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filter nan values from total_profit and avg_profit

This commit is contained in:
Samuel Husso 2017-12-23 09:21:04 +02:00
parent b6dd9dd227
commit 8d93363655
1 changed files with 14 additions and 2 deletions
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16
freqtrade/optimize/hyperopt.py
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@ -11,6 +11,7 @@ from operator import itemgetter
from hyperopt import fmin, tpe, hp, Trials, STATUS_OK from hyperopt import fmin, tpe, hp, Trials, STATUS_OK
from hyperopt.mongoexp import MongoTrials from hyperopt.mongoexp import MongoTrials
from pandas import DataFrame from pandas import DataFrame
import numpy as np
from freqtrade import exchange, optimize from freqtrade import exchange, optimize
from freqtrade.exchange import Bittrex from freqtrade.exchange import Bittrex
@ -148,7 +149,9 @@ def optimizer(params):
return { return {
'loss': trade_loss + profit_loss, 'loss': trade_loss + profit_loss,
'status': STATUS_OK, 'status': STATUS_OK,
'result': result 'result': result,
'total_profit': total_profit,
'avg_profit': result_data['avg_profit'],
} }
@ -162,6 +165,10 @@ def format_results(results: DataFrame):
) )
def filter_nan(result, filter_key):
return [r for r in result if not np.isnan(r[filter_key])]
def buy_strategy_generator(params): def buy_strategy_generator(params):
def populate_buy_trend(dataframe: DataFrame) -> DataFrame: def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
conditions = [] conditions = []
@ -236,5 +243,10 @@ def start(args):
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('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'))
filt_res = filter_nan(trials.results, 'total_profit')
filt_res = filter_nan(filt_res, 'avg_profit')
results = sorted(filt_res, key=itemgetter('loss'))
logger.info('Best Result:\n%s', results[0]['result']) logger.info('Best Result:\n%s', results[0]['result'])