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indicators.py
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import pandas as pd
import os
import sys
# Note: Shayad RSI theek se code ni ho payega. Iski requirements discuss kar lenge
def vwap(high, low, close, vol, commTotal, commVol):
avg= (high+low+close)/3
temp= avg*vol
commTotal+= temp
commVol+= vol
vwap= commTotal/commVol
# commTotal and commVol will be required
return [vwap, commTotal, commVol]
def ema(currPrice, prevEma, n ):
# logger.info("Calculating EMA")
noOfPeriods = n
k = 2/(noOfPeriods + 1)
emavg = k * ( currPrice - prevEma ) + prevEma # ema = K * ( currPrice - prevEma ) + prevEma
return emavg
############# Average for ADX #############
def smooth(curr, prev, period):
return prev - (prev / period) + curr
def adx(df, dic):
plusDM1= dic['intervalHigh'] - df['intervalHigh'].iloc[-1]
minusDM1= df['intervalLow'].iloc[-1] - dic['intervalLow']
plusDM= 0
minusDM= 0
if plusDM1> minusDM1:
plusDM= max(0, plusDM1)
else:
minusDM= max(0, minusDM1)
a= dic['intervalHigh'] - dic['intervalLow']
b= abs(dic['intervalHigh'] - df['currentPrice'].iloc[-1])
c= abs(dic['intervalLow'] - df['currentPrice'].iloc[-1])
trueRange= max(a, b, c)
# data would be pepared first
##### Replace EMA with smooth ######
prevTrueRangeEMA= df['trueRange14'].iloc[-1] # assuming it to be present
trueRange14= smooth(trueRange, prevTrueRangeEMA, 14)
plusDI14= df['plusDM14'].iloc[-1]
minusDI14= df['plusDM14'].iloc[-1]
plusDI14= smooth(plusDM, plusDI14, 14)
minusDI14= smooth(minusDM, minusDI14, 14)
dx= 100 * (abs(plusDI14 - minusDI14) / (plusDI14 + minusDI14))
adxVal= (sum(df['adx'].iloc[ - 14: -1]) + dx) / 14
return trueRange, trueRange14, plusDM, minusDM, plusDI14, minusDI14, dx, adxVal
def makeReady(dic, fileName):
path= os.path.join(os.getcwd(), 'daySummary', fileName)
df= pd.read_csv(path)
# update original dictionary. so don't make copy of dic
# ----------------- logic here -----------------
obj = vwap(dic['intervalHigh'],dic['intervalLow'],dic['currentPrice'],dic['intervalVolume'],dic['commulativeTotal'],dic['commulativeVolume'])
dic['commulativeTotal'] = obj[1]
dic['vwap'] = obj[0]
dic['ema50'] = ema(dic['currentPrice'],df['ema50'].iloc[-1], 50)
dic['ema13'] = ema(dic['currentPrice'],df['ema13'].iloc[-1], 13)
dic['ema9'] = ema(dic['currentPrice'],df['ema9'].iloc[-1], 9)
dic['ema26'] = ema(dic['currentPrice'],df['ema26'].iloc[-1], 26)
dic['trueRange'], dic['trueRange14'], dic['plusDM'], dic['minusDM'], dic['plusDM14'], dic['minusDM14'], dic['dx'], dic['adx']= adx(df.tail(2), dic)
# -----------------logic ends ------------------
return dic
def preparePastData(df, token, symbol):
defaultColumns= ['vwap', 'lastStrategyTime', 'dayHigh', 'dayLow', 'r1', 'r2', 'r3',
's1', 's2', 's3', 'pivotpoint', 'currentResistance', 'currentSupport']
for col in defaultColumns:
df[col]= -1
df['token']= token
df['symbol']= symbol
emas= ['ema9', 'ema13', 'ema26', 'ema50']
emaPeriods= [9, 13, 26, 50]
initialEmas= []
for i in range(4):
x= emaPeriods[i]
em= [-1 for i in range(x-1)]
em.append(df['currentPrice'].iloc[:x].sum() / x)
initialEmas.append(em)
# try:
for x, i in enumerate(initialEmas):
for j in range(len(i), len(df)):
i.append(ema(df['currentPrice'].iloc[j], i[-1], emaPeriods[x]))
# except:
# print(error)
# print(df.columns.values.tolist ())
# sys.exit()
for ind, colName in enumerate(emas):
df[colName]= initialEmas[ind]
# adx calculations
trueRange= [-1]
plusDM= [-1]
minusDM= [-1]
for i in range(1, len(df)):
plusDM1= df['intervalHigh'].iloc[i] - df['intervalHigh'].iloc[i-1]
minusDM1= df['intervalLow'].iloc[i-1] - df['intervalLow'].iloc[i]
if plusDM1> minusDM1:
plusDM.append(max(0, plusDM1))
minusDM.append(0)
else:
minusDM.append(max(0, minusDM1))
plusDM.append(0)
a= df['intervalHigh'].iloc[i] - df['intervalLow'].iloc[i]
b= abs(df['intervalHigh'].iloc[i] - df['currentPrice'].iloc[i-1])
c= abs(df['intervalLow'].iloc[i] - df['currentPrice'].iloc[i-1])
trueRange.append(max(a, b, c))
plusDM14= []
minusDM14= []
dx= []
trueRange14= []
for i in range(14):
plusDM14.append(-1)
minusDM14.append(-1)
dx.append(-1)
trueRange14.append(-1)
plusDM14.append(sum(plusDM[1 : 15]))
minusDM14.append(sum(minusDM[1 : 15]))
trueRange14.append(sum(trueRange[1 : 15]))
d= (plusDM14[-1] - minusDM14[-1]) / (plusDM14[-1] + minusDM14[-1])
dx.append(abs(d)*100)
for i in range(15, len(df)):
plusDM14.append(smooth(plusDM[i], plusDM14[-1], 14))
minusDM14.append(smooth(minusDM[i], minusDM14[-1], 14))
trueRange14.append(smooth(trueRange[i], trueRange14[-1], 14))
d= (plusDM14[-1] - minusDM14[-1]) / (plusDM14[-1] + minusDM14[-1])
dx.append(abs(d)*100)
adxArr= []
for i in range(29):
adxArr.append(-1)
for i in range(29, len(df)):
adxArr.append(sum(dx[ i-13 : i+1]) / 14)
df['trueRange']= trueRange
df['trueRange14']= trueRange14
df['plusDM']= plusDM
df['minusDM']= minusDM
df['plusDM14']= plusDM14
df['minusDM14']= minusDM14
df['dx']= dx
df['adx']= adxArr
return df