 0.00098618, 0.00091618, 12345, 0, 0]],
stop_loss=-0.05, roi=1, trades=1, profit_perc=-0.08839, sell_r=SellType.STOP_LOSS)
# Test 1 Minus 8% Close
# Candle Data for test 1 – close at -8% (9200)
# Test with Stop-loss at 1%
# TC1: Stop-Loss Triggered 1% loss
tc1 = BTContainer(data=[
tc0 = BTContainer(data=[
[0, 10000.0, 10050, 9950, 9975, 12345, 1, 0],
[1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle)
[2, 9975, 10025, 9200, 9200, 12345, 0, 0], # Exit with stoploss hit
[3, 9950, 10000, 9960, 9955, 12345, 0, 0],
[4, 9955, 9975, 9955, 9990, 12345, 0, 0],
[5, 9990, 9990, 9990, 9900, 12345, 0, 0]],
stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sell_r=SellType.STOP_LOSS)
stop_loss=-0.01, roi=1, profit_perc=-0.01,
trades=[BTrade(sell_r=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
# Test 2 Minus 4% Low, minus 1% close
# Candle Data for test 2
# Test with Stop-Loss at 3%
# TC2: Stop-Loss Triggered 3% Loss
tc2 = BTContainer(data=[
tc1 = BTContainer(data=[
[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
[1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle)
[2, 9975, 10025, 9925, 9950, 12345, 0, 0],
[3, 9950, 10000, 9600, 9925, 12345, 0, 0], # Exit with stoploss hit
[4, 9925, 9975, 9875, 9900, 12345, 0, 0],
[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.03, sell_r=SellType.STOP_LOSS)
stop_loss=-0.03, roi=1, profit_perc=-0.03,
trades=[BTrade(sell_r=SellType.STOP_LOSS, open_tick=1, close_tick=3)]
)
# Test 3 Candle drops 4%, Recovers 1%.
@ -98,79 +89,90 @@ tc2 = BTContainer(data=[
# Test with Stop-Loss at 2%
# TC3: Trade-A: Stop-Loss Triggered 2% Loss
# Trade-B: Stop-Loss Triggered 2% Loss
tc3 = BTContainer(data=[
tc2 = BTContainer(data=[
[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
[1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle)
[2, 9975, 10025, 9600, 9950, 12345, 0, 0],
[3, 9950, 10000, 9900, 9925, 12345, 1, 0], # enter trade 2 (signal on last candle)
[4, 9950, 10000, 9900, 9925, 12345, 0, 0],
[3, 9950, 10000, 9900, 9925, 12345, 1, 0],
[4, 9950, 10000, 9900, 9925, 12345, 0, 0], # enter trade 2 (signal on last candle)
[5, 9925, 9975, 8000, 8000, 12345, 0, 0],
[6, 9900, 9950, 9950, 9900, 12345, 0, 0]],
stop_loss=-0.02, roi=1, trades=2, profit_perc=-0.04, sell_r=SellType.STOP_LOSS)
stop_loss=-0.02, roi=1, profit_perc=-0.04,
trades=[BTrade(sell_r=SellType.STOP_LOSS, open_tick=1, close_tick=2),
BTrade(sell_r=SellType.STOP_LOSS, open_tick=4, close_tick=5)]
)
# Test 4 Minus 3% / recovery +15%
# Candle Data for test 4 – Candle drops 3% Closed 15% up
# Test with Stop-loss at 2% ROI 6%
# TC4: Stop-Loss Triggered 2% Loss
tc4 = BTContainer(data=[
tc3 = BTContainer(data=[
[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
[1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle)
[2, 9975, 11500, 9700, 11500, 12345, 0, 0],
[3, 9950, 10000, 9900, 9925, 12345, 0, 0],
[4, 9925, 9975, 9875, 9900, 12345, 0, 0], # Exit with stoploss hit
[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS)
stop_loss=-0.02, roi=0.06, profit_perc=-0.02,
trades=[BTrade(sell_r=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
# Test 5 / Drops 0.5% Closes +20%
# Candle Data for test 5
# Set stop-loss at 1% ROI 3%
# TC5: ROI triggers 3% Gain
tc5 = BTContainer(data=[
tc4 = BTContainer(data=[
[0, 10000, 10050, 9960, 9975, 12345, 1, 0],
[1, 10000, 10050, 9960, 9975, 12345, 0, 0], # enter trade (signal on last candle)
[2, 9975, 10050, 9950, 9975, 12345, 0, 0],
[3, 9950, 12000, 9950, 12000, 12345, 0, 0], # ROI
[4, 9925, 9975, 9945, 9900, 12345, 0, 0],
[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
stop_loss=-0.01, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI)
stop_loss=-0.01, roi=0.03, profit_perc=0.03,
trades=[BTrade(sell_r=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
tc6 = BTContainer(data=[
tc5 = BTContainer(data=[
[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
[1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle)
[2, 9975, 10600, 9700, 10100, 12345, 0, 0], # Exit with stoploss
[3, 9950, 10000, 9900, 9925, 12345, 0, 0],
[4, 9925, 9975, 9945, 9900, 12345, 0, 0],
[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS)
stop_loss=-0.02, roi=0.05, profit_perc=-0.02,
trades=[BTrade(sell_r=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
tc7 = BTContainer(data=[
tc6 = BTContainer(data=[
[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
[1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle)
[2, 9975, 10600, 9900, 10100, 12345, 0, 0], # ROI
[3, 9950, 10000, 9900, 9925, 12345, 0, 0],
[4, 9925, 9975, 9945, 9900, 12345, 0, 0],
[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
stop_loss=-0.02, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI)
stop_loss=-0.02, roi=0.03, profit_perc=0.03,
trades=[BTrade(sell_r=SellType.ROI, open_tick=1, close_tick=2)]
)
TESTS = [
# tc_profit1,
# tc_profit2,
# tc_loss0,
tc0,
tc1,
tc2,
tc3,
tc4,
tc5,
tc6,
tc7,
]
@ -203,17 +205,22 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
)
print(results.T)
assert len(results) == data.trades
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)
# 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_r
assert res.open_time == _get_frame_time(trade.open_tick)
assert res.close_time == _get_frame_time(trade.close_tick)