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remove pass-through methods from Analyze

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This commit is contained in:
Janne Sinivirta 2018-07-10 09:11:36 +03:00
parent a74147c472
commit 85e6c9585a
3 changed files with 7 additions and 84 deletions
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48
freqtrade/analyze.py
View File

@ -64,46 +64,6 @@ class Analyze(object):
frame.drop(frame.tail(1).index, inplace=True) # eliminate partial candle
return frame
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
"""
return self.strategy.populate_indicators(dataframe=dataframe)
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
return self.strategy.populate_buy_trend(dataframe=dataframe)
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
return self.strategy.populate_sell_trend(dataframe=dataframe)
def get_ticker_interval(self) -> str:
"""
Return ticker interval to use
:return: Ticker interval value to use
"""
return self.strategy.ticker_interval
def get_stoploss(self) -> float:
"""
Return stoploss to use
:return: Strategy stoploss value to use
"""
return self.strategy.stoploss
def analyze_ticker(self, ticker_history: List[Dict]) -> DataFrame:
"""
Parses the given ticker history and returns a populated DataFrame
@ -111,9 +71,9 @@ class Analyze(object):
:return DataFrame with ticker data and indicator data
"""
dataframe = self.parse_ticker_dataframe(ticker_history)
dataframe = self.populate_indicators(dataframe)
dataframe = self.populate_buy_trend(dataframe)
dataframe = self.populate_sell_trend(dataframe)
dataframe = self.strategy.populate_indicators(dataframe)
dataframe = self.strategy.populate_buy_trend(dataframe)
dataframe = self.strategy.populate_sell_trend(dataframe)
return dataframe
def get_signal(self, exchange: Exchange, pair: str, interval: str) -> Tuple[bool, bool]:
@ -267,5 +227,5 @@ class Analyze(object):
"""
Creates a dataframe and populates indicators for given ticker data
"""
return {pair: self.populate_indicators(self.parse_ticker_dataframe(pair_data))
return {pair: self.strategy.populate_indicators(self.parse_ticker_dataframe(pair_data))
for pair, pair_data in tickerdata.items()}

4
freqtrade/optimize/backtesting.py
View File

@ -57,8 +57,8 @@ class Backtesting(object):
self.analyze = Analyze(self.config, self.strategy)
self.ticker_interval = self.analyze.strategy.ticker_interval
self.tickerdata_to_dataframe = self.analyze.tickerdata_to_dataframe
self.populate_buy_trend = self.analyze.populate_buy_trend
self.populate_sell_trend = self.analyze.populate_sell_trend
self.populate_buy_trend = self.strategy.populate_buy_trend
self.populate_sell_trend = self.strategy.populate_sell_trend
# Reset keys for backtesting
self.config['exchange']['key'] = ''

39
freqtrade/tests/test_analyze.py
View File

@ -10,7 +10,7 @@ from unittest.mock import MagicMock
import arrow
from pandas import DataFrame
from freqtrade.analyze import Analyze, SignalType
from freqtrade.analyze import Analyze
from freqtrade.arguments import TimeRange
from freqtrade.optimize.__init__ import load_tickerdata_file
from freqtrade.tests.conftest import get_patched_exchange, log_has
@ -20,31 +20,6 @@ from freqtrade.strategy.default_strategy import DefaultStrategy
_ANALYZE = Analyze({}, DefaultStrategy())
def test_signaltype_object() -> None:
"""
Test the SignalType object has the mandatory Constants
:return: None
"""
assert hasattr(SignalType, 'BUY')
assert hasattr(SignalType, 'SELL')
def test_analyze_object() -> None:
"""
Test the Analyze object has the mandatory methods
:return: None
"""
assert hasattr(Analyze, 'parse_ticker_dataframe')
assert hasattr(Analyze, 'populate_indicators')
assert hasattr(Analyze, 'populate_buy_trend')
assert hasattr(Analyze, 'populate_sell_trend')
assert hasattr(Analyze, 'analyze_ticker')
assert hasattr(Analyze, 'get_signal')
assert hasattr(Analyze, 'should_sell')
assert hasattr(Analyze, 'min_roi_reached')
assert hasattr(Analyze, 'stop_loss_reached')
def test_dataframe_correct_length(result):
dataframe = Analyze.parse_ticker_dataframe(result)
assert len(result.index) - 1 == len(dataframe.index) # last partial candle removed
@ -55,18 +30,6 @@ def test_dataframe_correct_columns(result):
['date', 'open', 'high', 'low', 'close', 'volume']
def test_populates_buy_trend(result):
# Load the default strategy for the unit test, because this logic is done in main.py
dataframe = _ANALYZE.populate_buy_trend(_ANALYZE.populate_indicators(result))
assert 'buy' in dataframe.columns
def test_populates_sell_trend(result):
# Load the default strategy for the unit test, because this logic is done in main.py
dataframe = _ANALYZE.populate_sell_trend(_ANALYZE.populate_indicators(result))
assert 'sell' in dataframe.columns
def test_returns_latest_buy_signal(mocker, default_conf):
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=MagicMock())
exchange = get_patched_exchange(mocker, default_conf)