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Merge pull request #1290 from freqtrade/fix/backtest_toomanyopen

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fix backtesting not respecting max_open_trades
This commit is contained in:
Matthias
2018-11-30 19:17:09 +01:00
committed by GitHub
parent 8effcc2de5 805f509498
commit 3ac2106a16
6 changed files with 159 additions and 49 deletions
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7
freqtrade/tests/optimize/__init__.py
View File

@@ -4,9 +4,10 @@ import arrow
from pandas import DataFrame
from freqtrade.strategy.interface import SellType
from freqtrade.constants import TICKER_INTERVAL_MINUTES
ticker_start_time = arrow.get(2018, 10, 3)
ticker_interval_in_minute = 60
tests_ticker_interval = "1h"
class BTrade(NamedTuple):
@@ -30,8 +31,8 @@ class BTContainer(NamedTuple):
def _get_frame_time_from_offset(offset):
return ticker_start_time.shift(
minutes=(offset * ticker_interval_in_minute)).datetime.replace(tzinfo=None)
return ticker_start_time.shift(minutes=(offset * TICKER_INTERVAL_MINUTES[tests_ticker_interval])
).datetime.replace(tzinfo=None)
def _build_backtest_dataframe(ticker_with_signals):

20
freqtrade/tests/optimize/test_backtest_detail.py
View File

@@ -6,10 +6,11 @@ from pandas import DataFrame
import pytest
from freqtrade.optimize import get_timeframe
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)
_get_frame_time_from_offset, tests_ticker_interval)
from freqtrade.tests.conftest import patch_exchange
@@ -147,6 +148,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
"""
default_conf["stoploss"] = data.stop_loss
default_conf["minimal_roi"] = {"0": data.roi}
default_conf['ticker_interval'] = tests_ticker_interval
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0))
patch_exchange(mocker)
frame = _build_backtest_dataframe(data.data)
@@ -158,29 +160,21 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
pair = 'UNITTEST/BTC'
# Dummy data as we mock the analyze functions
data_processed = {pair: DataFrame()}
min_date, max_date = get_timeframe({pair: frame})
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
'start_date': min_date,
'end_date': max_date,
}
)
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

130
freqtrade/tests/optimize/test_backtesting.py
View File

@@ -13,6 +13,7 @@ from arrow import Arrow
from freqtrade import DependencyException, constants, optimize
from freqtrade.arguments import Arguments, TimeRange
from freqtrade.optimize import get_timeframe
from freqtrade.optimize.backtesting import (Backtesting, setup_configuration,
start)
from freqtrade.tests.conftest import log_has, patch_exchange
@@ -86,17 +87,21 @@ def load_data_test(what):
def simple_backtest(config, contour, num_results, mocker) -> None:
patch_exchange(mocker)
config['ticker_interval'] = '1m'
backtesting = Backtesting(config)
data = load_data_test(contour)
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(processed)
assert isinstance(processed, dict)
results = backtesting.backtest(
{
'stake_amount': config['stake_amount'],
'processed': processed,
'max_open_trades': 1,
'position_stacking': False
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
)
# results :: <class 'pandas.core.frame.DataFrame'>
@@ -123,12 +128,16 @@ def _make_backtest_conf(mocker, conf=None, pair='UNITTEST/BTC', record=None):
data = trim_dictlist(data, -201)
patch_exchange(mocker)
backtesting = Backtesting(conf)
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(processed)
return {
'stake_amount': conf['stake_amount'],
'processed': backtesting.strategy.tickerdata_to_dataframe(data),
'processed': processed,
'max_open_trades': 10,
'position_stacking': False,
'record': record
'record': record,
'start_date': min_date,
'end_date': max_date,
}
@@ -449,7 +458,7 @@ def test_backtesting_start(default_conf, mocker, caplog) -> None:
)
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
default_conf['ticker_interval'] = "1m"
default_conf['ticker_interval'] = '1m'
default_conf['live'] = False
default_conf['datadir'] = None
default_conf['export'] = None
@@ -505,12 +514,15 @@ def test_backtest(default_conf, fee, mocker) -> None:
data = optimize.load_data(None, ticker_interval='5m', pairs=['UNITTEST/BTC'])
data = trim_dictlist(data, -200)
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(data_processed)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
'position_stacking': False
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
)
assert not results.empty
@@ -554,12 +566,16 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
# Run a backtesting for an exiting 5min ticker_interval
data = optimize.load_data(None, ticker_interval='1m', pairs=['UNITTEST/BTC'])
data = trim_dictlist(data, -200)
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(processed)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': backtesting.strategy.tickerdata_to_dataframe(data),
'processed': processed,
'max_open_trades': 1,
'position_stacking': False
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
)
assert not results.empty
@@ -583,25 +599,13 @@ def test_processed(default_conf, mocker) -> None:
def test_backtest_pricecontours(default_conf, fee, mocker) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
tests = [['raise', 18], ['lower', 0], ['sine', 19]]
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
for [contour, numres] in tests:
simple_backtest(default_conf, contour, numres, mocker)
# Test backtest using offline data (testdata directory)
def test_backtest_ticks(default_conf, fee, mocker):
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
ticks = [1, 5]
fun = Backtesting(default_conf).advise_buy
for _ in ticks:
backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
backtesting = Backtesting(default_conf)
backtesting.advise_buy = fun # Override
backtesting.advise_sell = fun # Override
results = backtesting.backtest(backtest_conf)
assert not results.empty
def test_backtest_clash_buy_sell(mocker, default_conf):
# Override the default buy trend function in our default_strategy
def fun(dataframe=None, pair=None):
@@ -636,14 +640,92 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch('freqtrade.optimize.backtesting.file_dump_json', MagicMock())
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, pair='UNITTEST/BTC')
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '1m'
backtesting = Backtesting(default_conf)
backtesting.advise_buy = _trend_alternate # Override
backtesting.advise_sell = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
backtesting._store_backtest_result("test_.json", results)
assert len(results) == 4
# 200 candles in backtest data
# won't buy on first (shifted by 1)
# 100 buys signals
assert len(results) == 99
# One trade was force-closed at the end
assert len(results.loc[results.open_at_end]) == 1
assert len(results.loc[results.open_at_end]) == 0
def test_backtest_multi_pair(default_conf, fee, mocker):
def evaluate_result_multi(results, freq, max_open_trades):
# Find overlapping trades by expanding each trade once per period
# and then counting overlaps
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
for row in results[['open_time', 'close_time']].iterrows()]
deltas = [len(x) for x in dates]
dates = pd.Series(pd.concat(dates).values, name='date')
df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns)
df2 = df2.astype(dtype={"open_time": "datetime64", "close_time": "datetime64"})
df2 = pd.concat([dates, df2], axis=1)
df2 = df2.set_index('date')
df_final = df2.resample(freq)[['pair']].count()
return df_final[df_final['pair'] > max_open_trades]
def _trend_alternate_hold(dataframe=None, metadata=None):
"""
Buy every 8th candle - sell every other 8th -2 (hold on to pairs a bit)
"""
multi = 8
dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
if metadata['pair'] in('ETH/BTC', 'LTC/BTC'):
dataframe['buy'] = dataframe['buy'].shift(-4)
dataframe['sell'] = dataframe['sell'].shift(-4)
return dataframe
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
data = optimize.load_data(None, ticker_interval='5m', pairs=pairs)
data = trim_dictlist(data, -500)
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '5m'
backtesting = Backtesting(default_conf)
backtesting.advise_buy = _trend_alternate_hold # Override
backtesting.advise_sell = _trend_alternate_hold # Override
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(data_processed)
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 3,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
results = backtesting.backtest(backtest_conf)
# Make sure we have parallel trades
assert len(evaluate_result_multi(results, '5min', 2)) > 0
# make sure we don't have trades with more than configured max_open_trades
assert len(evaluate_result_multi(results, '5min', 3)) == 0
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 1,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
results = backtesting.backtest(backtest_conf)
assert len(evaluate_result_multi(results, '5min', 1)) == 0
def test_backtest_record(default_conf, fee, mocker):

7
freqtrade/tests/optimize/test_hyperopt.py
View File

@@ -1,11 +1,12 @@
# pragma pylint: disable=missing-docstring,W0212,C0103
from datetime import datetime
import os
from unittest.mock import MagicMock
import pandas as pd
import pytest
from freqtrade.optimize.__init__ import load_tickerdata_file
from freqtrade.optimize import load_tickerdata_file
from freqtrade.optimize.hyperopt import Hyperopt, start
from freqtrade.resolvers import StrategyResolver
from freqtrade.tests.conftest import log_has, patch_exchange
@@ -293,6 +294,10 @@ def test_generate_optimizer(mocker, default_conf) -> None:
'freqtrade.optimize.hyperopt.Hyperopt.backtest',
MagicMock(return_value=backtest_result)
)
mocker.patch(
'freqtrade.optimize.hyperopt.get_timeframe',
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
)
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())