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Merge pull request #400 from gcarq/feature/custom_strategy

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Allow custom strategy files
This commit is contained in:
Janne Sinivirta
2018-01-23 15:25:18 +02:00
committed by GitHub
parent b11fe2f814 5c499d16a5
commit a6cbc1ba16
26 changed files with 1464 additions and 434 deletions
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3
freqtrade/optimize/__init__.py
View File

@@ -6,9 +6,10 @@ import os
from typing import Optional, List, Dict
from pandas import DataFrame
from freqtrade.exchange import get_ticker_history
from freqtrade.optimize.hyperopt_conf import hyperopt_optimize_conf
from freqtrade.analyze import populate_indicators, parse_ticker_dataframe
from freqtrade import misc
from user_data.hyperopt_conf import hyperopt_optimize_conf
logger = logging.getLogger(__name__)

8
freqtrade/optimize/backtesting.py
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@@ -14,6 +14,7 @@ from freqtrade.analyze import populate_buy_trend, populate_sell_trend
from freqtrade.exchange import Bittrex
from freqtrade.main import min_roi_reached
from freqtrade.persistence import Trade
from freqtrade.strategy.strategy import Strategy
logger = logging.getLogger(__name__)
@@ -199,6 +200,11 @@ def start(args):
logger.info('Using max_open_trades: %s ...', config['max_open_trades'])
max_open_trades = config['max_open_trades']
# init the strategy to use
config.update({'strategy': args.strategy})
strategy = Strategy()
strategy.init(config)
# Monkey patch config
from freqtrade import main
main._CONF = config
@@ -216,7 +222,7 @@ def start(args):
'realistic': args.realistic_simulation,
'sell_profit_only': sell_profit_only,
'use_sell_signal': use_sell_signal,
'stoploss': config.get('stoploss'),
'stoploss': strategy.stoploss,
'record': args.export
})
logger.info(

135
freqtrade/optimize/hyperopt.py
View File

@@ -7,11 +7,10 @@ import sys
import pickle
import signal
import os
from functools import reduce
from math import exp
from operator import itemgetter
from hyperopt import STATUS_FAIL, STATUS_OK, Trials, fmin, hp, space_eval, tpe
from hyperopt import STATUS_FAIL, STATUS_OK, Trials, fmin, space_eval, tpe
from hyperopt.mongoexp import MongoTrials
from pandas import DataFrame
@@ -20,8 +19,8 @@ from freqtrade import exchange, optimize
from freqtrade.exchange import Bittrex
from freqtrade.misc import load_config
from freqtrade.optimize.backtesting import backtest
from freqtrade.optimize.hyperopt_conf import hyperopt_optimize_conf
from freqtrade.vendor.qtpylib.indicators import crossed_above
from freqtrade.strategy.strategy import Strategy
from user_data.hyperopt_conf import hyperopt_optimize_conf
# Remove noisy log messages
logging.getLogger('hyperopt.mongoexp').setLevel(logging.WARNING)
@@ -49,7 +48,7 @@ PROCESSED = None # optimize.preprocess(optimize.load_data())
OPTIMIZE_CONFIG = hyperopt_optimize_conf()
# Hyperopt Trials
TRIALS_FILE = os.path.join('freqtrade', 'optimize', 'hyperopt_trials.pickle')
TRIALS_FILE = os.path.join('user_data', 'hyperopt_trials.pickle')
TRIALS = Trials()
# Monkey patch config
@@ -57,63 +56,6 @@ from freqtrade import main # noqa
main._CONF = OPTIMIZE_CONFIG
SPACE = {
'macd_below_zero': hp.choice('macd_below_zero', [
{'enabled': False},
{'enabled': True}
]),
'mfi': hp.choice('mfi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('mfi-value', 5, 25, 1)}
]),
'fastd': hp.choice('fastd', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('fastd-value', 10, 50, 1)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)}
]),
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]),
'uptrend_long_ema': hp.choice('uptrend_long_ema', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_short_ema': hp.choice('uptrend_short_ema', [
{'enabled': False},
{'enabled': True}
]),
'over_sar': hp.choice('over_sar', [
{'enabled': False},
{'enabled': True}
]),
'green_candle': hp.choice('green_candle', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_sma': hp.choice('uptrend_sma', [
{'enabled': False},
{'enabled': True}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'lower_bb_tema'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema3_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'ht_sine'},
{'type': 'heiken_reversal_bull'},
{'type': 'di_cross'},
]),
'stoploss': hp.uniform('stoploss', -0.5, -0.02),
}
def save_trials(trials, trials_path=TRIALS_FILE):
"""Save hyperopt trials to file"""
logger.info('Saving Trials to \'{}\''.format(trials_path))
@@ -162,7 +104,9 @@ def optimizer(params):
global _CURRENT_TRIES
from freqtrade.optimize import backtesting
backtesting.populate_buy_trend = buy_strategy_generator(params)
strategy = Strategy()
backtesting.populate_buy_trend = strategy.buy_strategy_generator(params)
results = backtest({'stake_amount': OPTIMIZE_CONFIG['stake_amount'],
'processed': PROCESSED,
@@ -209,58 +153,8 @@ def format_results(results: DataFrame):
)
def buy_strategy_generator(params):
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if params['uptrend_long_ema']['enabled']:
conditions.append(dataframe['ema50'] > dataframe['ema100'])
if params['macd_below_zero']['enabled']:
conditions.append(dataframe['macd'] < 0)
if params['uptrend_short_ema']['enabled']:
conditions.append(dataframe['ema5'] > dataframe['ema10'])
if params['mfi']['enabled']:
conditions.append(dataframe['mfi'] < params['mfi']['value'])
if params['fastd']['enabled']:
conditions.append(dataframe['fastd'] < params['fastd']['value'])
if params['adx']['enabled']:
conditions.append(dataframe['adx'] > params['adx']['value'])
if params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value'])
if params['over_sar']['enabled']:
conditions.append(dataframe['close'] > dataframe['sar'])
if params['green_candle']['enabled']:
conditions.append(dataframe['close'] > dataframe['open'])
if params['uptrend_sma']['enabled']:
prevsma = dataframe['sma'].shift(1)
conditions.append(dataframe['sma'] > prevsma)
# TRIGGERS
triggers = {
'lower_bb': (dataframe['close'] < dataframe['bb_lowerband']),
'lower_bb_tema': (dataframe['tema'] < dataframe['bb_lowerband']),
'faststoch10': (crossed_above(dataframe['fastd'], 10.0)),
'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
'ema3_cross_ema10': (crossed_above(dataframe['ema3'], dataframe['ema10'])),
'macd_cross_signal': (crossed_above(dataframe['macd'], dataframe['macdsignal'])),
'sar_reversal': (crossed_above(dataframe['close'], dataframe['sar'])),
'ht_sine': (crossed_above(dataframe['htleadsine'], dataframe['htsine'])),
'heiken_reversal_bull': (crossed_above(dataframe['ha_close'], dataframe['ha_open'])) &
(dataframe['ha_low'] == dataframe['ha_open']),
'di_cross': (crossed_above(dataframe['plus_di'], dataframe['minus_di'])),
}
conditions.append(triggers.get(params['trigger']['type']))
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
return dataframe
return populate_buy_trend
def start(args):
global TOTAL_TRIES, PROCESSED, SPACE, TRIALS, _CURRENT_TRIES
global TOTAL_TRIES, PROCESSED, TRIALS, _CURRENT_TRIES
TOTAL_TRIES = args.epochs
@@ -275,6 +169,12 @@ def start(args):
logger.info('Using config: %s ...', args.config)
config = load_config(args.config)
pairs = config['exchange']['pair_whitelist']
# init the strategy to use
config.update({'strategy': args.strategy})
strategy = Strategy()
strategy.init(config)
timerange = misc.parse_timerange(args.timerange)
data = optimize.load_data(args.datadir, pairs=pairs,
ticker_interval=args.ticker_interval,
@@ -303,7 +203,7 @@ def start(args):
try:
best_parameters = fmin(
fn=optimizer,
space=SPACE,
space=strategy.hyperopt_space(),
algo=tpe.suggest,
max_evals=TOTAL_TRIES,
trials=TRIALS
@@ -319,7 +219,10 @@ def start(args):
# Improve best parameter logging display
if best_parameters:
best_parameters = space_eval(SPACE, best_parameters)
best_parameters = space_eval(
strategy.hyperopt_space(),
best_parameters
)
logger.info('Best parameters:\n%s', json.dumps(best_parameters, indent=4))
logger.info('Best Result:\n%s', best_result)

41
freqtrade/optimize/hyperopt_conf.py
View File

@@ -1,41 +0,0 @@
"""
File that contains the configuration for Hyperopt
"""
def hyperopt_optimize_conf() -> dict:
"""
This function is used to define which parameters Hyperopt must used.
The "pair_whitelist" is only used is your are using Hyperopt with MongoDB,
without MongoDB, Hyperopt will use the pair your have set in your config file.
:return:
"""
return {
'max_open_trades': 3,
'stake_currency': 'BTC',
'stake_amount': 0.01,
"minimal_roi": {
'40': 0.0,
'30': 0.01,
'20': 0.02,
'0': 0.04,
},
'stoploss': -0.10,
"bid_strategy": {
"ask_last_balance": 0.0
},
"exchange": {
"pair_whitelist": [
"BTC_ETH",
"BTC_LTC",
"BTC_ETC",
"BTC_DASH",
"BTC_ZEC",
"BTC_XLM",
"BTC_NXT",
"BTC_POWR",
"BTC_ADA",
"BTC_XMR"
]
}
}