Merge pull request #111 from gcarq/memoryfix-hyperopt

Memory fix hyperopt
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Samuel Husso 2017-11-17 18:41:38 +02:00 committed by GitHub
commit 77887d6fbc
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5 changed files with 39 additions and 21 deletions

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@ -66,14 +66,13 @@ def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.ix[
dataframe.loc[
(dataframe['close'] < dataframe['sma']) &
(dataframe['tema'] <= dataframe['blower']) &
(dataframe['mfi'] < 25) &
(dataframe['fastd'] < 25) &
(dataframe['adx'] > 30),
'buy'] = 1
dataframe.ix[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
return dataframe
@ -83,10 +82,9 @@ def populate_sell_trend(dataframe: DataFrame) -> DataFrame:
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.ix[
dataframe.loc[
(crossed_above(dataframe['rsi'], 70)),
'sell'] = 1
dataframe.ix[dataframe['sell'] == 1, 'sell_price'] = dataframe['close']
return dataframe
@ -106,6 +104,9 @@ def analyze_ticker(pair: str) -> DataFrame:
dataframe = populate_indicators(dataframe)
dataframe = populate_buy_trend(dataframe)
dataframe = populate_sell_trend(dataframe)
# TODO: buy_price and sell_price are only used by the plotter, should probably be moved there
dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
dataframe.loc[dataframe['sell'] == 1, 'sell_price'] = dataframe['close']
return dataframe

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@ -163,9 +163,9 @@ def min_roi_reached(trade: Trade, current_rate: float, current_time: datetime) -
logger.debug('Stop loss hit.')
return True
for duration, threshold in sorted(_CONF['minimal_roi'].items()):
# Check if time matches and current rate is above threshold
time_diff = (current_time - trade.open_date).total_seconds() / 60
for duration, threshold in sorted(_CONF['minimal_roi'].items()):
if time_diff > float(duration) and current_profit > threshold:
return True

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@ -5,7 +5,7 @@ import pytest
from pandas import DataFrame
from freqtrade.analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators, \
get_signal, SignalType
get_signal, SignalType, populate_sell_trend
@pytest.fixture
@ -26,7 +26,11 @@ def test_dataframe_correct_length(result):
def test_populates_buy_trend(result):
dataframe = populate_buy_trend(populate_indicators(result))
assert 'buy' in dataframe.columns
assert 'buy_price' in dataframe.columns
def test_populates_buy_trend(result):
dataframe = populate_sell_trend(populate_indicators(result))
assert 'sell' in dataframe.columns
def test_returns_latest_buy_signal(mocker):

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@ -1,4 +1,5 @@
# pragma pylint: disable=missing-docstring
from typing import Dict
import logging
import os
@ -7,7 +8,8 @@ import arrow
from pandas import DataFrame
from freqtrade import exchange
from freqtrade.analyze import analyze_ticker
from freqtrade.analyze import parse_ticker_dataframe, populate_indicators, \
populate_buy_trend, populate_sell_trend
from freqtrade.exchange import Bittrex
from freqtrade.main import min_roi_reached
from freqtrade.persistence import Trade
@ -25,15 +27,22 @@ def print_pair_results(pair, results):
print(format_results(results[results.currency == pair]))
def backtest(backtest_conf, backdata, mocker):
def preprocess(backdata) -> Dict[str, DataFrame]:
processed = {}
for pair, pair_data in backdata.items():
processed[pair] = populate_indicators(parse_ticker_dataframe(pair_data))
return processed
def backtest(backtest_conf, processed, mocker):
trades = []
exchange._API = Bittrex({'key': '', 'secret': ''})
mocked_history = mocker.patch('freqtrade.analyze.get_ticker_history')
mocker.patch.dict('freqtrade.main._CONF', backtest_conf)
mocker.patch('arrow.utcnow', return_value=arrow.get('2017-08-20T14:50:00'))
for pair, pair_data in backdata.items():
mocked_history.return_value = pair_data
ticker = analyze_ticker(pair)[['close', 'date', 'buy', 'sell']].copy()
for pair, pair_data in processed.items():
pair_data['buy'] = 0
pair_data['sell'] = 0
ticker = populate_sell_trend(populate_buy_trend(pair_data))
# for each buy point
for row in ticker[ticker.buy == 1].itertuples(index=True):
trade = Trade(
@ -50,13 +59,12 @@ def backtest(backtest_conf, backdata, mocker):
trades.append((pair, current_profit, row2.Index - row.Index))
break
labels = ['currency', 'profit', 'duration']
results = DataFrame.from_records(trades, columns=labels)
return results
return DataFrame.from_records(trades, columns=labels)
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_backtest(backtest_conf, backdata, mocker, report=True):
results = backtest(backtest_conf, backdata, mocker)
results = backtest(backtest_conf, preprocess(backdata), mocker)
print('====================== BACKTESTING REPORT ================================')
for pair in backdata:

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@ -9,7 +9,7 @@ import pytest
from hyperopt import fmin, tpe, hp, Trials, STATUS_OK
from pandas import DataFrame
from freqtrade.tests.test_backtesting import backtest, format_results
from freqtrade.tests.test_backtesting import backtest, format_results, preprocess
from freqtrade.vendor.qtpylib.indicators import crossed_above
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
@ -59,7 +59,6 @@ def buy_strategy_generator(params):
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
@ -67,12 +66,13 @@ def buy_strategy_generator(params):
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_hyperopt(backtest_conf, backdata, mocker):
mocked_buy_trend = mocker.patch('freqtrade.analyze.populate_buy_trend')
mocked_buy_trend = mocker.patch('freqtrade.tests.test_backtesting.populate_buy_trend')
processed = preprocess(backdata)
def optimizer(params):
mocked_buy_trend.side_effect = buy_strategy_generator(params)
results = backtest(backtest_conf, backdata, mocker)
results = backtest(backtest_conf, processed, mocker)
result = format_results(results)
@ -146,3 +146,8 @@ def test_hyperopt(backtest_conf, backdata, mocker):
print('Best parameters {}'.format(best))
newlist = sorted(trials.results, key=itemgetter('loss'))
print('Result: {}'.format(newlist[0]['result']))
if __name__ == '__main__':
# for profiling with cProfile and line_profiler
pytest.main([__file__, '-s'])