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avoid re-serialization of whole dataframe

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This commit is contained in:
Janne Sinivirta 2018-07-03 14:46:16 +03:00
parent 4a26b88a17
commit ee4754cfb9
1 changed files with 7 additions and 5 deletions
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12
freqtrade/optimize/hyperopt.py
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@ -14,14 +14,14 @@ from argparse import Namespace
from functools import reduce from functools import reduce
from math import exp from math import exp
from operator import itemgetter from operator import itemgetter
from typing import Dict, Any, Callable, Optional, List from typing import Dict, Any, Callable, List
import talib.abstract as ta import talib.abstract as ta
from pandas import DataFrame from pandas import DataFrame
from skopt.space import Real, Integer, Categorical, Dimension from skopt.space import Real, Integer, Categorical, Dimension
from skopt import Optimizer from skopt import Optimizer
from sklearn.externals.joblib import Parallel, delayed from sklearn.externals.joblib import Parallel, delayed, load, dump
import freqtrade.vendor.qtpylib.indicators as qtpylib import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.arguments import Arguments from freqtrade.arguments import Arguments
@ -32,6 +32,7 @@ from freqtrade.optimize.backtesting import Backtesting
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
MAX_LOSS = 100000 # just a big enough number to be bad result in loss optimization MAX_LOSS = 100000 # just a big enough number to be bad result in loss optimization
TICKERDATA_PICKLE = os.path.join('user_data', 'hyperopt_tickerdata.pkl')
class Hyperopt(Backtesting): class Hyperopt(Backtesting):
@ -60,7 +61,7 @@ class Hyperopt(Backtesting):
self.expected_max_profit = 3.0 self.expected_max_profit = 3.0
# Configuration and data used by hyperopt # Configuration and data used by hyperopt
self.processed: Optional[Dict[str, Any]] = None # self.processed: Optional[Dict[str, Any]] = None
# Previous evaluations # Previous evaluations
self.trials_file = os.path.join('user_data', 'hyperopt_trials.pickle') self.trials_file = os.path.join('user_data', 'hyperopt_trials.pickle')
@ -281,10 +282,11 @@ class Hyperopt(Backtesting):
if self.has_space('stoploss'): if self.has_space('stoploss'):
self.analyze.strategy.stoploss = params['stoploss'] self.analyze.strategy.stoploss = params['stoploss']
processed = load(TICKERDATA_PICKLE)
results = self.backtest( results = self.backtest(
{ {
'stake_amount': self.config['stake_amount'], 'stake_amount': self.config['stake_amount'],
'processed': self.processed, 'processed': processed,
'realistic': self.config.get('realistic_simulation', False), 'realistic': self.config.get('realistic_simulation', False),
} }
) )
@ -356,7 +358,7 @@ class Hyperopt(Backtesting):
if self.has_space('buy'): if self.has_space('buy'):
self.analyze.populate_indicators = Hyperopt.populate_indicators # type: ignore self.analyze.populate_indicators = Hyperopt.populate_indicators # type: ignore
self.processed = self.tickerdata_to_dataframe(data) dump(self.tickerdata_to_dataframe(data), TICKERDATA_PICKLE)
self.exchange = None # type: ignore self.exchange = None # type: ignore
self.load_previous_results() self.load_previous_results()