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Merge pull request #43 from il-katta/master

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CombinedBinHAndCluc code clean
This commit is contained in:
Matthias
2019-08-22 12:42:23 +02:00
committed by GitHub
parent 456de39bfa 531a1c83a3
commit 1c67803f5c
1 changed files with 27 additions and 30 deletions
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user_data/strategies/berlinguyinca/CombinedBinHAndCluc.py
+27 -30
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@@ -1,17 +1,17 @@
# --- Do not remove these libs ---
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
# --------------------------------
import talib.abstract as ta
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.strategy.interface import IStrategy
def bollinger_bands(stock_price, window_size, num_of_std):
rolling_mean = stock_price.rolling(window=window_size).mean()
rolling_std = stock_price.rolling(window=window_size).std()
lower_band = rolling_mean - (rolling_std * num_of_std)
return rolling_mean, lower_band
return np.nan_to_num(rolling_mean), np.nan_to_num(lower_band)
class CombinedBinHAndCluc(IStrategy):
@@ -21,58 +21,55 @@ class CombinedBinHAndCluc(IStrategy):
# - if the market is constantly green(like in JAN 2018) the best performance is reached with
# "max_open_trades" = 2 and minimal_roi = 0.01
minimal_roi = {
"0": 0.02
"0": 0.05
}
stoploss = -0.15
stoploss = -0.05
ticker_interval = '5m'
use_sell_signal = True
sell_profit_only = True
ignore_roi_if_buy_signal = False
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# strategy BinHV45
mid, lower = bollinger_bands(dataframe['close'], window_size=40, num_of_std=2)
dataframe['mid'] = np.nan_to_num(mid)
dataframe['lower'] = np.nan_to_num(lower)
dataframe['bbdelta'] = (dataframe['mid'] - dataframe['lower']).abs()
dataframe['pricedelta'] = (dataframe['open'] - dataframe['close']).abs()
dataframe['lower'] = lower
dataframe['bbdelta'] = (mid - dataframe['lower']).abs()
dataframe['closedelta'] = (dataframe['close'] - dataframe['close'].shift()).abs()
dataframe['tail'] = (dataframe['close'] - dataframe['low']).abs()
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=5)
rsiframe = DataFrame(dataframe['rsi']).rename(columns={'rsi': 'close'})
dataframe['emarsi'] = ta.EMA(rsiframe, timeperiod=5)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['adx'] = ta.ADX(dataframe)
# strategy ClucMay72018
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema_slow'] = ta.EMA(dataframe, timeperiod=50)
dataframe['volume_mean_slow'] = dataframe['volume'].rolling(window=30).mean()
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
( # strategy BinHV45
dataframe['lower'].shift().gt(0) &
dataframe['bbdelta'].gt(dataframe['close'] * 0.008) &
dataframe['closedelta'].gt(dataframe['close'] * 0.0175) &
dataframe['tail'].lt(dataframe['bbdelta'] * 0.25) &
dataframe['close'].lt(dataframe['lower'].shift()) &
dataframe['close'].le(dataframe['close'].shift())
)
|
(
(dataframe['close'] < dataframe['ema100']) &
) |
( # strategy ClucMay72018
(dataframe['close'] < dataframe['ema_slow']) &
(dataframe['close'] < 0.985 * dataframe['bb_lowerband']) &
(dataframe['volume'] < (dataframe['volume'].rolling(window=30).mean().shift(1) * 20))
)
,
'buy'] = 1
(dataframe['volume'] < (dataframe['volume_mean_slow'].shift(1) * 20))
),
'buy'
] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
"""
dataframe.loc[
(
(dataframe['close'] > dataframe['bb_middleband'])
),
'sell'] = 1
(dataframe['close'] > dataframe['bb_middleband']),
'sell'
] = 1
return dataframe