def __init__(self, args=[]):
[rocA, rocB, rocC, rocD, smaA, smaB, smaC, smaD, smaSignal] = args
self._rocA = ROC([rocA])
self._rocB = ROC([rocB])
self._rocC = ROC([rocC])
self._rocD = ROC([rocD])
self._smaA = SMA([smaA])
self._smaB = SMA([smaB])
self._smaC = SMA([smaC])
self._smaD = SMA([smaD])
self._smaSignal = SMA([smaSignal])
super().__init__({
'args':
args,
'id':
'kst',
'name':
'KST(%f, %f, %f, %f, %f, %f, %f, %f, %f)' %
(rocA, rocB, rocC, rocD, smaA, smaB, smaC, smaD, smaSignal),
'seedPeriod':
max([
rocA + smaA, rocB + smaB, rocC + smaC, rocD + smaD, smaSignal
])
})
class DPO(Indicator):
def __init__(self, args = []):
[ period ] = args
self._pricePeriod = floor(period / 2) + 1
self._sma = SMA([period])
super().__init__({
'args': args,
'id': 'dpo',
'name': 'DPO(%f)' % period,
'seedPeriod': period
})
def reset(self):
super().reset()
self._sma.reset()
def update(self, v):
self._sma.update(v)
super().update(v - self._sma.prev(self._pricePeriod - 1))
return self.v()
def add(self, v):
self._sma.add(v)
if self._sma.l() < self._pricePeriod + 1:
return
super().add(v - self._sma.prev(self._pricePeriod))
return self.v()
def __init__(self, args = []):
[ period ] = args
self._pricePeriod = floor(period / 2) + 1
self._sma = SMA([period])
super().__init__({
'args': args,
'id': 'dpo',
'name': 'DPO(%f)' % period,
'seedPeriod': period
})
def __init__(self, args=[]):
self._smaShort = SMA([5])
self._smaLong = SMA([34])
super().__init__({
'args': args,
'id': 'ao',
'name': 'AO',
'seedPeriod': None,
'dataType': 'candle',
'dataKey': '*'
})
def __init__(self, args=[]):
[length, percent] = args
self._sma = SMA([length])
self._p = percent / 100
super().__init__({
'args': args,
'id': 'env',
'name': 'Env(%f, %f)' % (length, percent),
'seedPeriod': length,
})
def __init__(self, args=[]):
[period, mul] = args
self._p = period
self._m = mul
self._sma = SMA([period])
self._stddev = StdDeviation([period])
super().__init__({
'args': args,
'id': 'bbands',
'name': 'BBANDS(%f, %f)' % (period, mul),
'seedPeriod': period
})
def __init__(self, args=[]):
[divisor, length] = args
self._d = divisor
self._sma = SMA([length])
self._lastCandle = None
super().__init__({
'args': args,
'id': 'eom',
'name': 'EOM(%f, %f)' % (divisor, length),
'seedPeriod': length,
'dataType': 'candle',
'dataKey': '*'
})
def __init__(self, args=[]):
[period] = args
self._numeratorSMA = SMA([period])
self._denominatorSMA = SMA([period])
self._buffer = []
super().__init__({
'args': args,
'id': 'rvgi',
'name': 'RVGI(%f)' % period,
'seedPeriod': period,
'dataType': 'candle',
'dataKey': '*'
})
def __init__(self, args=[]):
[period, smoothK, smoothD] = args
self._p = period
self._buffer = []
self._kSMA = SMA([smoothK])
self._dSMA = SMA([smoothD])
super().__init__({
'args': args,
'id': 'stoch',
'name': 'Stoch(%f)' % (period),
'seedPeriod': period,
'dataType': 'candle',
'dataKey': '*'
})
def __init__(self, args=[]):
[lengthRSI, lengthStochastic, smoothStoch, smoothSignal] = args
self._buffer = []
self._l = lengthStochastic
self._rsi = RSI([lengthRSI])
self._smaStoch = SMA([smoothStoch])
self._smaSignal = SMA([smoothSignal])
super().__init__({
'args':
args,
'id':
'stochrsi',
'name':
'Stoch RSI(%f, %f, %f, %f)' %
(lengthRSI, lengthStochastic, smoothStoch, smoothSignal),
'seedPeriod':
lengthRSI + lengthStochastic + smoothStoch
})
class BollingerBands(Indicator):
def __init__(self, args=[]):
[period, mul] = args
self._p = period
self._m = mul
self._sma = SMA([period])
self._stddev = StdDeviation([period])
super().__init__({
'args': args,
'id': 'bbands',
'name': 'BBANDS(%f, %f)' % (period, mul),
'seedPeriod': period
})
def reset(self):
super().reset()
self._sma.reset()
self._stddev.reset()
def update(self, v):
self._sma.update(v)
self._stddev.update(v)
middle = self._sma.v()
stddev = self._stddev.v()
super().update({
'top': middle + (self._m * stddev),
'middle': middle,
'bottom': middle - (self._m * stddev)
})
return self.v()
def add(self, v):
self._sma.add(v)
self._stddev.add(v)
middle = self._sma.v()
stddev = self._stddev.v()
super().add({
'top': middle + (self._m * stddev),
'middle': middle,
'bottom': middle - (self._m * stddev)
})
return self.v()
class Envelope(Indicator):
def __init__(self, args=[]):
[length, percent] = args
self._sma = SMA([length])
self._p = percent / 100
super().__init__({
'args': args,
'id': 'env',
'name': 'Env(%f, %f)' % (length, percent),
'seedPeriod': length,
})
def reset(self):
super().reset()
self._sma.reset()
def update(self, v):
self._sma.update(v)
basis = self._sma.v()
if not isfinite(basis):
return
delta = basis * self._p
super().update({
'upper': basis + delta,
'basis': basis,
'lower': basis - delta
})
return self.v()
def add(self, v):
self._sma.add(v)
basis = self._sma.v()
if not isfinite(basis):
return
delta = basis * self._p
super().add({
'upper': basis + delta,
'basis': basis,
'lower': basis - delta
})
return self.v()
class StochasticRSI(Indicator):
def __init__(self, args=[]):
[lengthRSI, lengthStochastic, smoothStoch, smoothSignal] = args
self._buffer = []
self._l = lengthStochastic
self._rsi = RSI([lengthRSI])
self._smaStoch = SMA([smoothStoch])
self._smaSignal = SMA([smoothSignal])
super().__init__({
'args':
args,
'id':
'stochrsi',
'name':
'Stoch RSI(%f, %f, %f, %f)' %
(lengthRSI, lengthStochastic, smoothStoch, smoothSignal),
'seedPeriod':
lengthRSI + lengthStochastic + smoothStoch
})
def reset(self):
super().reset()
self._buffer = []
self._rsi.reset()
self._smaStoch.reset()
self._smaSignal.reset()
def update(self, v):
self._rsi.update(v)
rsi = self._rsi.v()
if not isfinite(rsi):
return self.v()
if len(self._buffer) == 0:
self._buffer.append(rsi)
else:
self._buffer[-1] = rsi
if len(self._buffer) < self._l:
return self.v()
low = min(self._buffer)
high = max(self._buffer)
stoch = 1 if high == low else ((rsi - low) / (high - low))
self._smaStoch.update(stoch * 100)
smaStoch = self._smaStoch.v()
if not isfinite(smaStoch):
return self.v()
self._smaSignal.update(smaStoch)
smaSignal = self._smaSignal.v()
if isfinite(smaSignal):
super().update({'v': smaStoch, 'signal': smaSignal})
return self.v()
def add(self, v):
self._rsi.add(v)
rsi = self._rsi.v()
if not isfinite(rsi):
return self.v()
self._buffer.append(rsi)
if len(self._buffer) > self._l:
del self._buffer[0]
elif len(self._buffer) < self._l:
return self.v()
low = min(self._buffer)
high = max(self._buffer)
stoch = 1 if high == low else ((rsi - low) / (high - low))
self._smaStoch.add(stoch * 100)
smaStoch = self._smaStoch.v()
if not isfinite(smaStoch):
return self.v()
self._smaSignal.add(smaStoch)
smaSignal = self._smaSignal.v()
if isfinite(smaSignal):
super().add({'v': smaStoch, 'signal': smaSignal})
return self.v()
class AO(Indicator):
def __init__(self, args=[]):
self._smaShort = SMA([5])
self._smaLong = SMA([34])
super().__init__({
'args': args,
'id': 'ao',
'name': 'AO',
'seedPeriod': None,
'dataType': 'candle',
'dataKey': '*'
})
def reset(self):
super().reset()
self._smaShort.reset()
self._smaLong.reset()
def update(self, candle):
v = (candle['high'] + candle['low']) / 2
self._smaShort.update(v)
self._smaLong.update(v)
super().update(self._smaShort.v() - self._smaLong.v())
return self.v()
def add(self, candle):
v = (candle['high'] + candle['low']) / 2
self._smaShort.add(v)
self._smaLong.add(v)
super().add(self._smaShort.v() - self._smaLong.v())
return self.v()
class KST(Indicator):
def __init__(self, args=[]):
[rocA, rocB, rocC, rocD, smaA, smaB, smaC, smaD, smaSignal] = args
self._rocA = ROC([rocA])
self._rocB = ROC([rocB])
self._rocC = ROC([rocC])
self._rocD = ROC([rocD])
self._smaA = SMA([smaA])
self._smaB = SMA([smaB])
self._smaC = SMA([smaC])
self._smaD = SMA([smaD])
self._smaSignal = SMA([smaSignal])
super().__init__({
'args':
args,
'id':
'kst',
'name':
'KST(%f, %f, %f, %f, %f, %f, %f, %f, %f)' %
(rocA, rocB, rocC, rocD, smaA, smaB, smaC, smaD, smaSignal),
'seedPeriod':
max([
rocA + smaA, rocB + smaB, rocC + smaC, rocD + smaD, smaSignal
])
})
def reset(self):
super().reset()
self._rocA.reset()
self._rocB.reset()
self._rocC.reset()
self._rocD.reset()
self._smaA.reset()
self._smaB.reset()
self._smaC.reset()
self._smaD.reset()
self._smaSignal.reset()
def update(self, v):
self._rocA.update(v)
self._rocB.update(v)
self._rocC.update(v)
self._rocD.update(v)
if self._rocA.ready():
self._smaA.update(self._rocA.v())
if self._rocB.ready():
self._smaB.update(self._rocB.v())
if self._rocC.ready():
self._smaC.update(self._rocC.v())
if self._rocD.ready():
self._smaD.update(self._rocD.v())
if not self._smaA.ready() or not self._smaB.ready(
) or not self._smaC.ready() or not self._smaD.ready():
return
kst = self._smaA.v() + (self._smaB.v() * 2) + (self._smaC.v() * 3) + (
self._smaD.v() * 4)
self._smaSignal.update(kst)
super().update({'v': kst, 'signal': self._smaSignal.v()})
return self.v()
def add(self, v):
self._rocA.add(v)
self._rocB.add(v)
self._rocC.add(v)
self._rocD.add(v)
if self._rocA.ready():
self._smaA.add(self._rocA.v())
if self._rocB.ready():
self._smaB.add(self._rocB.v())
if self._rocC.ready():
self._smaC.add(self._rocC.v())
if self._rocD.ready():
self._smaD.add(self._rocD.v())
if not self._smaA.ready() or not self._smaB.ready(
) or not self._smaC.ready() or not self._smaD.ready():
return
kst = self._smaA.v() + (self._smaB.v() * 2) + (self._smaC.v() * 3) + (
self._smaD.v() * 4)
self._smaSignal.add(kst)
super().add({'v': kst, 'signal': self._smaSignal.v()})
return self.v()
class Stochastic(Indicator):
def __init__(self, args=[]):
[period, smoothK, smoothD] = args
self._p = period
self._buffer = []
self._kSMA = SMA([smoothK])
self._dSMA = SMA([smoothD])
super().__init__({
'args': args,
'id': 'stoch',
'name': 'Stoch(%f)' % (period),
'seedPeriod': period,
'dataType': 'candle',
'dataKey': '*'
})
def reset(self):
super().reset()
self._buffer = []
self._kSMA.reset()
self._dSMA.reset()
def update(self, candle):
if len(self._buffer) == 0:
self._buffer.append(candle)
else:
self._buffer[-1] = candle
if len(self._buffer) < self._p:
return self.v()
close = candle['close']
lowestLow = min(map(lambda c: c['low'], self._buffer))
highestHigh = max(map(lambda c: c['high'], self._buffer))
k = 100 * ((close - lowestLow) / (highestHigh - lowestLow))
self._kSMA.update(k)
self._dSMA.update(self._kSMA.v())
return super().update({'k': self._kSMA.v(), 'd': self._dSMA.v()})
def add(self, candle):
self._buffer.append(candle)
if len(self._buffer) > self._p:
del self._buffer[0]
elif len(self._buffer) < self._p:
return self.v()
close = candle['close']
lowestLow = min(map(lambda c: c['low'], self._buffer))
highestHigh = max(map(lambda c: c['high'], self._buffer))
k = 100 * ((close - lowestLow) / (highestHigh - lowestLow))
self._kSMA.add(k)
self._dSMA.add(self._kSMA.v())
return super().add({'k': self._kSMA.v(), 'd': self._dSMA.v()})
class RVGI(Indicator):
def __init__(self, args=[]):
[period] = args
self._numeratorSMA = SMA([period])
self._denominatorSMA = SMA([period])
self._buffer = []
super().__init__({
'args': args,
'id': 'rvgi',
'name': 'RVGI(%f)' % period,
'seedPeriod': period,
'dataType': 'candle',
'dataKey': '*'
})
def reset(self):
super().reset()
self._numeratorSMA.reset()
self._denominatorSMA.reset()
self._buffer = []
def calc(candle, buffer):
barA = candle['close'] - candle['open']
barB = buffer[2]['close'] - buffer[2]['open']
barC = buffer[1]['close'] - buffer[1]['open']
barD = buffer[0]['close'] - buffer[0]['open']
num = (barA + (barB * 2) + (barC * 2) + barD) / 6
e = candle['high'] - candle['low']
f = buffer[2]['high'] - buffer[2]['low']
g = buffer[1]['high'] - buffer[1]['low']
h = buffer[0]['high'] - buffer[0]['low']
den = (e + (f * 2) + (g * 2) + h) / 6
return [num, den]
def update(self, candle):
if len(self._buffer) == 0:
self._buffer.append(candle)
else:
self._buffer[-1] = candle
if len(self._buffer) < 4:
return super().update(0)
[num, den] = RVGI.calc(candle, self._buffer)
self._numeratorSMA.update(num)
self._denominatorSMA.update(den)
rvi = self._numeratorSMA.v() / self._denominatorSMA.v()
signal = 0
if self.l() >= 3:
i = self.v()['rvi']
j = self.prev(1)['rvi']
k = self.prev(2)['rvi']
signal = (rvi + (i * 2) + (j * 2) + k) / 6
super().update({'rvi': rvi, 'signal': signal})
def add(self, candle):
self._buffer.append(candle)
if len(self._buffer) > 4:
del self._buffer[0]
elif len(self._buffer) < 4:
return self.v()
[num, den] = RVGI.calc(candle, self._buffer)
self._numeratorSMA.add(num)
self._denominatorSMA.add(den)
rvi = self._numeratorSMA.v() / self._denominatorSMA.v()
signal = 0
if self.l() >= 4:
i = self.prev(1)['rvi']
j = self.prev(2)['rvi']
k = self.prev(3)['rvi']
signal = (rvi + (i * 2) + (j * 2) + k) / 6
super().add({'rvi': rvi, 'signal': signal})
class EOM(Indicator):
def __init__(self, args=[]):
[divisor, length] = args
self._d = divisor
self._sma = SMA([length])
self._lastCandle = None
super().__init__({
'args': args,
'id': 'eom',
'name': 'EOM(%f, %f)' % (divisor, length),
'seedPeriod': length,
'dataType': 'candle',
'dataKey': '*'
})
def reset(self):
super().reset()
self._lastCandle = None
self._sma.reset()
def calcEOM(candle, lastCandle, divisor):
high = candle['high']
low = candle['low']
vol = candle['vol']
lastHigh = lastCandle['high']
lastLow = lastCandle['low']
moved = ((high + low) / 2) - ((lastHigh + lastLow) / 2)
if high == low:
boxRatio = 1
else:
boxRatio = (vol / divisor) / (high - low)
return moved / boxRatio
def update(self, candle):
if self._lastCandle == None:
return
eom = EOM.calcEOM(candle, self._lastCandle, self._d)
self._sma.update(eom)
v = self._sma.v()
if isfinite(v):
super().update(v)
return self.v()
def add(self, candle):
if self._lastCandle == None:
self._lastCandle = candle
return
eom = EOM.calcEOM(candle, self._lastCandle, self._d)
self._sma.add(eom)
v = self._sma.v()
if isfinite(v):
super().add(v)
self._lastCandle = candle
return self.v()
