def addMagneticField():
path=r"D:"+os.sep+"DATA"+os.sep+"Acquired_data"
env=Environment()
listeFiles=[]
for file in os.listdir(path):
if file.endswith(".h5"):
listeFiles.append(file[0:-3])
for file in listeFiles:
try:
readHdf5.saveAttr(file,'date',timei,env)
except:
print file+'.tdms not found'
def saveAttr(self):
attr=self.saveL.text()
readHdf5.saveAttr(self.fileName,attr,np.array([self.T,self.dens,self.Vfloat,self.Vplasma]),self.env)
sig1=self.signalChoice1.currentText()
sig2=self.signalChoice2.currentText()
lsample=self.text1.text()
gasindex=self.gas.currentIndex()
temp=self.temp.text()
calculate=self.tempChoice.isChecked()
pickle.dump([sig1,sig2,self.l1,self.r1,self.l2,self.r2,self.l3,self.r3,lsample,gasindex,calculate,temp] , open( "UserLangmuir.dat", "wb" ) )
self.env.process.updateShot([self.fileName])
def addDate():
path=r"D:"+os.sep+"DATA"+os.sep+"Acquired_data"
env=Environment()
listeFiles=[]
for file in os.listdir(path):
if file.endswith(".h5"):
listeFiles.append(file[0:-3])
for file in listeFiles:
try:
timei=time.ctime(os.path.getmtime(path+os.sep+file+'.tdms'))
readHdf5.saveAttr(file,'date',timei,env)
except:
print file+'.tdms not found'
def addWincc():
path=r"D:"+os.sep+"DATA"+os.sep+"Acquired_data"
env=Environment()
listeFiles=[]
for file in os.listdir(path):
#print file[0:2]
if file.endswith(".csv") and file[0:2]=='Is':
#listeFiles.append(file[0:-3])
inputfile=open(path+os.sep+file)
#inputfile.next()
print inputfile.readline()
#timei=datetime.datetime.strptime(inputfile.readline()[13:-1],'%d.%m.%Y %H:%M:%S')
timei=inputfile.readline()[13:-1]
print timei
h5file='0'+file[7:-4]+'_Data'
print h5file
readHdf5.saveAttr(h5file,'date',timei,env)
def convert_csv(fileName,tempo,env):
path=env.path
if tempo:
time.sleep(2)
try:
inputfile=open(path+os.sep+fileName+'.csv')
#inputfile.next()
print inputfile.readline()
#timei=datetime.datetime.strptime(inputfile.readline()[13:-1],'%d.%m.%Y %H:%M:%S')
timei=inputfile.readline()[13:-1]
#print timei
h5file=fileName[7:].zfill(5)+'_Data'
#print h5file
readHdf5.saveAttr(h5file,'date',timei,env)
#print h5file
env.process.updateShot([h5file])
except:
print "Doesn't work"
def calculate(self):
self.results=dict()
#item=self.signalChoice.currentText()
for file in self.fileName:
for item in self.env.getSignals():
try:
print item
time,data,self.sampling=readHdf5.getData(file,item,self.env)
rang=self.p2.getPlotItem().getViewBox().viewRange()
rang2=rang[0]
average=np.mean(data[(time>=rang2[0]) & (time<=rang2[1])])
maxi=np.max(data[(time>=rang2[0]) & (time<=rang2[1])])
mini=np.min(data[(time>=rang2[0]) & (time<=rang2[1])])
# self.results[file]=[average,maxi,mini]
# self.textResult.append(file+':\n'+'Mean: '+str(average)+'\n'+'Max: '+str(maxi)+'\n'+'Min: '+str(mini)+'\n')
nameAttr=self.env.attr(item)+self.attribut.text()
readHdf5.saveAttr(file,nameAttr,np.array([average,maxi,mini]),self.env)
except:
pass
pickle.dump([self.left,self.right,self.attribut.text(),self.signalChoice.currentText()], open( "User.dat", "wb" ) )
class Environment():
def __init__(self):
self.path=r"D:"+os.sep+"ISHTARmay"
def calibr(x):
slope=(76.-23.)/(400.-1400.)
return (x-400.)*slope+76.-33
listePositionspace=[]
for x in listePosition:
listePositionspace.append(calibr(x))
i=0
env=Environment()
while i<len(listeShots):
fileName='00'+str(listeShots[i])+'_Data'
print listeShots[i]
Attrname='position'
value=listePosition[i]
readHdf5.saveAttr(fileName,Attrname,value,env)
Attrname='positionspace'
value=listePositionspace[i]
i=i+1
