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average trade duration added

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This commit is contained in:
misagh 2018-10-18 11:09:10 +02:00
parent 6aa9cd1060
commit 57bc4a866a
1 changed files with 14 additions and 6 deletions
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20
freqtrade/edge/__init__.py
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@ -14,6 +14,7 @@ from freqtrade.arguments import TimeRange
from freqtrade.strategy.interface import SellType
from freqtrade.strategy.resolver import IStrategy, StrategyResolver
from freqtrade.optimize.backtesting import Backtesting
import sys
logger = logging.getLogger(__name__)
@ -31,6 +32,7 @@ class Edge():
_timerange: TimeRange
def __init__(self, config: Dict[str, Any], exchange=None) -> None:
sys.setrecursionlimit(10000)
self.config = config
self.exchange = exchange
self.strategy: IStrategy = StrategyResolver(self.config).strategy
@ -68,7 +70,7 @@ class Edge():
self.config['datadir'],
pairs=pairs,
ticker_interval=self.ticker_interval,
refresh_pairs=True,
refresh_pairs=False,
exchange=self.exchange,
timerange=self._timerange
)
@ -272,13 +274,19 @@ class Edge():
return x
##############################
final = results.groupby(['pair', 'stoploss'])['profit_abs'].\
agg([winrate, risk_reward_ratio, required_risk_reward, expectancy]).\
reset_index().sort_values(by=['expectancy', 'stoploss'], ascending=False)\
.groupby('pair').first().sort_values(by=['expectancy'], ascending=False)
if results.empty:
return []
groupby_aggregator = {'profit_abs': [winrate, risk_reward_ratio, required_risk_reward, expectancy, 'count'], 'trade_duration': ['mean']}
final = results.groupby(['pair', 'stoploss'])['profit_abs','trade_duration'].agg(groupby_aggregator).reset_index(col_level=1)
final.columns = final.columns.droplevel(0)
final = final.sort_values(by=['expectancy', 'stoploss'], ascending=False).groupby(
'pair').first().sort_values(by=['expectancy'], ascending=False).reset_index()
final.rename(columns={'mean': 'avg_duration(min)'}, inplace=True)
# Returning an array of pairs in order of "expectancy"
return final.reset_index().values
return final.values
def _find_trades_for_stoploss_range(self, ticker_data, pair, stoploss_range):
buy_column = ticker_data['buy'].values