adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

remove duplicated backtesting from hyperopt

Browse Source
This commit is contained in:
Samuel Husso 2017-10-25 08:17:17 +03:00
parent f43ba44b15
commit 041e201713
1 changed files with 6 additions and 45 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

51
freqtrade/tests/test_hyperopt.py
View File

@ -35,44 +35,6 @@ def conf():
"stoploss": -0.05 "stoploss": -0.05
} }
def backtest2(conf, pairs, mocker, buy_strategy):
trades = []
mocker.patch.dict('freqtrade.main._CONF', conf)
for pair in pairs:
with open('freqtrade/tests/testdata/'+pair+'.json') as data_file:
data = json.load(data_file)
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=data)
mocker.patch('arrow.utcnow', return_value=arrow.get('2017-08-20T14:50:00'))
mocker.patch('freqtrade.analyze.populate_buy_trend', side_effect=buy_strategy)
ticker = analyze_ticker(pair)
# for each buy point
for index, row in ticker[ticker.buy == 1].iterrows():
trade = Trade(
open_rate=row['close'],
open_date=arrow.get(row['date']).datetime,
amount=1,
)
# calculate win/lose forwards from buy point
for index2, row2 in ticker[index:].iterrows():
if should_sell(trade, row2['close'], arrow.get(row2['date']).datetime):
current_profit = (row2['close'] - trade.open_rate) / trade.open_rate
trades.append((pair, current_profit, index2 - index))
break
labels = ['currency', 'profit', 'duration']
results = DataFrame.from_records(trades, columns=labels)
print_results(results)
# set the value below to suit your number concurrent trades so its realistic to 20days of data
TARGET_TRADES = 1200
if results.profit.sum() == 0 or results.profit.mean() == 0:
return 49999999999 # avoid division by zero, return huge value to discard result
return abs(len(results.index) - 1200.1) / (results.profit.sum() ** 2) * results.duration.mean() # the smaller the better
def buy_strategy_generator(params): def buy_strategy_generator(params):
print(params) print(params)
def populate_buy_trend(dataframe: DataFrame) -> DataFrame: def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
@ -114,19 +76,18 @@ def buy_strategy_generator(params):
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set") @pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_hyperopt(conf, pairs, mocker): def test_hyperopt(conf, pairs, mocker):
# def optimizer(params):
# return backtest2(conf, pairs, mocker, buy_strategy_generator(params))
def optimizer(params): def optimizer(params):
buy_strategy = buy_strategy_generator(params) buy_strategy = buy_strategy_generator(params)
mocker.patch('freqtrade.analyze.populate_buy_trend', side_effect=buy_strategy) mocker.patch('freqtrade.analyze.populate_buy_trend', side_effect=buy_strategy)
results = backtest(conf, pairs, mocker) results = backtest(conf, pairs, mocker)
print_results(results) print_results(results)
if len(results.index) < 800: # require at least 800 trades
return 100000 # return large number to "ignore" this result # set the value below to suit your number concurrent trades so its realistic to 20days of data
return results.duration.mean() ** 3 / results.profit.sum() / results.profit.mean() # the smaller the better TARGET_TRADES = 1200
if results.profit.sum() == 0 or results.profit.mean() == 0:
return 49999999999 # avoid division by zero, return huge value to discard result
return abs(len(results.index) - 1200.1) / (results.profit.sum() ** 2) * results.duration.mean() # the smaller the better
space = { space = {
'mfi': hp.choice('mfi', [ 'mfi': hp.choice('mfi', [