def __init__(self, period, timeSeries=None):
super(DEMA, self).__init__()
self.period = period
self.ema = EMA(period)
self.addSubIndicator(self.ema)
self.emaEma = EMA(period)
self.initialize(timeSeries)
def __init__(self, periodFast, periodSlow, timeSeries=None):
super(ChaikinOsc, self).__init__()
self.periodFast = periodFast
self.periodSlow = periodSlow
self.accuDist = AccuDist()
self.emaFast = EMA(periodFast)
self.emaSlow = EMA(periodSlow)
self.addSubIndicator(self.accuDist)
self.initialize(timeSeries)
def __init__(self, fastPeriod, slowPeriod, signalPeriod, timeSeries = None): super(MACD, self).__init__() self.fastPeriod = fastPeriod self.slowPeriod = slowPeriod self.signalPeriod = signalPeriod self.emaFast = EMA(fastPeriod) self.emaSlow = EMA(slowPeriod) self.signalLine = EMA(signalPeriod) self.macdLine = [] self.addSubIndicator(self.emaFast) self.addSubIndicator(self.emaSlow) self.initialize(timeSeries)
def __init__(self,
emaPeriod,
emaEmaPeriod,
emaRatioPeriod,
timeSeries=None):
super(MassIndex, self).__init__()
self.emaPeriod = emaPeriod
self.emaEmaPeriod = emaEmaPeriod
self.emaRatioPeriod = emaRatioPeriod
self.ema = EMA(emaPeriod)
self.emaEma = EMA(emaEmaPeriod)
self.emaRatio = []
self.initialize(timeSeries)
def getEMA(self, cretenInterval, symbol, period):
self.setupIndMap(symbol, cretenInterval)
indKey = self.getIndKey('EMA', period)
if not indKey in self.indMap[symbol][cretenInterval]:
self.indMap[symbol][cretenInterval][indKey] = EMA(
period, self.getCandles(symbol, cretenInterval))
return self.indMap[symbol][cretenInterval][indKey]
class DEMA(SingleValueIndicator):
def __init__(self, period, timeSeries=None):
super(DEMA, self).__init__()
self.period = period
self.ema = EMA(period)
self.addSubIndicator(self.ema)
self.emaEma = EMA(period)
self.initialize(timeSeries)
def _calculate(self):
if len(self.ema) < 1:
return
self.emaEma.addValue(self.ema[-1])
if len(self.emaEma) < 1:
return
self.values.append(2.0 * self.ema[-1] - self.emaEma[-1])
def removeValue(self):
super(DEMA, self).removeValue()
self.emaEma.removeValue()
def removeAll(self):
super(DEMA, self).removeAll()
self.emaEma.removeAll()
def generate_all_features(self, df):
# Calculating indicators
baseline = EMA(20, CLOSE).calculate(df)
first_trend_ind = SuperTrend(10, 3).calculate(df)
second_trend_ind = AroonHorn(20).calculate(df)
volume = SqueezeBreak(20, 20).calculate(df)
baseline = EMA_FT().transform(df, baseline)
first_trend_ind = SuperTrend_FT().transform(df, first_trend_ind)
second_trend_ind = AroonHorn_FT().transform(df, second_trend_ind)
volume = SqueezeBreak_FT().transform(df, volume)
features = pd.concat(
[baseline, first_trend_ind, second_trend_ind, volume],
join='inner',
axis=1)
return features
def generate(self, df, idx):
i = df.index.get_loc(idx)
new_df = df.iloc[i - 100:i + 1, :].copy()
# Calculating indicators
baseline = EMA(20, CLOSE).calculate(new_df)
first_trend_ind = SuperTrend(10, 3).calculate(new_df)
second_trend_ind = AroonHorn(20).calculate(new_df)
volume = SqueezeBreak(20, 20).calculate(new_df)
baseline = EMA_FT().transform(new_df, baseline)
first_trend_ind = SuperTrend_FT().transform(new_df, first_trend_ind)
second_trend_ind = AroonHorn_FT().transform(new_df, second_trend_ind)
volume = SqueezeBreak_FT().transform(new_df, volume)
features = pd.concat(
[baseline, first_trend_ind, second_trend_ind, volume],
join='inner',
axis=1).iloc[-1].tolist()
return features
def __init__(self,
maPeriod,
atrPeriod,
atrMultUp,
atrMultDown,
timeSeries=None):
super(KeltnerChannels, self).__init__()
self.maPeriod = maPeriod
self.atrPeriod = atrPeriod
self.atrMultUp = atrMultUp
self.atrMultDown = atrMultDown
self.atr = ATR(self.atrPeriod)
self.cb = EMA(self.maPeriod)
self.lb = []
self.ub = []
self.addSubIndicator(self.cb)
self.addSubIndicator(self.atr)
self.initialize(timeSeries)
class MACD(Indicator): def __init__(self, fastPeriod, slowPeriod, signalPeriod, timeSeries = None): super(MACD, self).__init__() self.fastPeriod = fastPeriod self.slowPeriod = slowPeriod self.signalPeriod = signalPeriod self.emaFast = EMA(fastPeriod) self.emaSlow = EMA(slowPeriod) self.signalLine = EMA(signalPeriod) self.macdLine = [] self.addSubIndicator(self.emaFast) self.addSubIndicator(self.emaSlow) self.initialize(timeSeries) def _calculate(self): if len(self.emaFast) > 0 and len(self.emaSlow) > 0: self.macdLine.append(self.emaFast[-1] - self.emaSlow[-1]) self.signalLine.addValue(self.macdLine[-1]) def removeValue(self): super(MACD, self).removeValue() if len(self.macdLine) > 0: self.macdLine.pop(-1) self.signalLine.removeValue() def removeAll(self): super(MACD, self).removeAll() self.macdLine = [] self.signalLine.removeAll() def getMACDLine(self): return self.macdLine def getSignalLine(self): return self.signalLine
class ChaikinOsc(SingleValueIndicator):
def __init__(self, periodFast, periodSlow, timeSeries=None):
super(ChaikinOsc, self).__init__()
self.periodFast = periodFast
self.periodSlow = periodSlow
self.accuDist = AccuDist()
self.emaFast = EMA(periodFast)
self.emaSlow = EMA(periodSlow)
self.addSubIndicator(self.accuDist)
self.initialize(timeSeries)
def _calculate(self):
if len(self.accuDist) < 1:
return
self.emaFast.addValue(self.accuDist[-1])
self.emaSlow.addValue(self.accuDist[-1])
if len(self.emaFast) < 1 or len(self.emaSlow) < 1:
return
self.values.append(self.emaFast[-1] - self.emaSlow[-1])
def removeValue(self):
super(ChaikinOsc, self).removeValue()
self.emaFast.removeValue()
self.emaSlow.removeValue()
def removeAll(self):
super(ChaikinOsc, self).removeAll()
self.emaFast.removeAll()
self.emaSlow.removeAll()
# signals = pd.Series(dm.decide(features), features.index)
# Trying to immitate VP
from indicators_transformer.EMA_FT import EMA_FT
from indicators_transformer.SqueezeBreak_FT import SqueezeBreak_FT
from indicators_transformer.AroonHorn_FT import AroonHorn_FT
from indicators_transformer.SMI_FT import SMI_FT
from indicators.EMA import EMA
from indicators.SqueezeBreak import SqueezeBreak
from indicators.AroonHorn import AroonHorn
from indicators.SMI import SMI
df = GBPUSD_data.get_1D()
baseline = EMA_FT().transform(df, EMA(14, CLOSE).calculate(df))
volume = SqueezeBreak_FT().transform(df,
SqueezeBreak(14, 14).calculate(df))
ind1 = AroonHorn_FT().transform(df, AroonHorn(20).calculate(df))
ind2 = SMI_FT().transform(df, SMI(14, 3).calculate(df))
signals = pd.concat([baseline, volume, ind1, ind2], axis=1)
signals_dic = {}
for index, row in signals.iterrows():
if row[0] == 1 and row[1] == 1 and row[2] == 1 and row[3] == 1:
signals_dic[index] = 1
elif row[0] == -1 and row[1] == 1 and row[2] == -1 and row[3] == -1:
signals_dic[index] = -1
else:
signals_dic[index] = 0
# make everything clean
out_series = df['EMA_FT']
df.drop(columns=['EMA_FT'], inplace=True)
# For test
# df['EMA(20)'] = features
# df['EMA(20)_transformed'] = out_series
# df.to_csv("../test_reports/EMA_test/EMA20_transformed.csv")
return out_series
if __name__ == "__main__":
# Loading the data
from data.FXDataLoader import Pair
GBPUSD_data = Pair(GBPUSD)
# Dataframe for test
df = GBPUSD_data.get_1D()
# Creating feature
from indicators.EMA import EMA
EMA = EMA(20, CLOSE)
ema_values = EMA.calculate(df)
# Transforming the Features
ema_transformed = EMA_FT().transform(df, ema_values)
print(ema_transformed)
class MassIndex(SingleValueIndicator):
def __init__(self,
emaPeriod,
emaEmaPeriod,
emaRatioPeriod,
timeSeries=None):
super(MassIndex, self).__init__()
self.emaPeriod = emaPeriod
self.emaEmaPeriod = emaEmaPeriod
self.emaRatioPeriod = emaRatioPeriod
self.ema = EMA(emaPeriod)
self.emaEma = EMA(emaEmaPeriod)
self.emaRatio = []
self.initialize(timeSeries)
def _calculate(self):
self.ema.addValue(self.timeSeries[-1].getHigh() -
self.timeSeries[-1].getLow())
if len(self.ema) < 1:
return
self.emaEma.addValue(self.ema[-1])
if len(self.emaEma) < 1:
return
self.emaRatio.append(self.ema[-1] / float(self.emaEma[-1]))
if len(self.emaRatio) < self.emaRatioPeriod:
return
self.values.append(sum(self.emaRatio[-self.emaRatioPeriod:]))
def removeValue(self):
super(MassIndex, self).removeValue()
self.ema.removeValue()
self.emaEma.removeValue()
if len(self.emaRatio) > 1:
self.emaRatio.pop(-1)
def removeAll(self):
super(MassIndex, self).removeAll()
self.ema.removeAll()
self.emaEma.removeAll()
self.emaRatio = []