stable/freqtrade/tests/test_hyperopt.py
2017-10-25 18:37:20 +03:00

134 lines
4.7 KiB
Python

# pragma pylint: disable=missing-docstring
import json
import logging
import os
from functools import reduce
import pytest
import arrow
from pandas import DataFrame
from qtpylib.indicators import crossed_above
from hyperopt import fmin, tpe, hp
from freqtrade.analyze import analyze_ticker
from freqtrade.main import should_sell
from freqtrade.persistence import Trade
from freqtrade.tests.test_backtesting import backtest, print_results
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
@pytest.fixture
def pairs():
return ['btc-neo', 'btc-eth', 'btc-omg', 'btc-edg', 'btc-pay',
'btc-pivx', 'btc-qtum', 'btc-mtl', 'btc-etc', 'btc-ltc']
@pytest.fixture
def conf():
return {
"minimal_roi": {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
},
"stoploss": -0.05
}
def buy_strategy_generator(params):
print(params)
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if params['below_sma']['enabled']:
conditions.append(dataframe['close'] < dataframe['sma'])
if params['over_sma']['enabled']:
conditions.append(dataframe['close'] > dataframe['sma'])
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['cci']['enabled']:
conditions.append(dataframe['cci'] < params['cci']['value'])
if params['over_sar']['enabled']:
conditions.append(dataframe['close'] > dataframe['sar'])
if params['uptrend_sma']['enabled']:
prevsma = dataframe['sma'].shift(1)
conditions.append(dataframe['sma'] > prevsma)
prev_fastd = dataframe['fastd'].shift(1)
# TRIGGERS
triggers = {
'lower_bb': dataframe['tema'] <= dataframe['blower'],
'faststoch10': (dataframe['fastd'] >= 10) & (prev_fastd < 10),
'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
}
conditions.append(triggers.get(params['trigger']['type']))
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
return dataframe
return populate_buy_trend
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_hyperopt(conf, pairs, mocker):
def optimizer(params):
buy_strategy = buy_strategy_generator(params)
mocker.patch('freqtrade.analyze.populate_buy_trend', side_effect=buy_strategy)
results = backtest(conf, pairs, mocker)
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
space = {
'mfi': hp.choice('mfi', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('mfi-value', 2, 40)}
]),
'fastd': hp.choice('fastd', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('fastd-value', 2, 40)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('adx-value', 2, 40)}
]),
'cci': hp.choice('cci', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('cci-value', -200, -100)}
]),
'below_sma': hp.choice('below_sma', [
{'enabled': False},
{'enabled': True}
]),
'over_sma': hp.choice('over_sma', [
{'enabled': False},
{'enabled': True}
]),
'over_sar': hp.choice('over_sar', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_sma': hp.choice('uptrend_sma', [
{'enabled': False},
{'enabled': True}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'}
]),
}
print('Best parameters {}'.format(fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=40)))