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extract Find parallel trades per interval

This commit is contained in:
Matthias 2019-10-30 13:35:55 +01:00
parent 669a6cf119
commit dac88c6aed
2 changed files with 27 additions and 11 deletions
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32
freqtrade/data/btanalysis.py
View File

@ -52,16 +52,17 @@ def load_backtest_data(filename) -> pd.DataFrame:
return df return df
def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int) -> pd.DataFrame: def parallel_trade_analysis(results: pd.DataFrame, timeframe: str) -> pd.DataFrame:
""" """
Find overlapping trades by expanding each trade once per period it was open Find overlapping trades by expanding each trade once per period it was open
and then counting overlaps and then counting overlaps.
:param results: Results Dataframe - can be loaded :param results: Results Dataframe - can be loaded
:param freq: Frequency used for the backtest :param timeframe: Timeframe used for backtest
:param max_open_trades: parameter max_open_trades used during backtest run :return: dataframe with open-counts per time-period in timeframe
:return: dataframe with open-counts per time-period in freq
""" """
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq)) from freqtrade.exchange import timeframe_to_minutes
timeframe_min = timeframe_to_minutes(timeframe)
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=f"{timeframe_min}min"))
for row in results[['open_time', 'close_time']].iterrows()] for row in results[['open_time', 'close_time']].iterrows()]
deltas = [len(x) for x in dates] deltas = [len(x) for x in dates]
dates = pd.Series(pd.concat(dates).values, name='date') dates = pd.Series(pd.concat(dates).values, name='date')
@ -69,8 +70,23 @@ def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int
df2 = pd.concat([dates, df2], axis=1) df2 = pd.concat([dates, df2], axis=1)
df2 = df2.set_index('date') df2 = df2.set_index('date')
df_final = df2.resample(freq)[['pair']].count() df_final = df2.resample(f"{timeframe_min}min")[['pair']].count()
return df_final[df_final['pair'] > max_open_trades] df_final = df_final.rename({'pair': 'open_trades'}, axis=1)
return df_final
def evaluate_result_multi(results: pd.DataFrame, timeframe: str,
max_open_trades: int) -> pd.DataFrame:
"""
Find overlapping trades by expanding each trade once per period it was open
and then counting overlaps
:param results: Results Dataframe - can be loaded
:param timeframe: Frequency used for the backtest
:param max_open_trades: parameter max_open_trades used during backtest run
:return: dataframe with open-counts per time-period in freq
"""
df_final = parallel_trade_analysis(results, timeframe)
return df_final[df_final['open_trades'] > max_open_trades]
def load_trades_from_db(db_url: str) -> pd.DataFrame: def load_trades_from_db(db_url: str) -> pd.DataFrame:

6
tests/optimize/test_backtesting.py
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@ -714,9 +714,9 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
results = backtesting.backtest(backtest_conf) results = backtesting.backtest(backtest_conf)
# Make sure we have parallel trades # Make sure we have parallel trades
assert len(evaluate_result_multi(results, '5min', 2)) > 0 assert len(evaluate_result_multi(results, '5m', 2)) > 0
# make sure we don't have trades with more than configured max_open_trades # make sure we don't have trades with more than configured max_open_trades
assert len(evaluate_result_multi(results, '5min', 3)) == 0 assert len(evaluate_result_multi(results, '5m', 3)) == 0
backtest_conf = { backtest_conf = {
'stake_amount': default_conf['stake_amount'], 'stake_amount': default_conf['stake_amount'],
@ -727,7 +727,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
'end_date': max_date, 'end_date': max_date,
} }
results = backtesting.backtest(backtest_conf) results = backtesting.backtest(backtest_conf)
assert len(evaluate_result_multi(results, '5min', 1)) == 0 assert len(evaluate_result_multi(results, '5m', 1)) == 0
def test_backtest_record(default_conf, fee, mocker): def test_backtest_record(default_conf, fee, mocker):