preProc.py
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import math
import numpy as np
import matplotlib.pyplot as plt
def readFile(filename):
data = []
f = open(filename)
lines = f.readlines()
for l in lines:
lineList = l.split(',')
data.append({'order':lineList[0], 'accel':[float(lineList[1]),float(lineList[2]),float(lineList[3])]})
return data
def FFTconversion(data):
accelXList = [i['accel'][0] for i in data]
fftAccelX = np.fft.fft(accelXList).real
accelYList = [i['accel'][1] for i in data]
fftAccelY = np.fft.fft(accelYList).real
accelZList = [i['accel'][2] for i in data]
fftAccelZ = np.fft.fft(accelZList).real
out = []
'''
print len(fftAccelX),len(fftAccelY),len(fftAccelZ)
plt.plot(range(0,len(accelXList)),accelXList,'-')
plt.plot(range(0,len(accelYList)),accelYList,'-')
plt.plot(range(0,len(accelZList)),accelZList,'-')
plt.figure()
plt.plot(range(0,len(fftAccelX)),[math.pow(i,2) for i in fftAccelX],'-') # Quadrado da transformada de fourier
plt.plot(range(0,len(fftAccelY)),[math.pow(i,2) for i in fftAccelY],'-')
plt.plot(range(0,len(fftAccelZ)),[math.pow(i,2) for i in fftAccelZ],'-')
plt.figure()
norma = [math.sqrt(math.pow(i[0],2) + math.pow(i[1],2) + math.pow(i[2],2)) for i in zip(fftAccelX,fftAccelY,fftAccelZ)]
plt.plot(range(0,len(norma)),norma,'-')
plt.show()
'''
for i in range(0,len(fftAccelX)):
out.append({'order':i, 'accel':[fftAccelX[i],fftAccelY[i],fftAccelZ[i]]})
return out
def calcSampleMeasures(data):
out = []
#frame = []
prevModule = 0
for d in data:
d['accel_module'] = module(d['accel'])
d['phi_angle'] = calcPhi(d['accel'])*180/math.pi
d['theta_angle'] = calcTheta(d['accel'])*180/math.pi
d['module_variation'] = math.fabs(d['accel_module'] - prevModule)
out.append(d)
prevModule = d['accel_module']
return out
def buildFrames(data,n=10):
out = []
def divideListNParts(l, n):
ret = []
for i in xrange(0, len(l), n):
ret.append(l[i:i+n])
return ret
frames = divideListNParts(data, n)
for f in frames:
modulesList = [i['accel_module'] for i in f]
modulesVarList = [i['module_variation'] for i in f]
thetaList = [i['theta_angle'] for i in f]
phiList = [i['phi_angle'] for i in f]
accelXFourier = np.fft.fft([i['accel'][0] for i in f]).real
accelYFourier = np.fft.fft([i['accel'][1] for i in f]).real
accelZFourier = np.fft.fft([i['accel'][2] for i in f]).real
FourierNorm = [math.sqrt(math.pow(i[0],2) + math.pow(i[1],2) + math.pow(i[2],2)) for i in zip(accelXFourier, accelYFourier, accelZFourier)]
#print max(FourierNorm[2:20])#Walk Detecting
#plt.plot(range(0,len(FourierNorm)),FourierNorm,'-')
#plt.show()
FourierMax_20HZ = abs(max(FourierNorm[2:30]) - min(FourierNorm[2:20]))#max(FourierNorm[2:20])#Walk Detecting
thetaMean = np.mean(thetaList)
thetaMin = min(thetaList)
thetaMax = max(thetaList)
phiMean = np.mean(phiList)
phiMin = min(phiList)
phiMax = max(phiList)
modulesMean = np.mean(modulesList)
modulesMin = min(modulesList)
modulesMax = max(modulesList)
modulesVarMean = np.mean(modulesVarList)
modulesVarMin = min(modulesVarList)
modulesVarMax = max(modulesVarList)
out.append({
'FourierMax20Hz':FourierMax_20HZ,
'thetaMean':thetaMean,
'thetaMin':thetaMin,
'thetaMax':thetaMax,
'phiMean':phiMean,
'phiMin':phiMin,
'phiMax':phiMax,
'modulesMean':modulesMean,
'modulesMin':modulesMin,
'modulesMax':modulesMax,
'modulesVarMean':modulesVarMean,
'modulesVarMin':modulesVarMin,
'modulesVarMax':modulesVarMax})
return out
def generateCSV(filename,className,frameLength,data,start=True):#,startIndex=1):
f = open(filename,'a')
i = 1#startIndex
if(start):
f.write("thetaMean,thetaMin,thetaMax,phiMean,phiMin,phiMax,modulesMean,modulesMin,modulesMax,modulesVarMean,modulesVarMin,modulesVarMax,FourierMax20Hz,class\n")
for l in data:
f.write(#str(i)+","+
#str(frameLength)+","+
str(l['thetaMean'])+","+
str(l['thetaMin'])+","+
str(l['thetaMax'])+","+
str(l['phiMean'])+","+
str(l['phiMin'])+","+
str(l['phiMax'])+","+
str(l['modulesMean'])+","+
str(l['modulesMin'])+","+
str(l['modulesMax'])+","+
str(l['modulesVarMean'])+","+
str(l['modulesVarMin'])+","+
str(l['modulesVarMax'])+","+
str(l['FourierMax20Hz'])+","+
className+"\n")
i+=1
f.close()
def calcPhi(vector):
return math.atan(vector[0]/vector[1])
def calcTheta(vector):
return math.atan(vector[2]/(math.sqrt(math.pow(vector[0],2) + math.pow(vector[1],2))))
def module(vector):
return math.sqrt(math.pow(vector[0],2) + math.pow(vector[1],2) + math.pow(vector[2],2))
###################################################################################################################
frameLength = 100
className = ["Correr","Bicicleta","Andar","Carro"]
filenameIN = ["Correr.csv","Bike.csv","Andar2.csv","Carro2.csv"]
filenameOUT = "AllOUT.csv"
#start_i = 211
for i in range(0,len(className)):
data = readFile(filenameIN[i])
#data2 = FFTconversion(data)
out = calcSampleMeasures(data)
print out
#out2 = buildFrames(out,frameLength)
#generateCSV(filenameOUT,className[i],frameLength,out2,(i==0))
'''
a1 = plt.subplot(3,1,1)#a1 = plt.subplot(341)
a1.plot(range(0,len(out2)),[i['modulesMin'] for i in out2],'-',color='red')
a1.set_title('Modules Minimum')
a2 = plt.subplot(3,1,2)#a2 = plt.subplot(345)
a2.plot(range(0,len(out2)),[i['modulesMax'] for i in out2],'-',color='green')
a2.set_title('Modules Maximum')
a3 = plt.subplot(3,1,3)#a3 = plt.subplot(349)
a3.plot(range(0,len(out2)),[i['modulesMean'] for i in out2],'-',color='blue')
a3.set_title('Modules Mean')
plt.figure()
b1 = plt.subplot(3,1,1)#b1 = plt.subplot(342)
b1.plot(range(0,len(out2)),[i['modulesVarMin'] for i in out2],'-',color='red')
b1.set_title('Modules Variation Minimum')
b1 = plt.subplot(3,1,2)#b1 = plt.subplot(346)
b1.plot(range(0,len(out2)),[i['modulesVarMax'] for i in out2],'-',color='green')
b1.set_title('Modules Variation Maximum')
b1 = plt.subplot(3,1,3)#b1 = plt.subplot(3,4,10)
b1.plot(range(0,len(out2)),[i['modulesVarMean'] for i in out2],'-',color='blue')
b1.set_title('Modules Variation Mean')
plt.figure()
c1 = plt.subplot(3,1,1)#c1 = plt.subplot(343)
c1.plot(range(0,len(out2)),[i['thetaMin'] for i in out2],'-',color='red')# modulo ??
c1.set_title('Theta Minimum')
c1 = plt.subplot(3,1,2)#c1 = plt.subplot(347)
c1.plot(range(0,len(out2)),[i['thetaMax'] for i in out2],'-',color='green')
c1.set_title('Theta Maximum')
c1 = plt.subplot(3,1,3)#c1 = plt.subplot(3,4,11)
c1.plot(range(0,len(out2)),[i['thetaMean'] for i in out2],'-',color='blue')
c1.set_title('Theta Mean')
plt.figure()
d1 = plt.subplot(3,1,1)#d1 = plt.subplot(344)
d1.plot(range(0,len(out2)),[i['phiMin'] for i in out2],'-',color='red')
d1.set_title('Phi Minimum')
d1 = plt.subplot(3,1,2)#d1 = plt.subplot(348)
d1.plot(range(0,len(out2)),[i['phiMax'] for i in out2],'-',color='green')
d1.set_title('Phi Maximum')
d1 = plt.subplot(3,1,3)#d1 = plt.subplot(3,4,12)
d1.plot(range(0,len(out2)),[i['phiMean'] for i in out2],'-',color='blue')
d1.set_title('Phi Mean')
plt.subplots_adjust(hspace = 0.4)
plt.show()
'''