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minor changes

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gcarq 2017-11-25 03:28:52 +01:00
parent 68521ea46c
commit 0c35e6ad19
2 changed files with 7 additions and 6 deletions
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1
freqtrade/analyze.py
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@ -15,6 +15,7 @@ from freqtrade.vendor.qtpylib.indicators import awesome_oscillator, crossed_abov
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
class SignalType(Enum): class SignalType(Enum):
""" Enum to distinguish between buy and sell signals """ """ Enum to distinguish between buy and sell signals """
BUY = "buy" BUY = "buy"

12
freqtrade/optimize/hyperopt.py
View File

@ -16,12 +16,15 @@ from freqtrade.exchange import Bittrex
from freqtrade.optimize.backtesting import backtest from freqtrade.optimize.backtesting import backtest
from freqtrade.vendor.qtpylib.indicators import crossed_above from freqtrade.vendor.qtpylib.indicators import crossed_above
# Remove noisy log messages
logging.getLogger('hyperopt.mongoexp').setLevel(logging.WARNING)
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
# set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data # set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
TARGET_TRADES = 1100 TARGET_TRADES = 1100
TOTAL_TRIES = 4 TOTAL_TRIES = None
_CURRENT_TRIES = 0 _CURRENT_TRIES = 0
# Configuration and data used by hyperopt # Configuration and data used by hyperopt
@ -188,8 +191,8 @@ def start(args):
) )
if args.mongodb: if args.mongodb:
logger.info('Using mongodb.') logger.info('Using mongodb ...')
logger.info('Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually') logger.info('Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!')
db_name = 'freqtrade_hyperopt' db_name = 'freqtrade_hyperopt'
trials = MongoTrials('mongo://127.0.0.1:1234/{}/jobs'.format(db_name), exp_key='exp1') trials = MongoTrials('mongo://127.0.0.1:1234/{}/jobs'.format(db_name), exp_key='exp1')
@ -197,9 +200,6 @@ def start(args):
trials = Trials() trials = Trials()
best = fmin(fn=optimizer, space=SPACE, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials) best = fmin(fn=optimizer, space=SPACE, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
logger.info(
'\n==================== HYPEROPT BACKTESTING REPORT ==============================\n'
)
logger.info('Best parameters:\n%s', json.dumps(best, indent=4)) logger.info('Best parameters:\n%s', json.dumps(best, indent=4))
results = sorted(trials.results, key=itemgetter('loss')) results = sorted(trials.results, key=itemgetter('loss'))
logger.info('Best Result:\n%s', results[0]['result']) logger.info('Best Result:\n%s', results[0]['result'])