def calculate(self):
attr1=[]
attr2=[]
for fileName in self.fileName:
error=False
try:
value1=readHdf5.getAttr(fileName,self.attr1.text(),self.env)
if isinstance(value1,float) or isinstance(value1,int):
attr1.append(value1)
else:
attr1.append(value1[0])
error=True
value2=readHdf5.getAttr(fileName,self.attr2.text(),self.env)
if isinstance(value2,float) or isinstance(value2,int):
print value2
attr2.append(value2)
else:
attr2.append(value2[0])
except:
if error:
attr2.append(0.0)
continue
#print attr1,attr2[0]
#print attr1,attr2
self.p1.plot(attr1,attr2,pen=None,symbol='o')
fit = np.polyfit(attr1,attr2,1)
xx=np.linspace(min(attr1),max(attr1),200)
self.p1.plot(xx,np.poly1d(fit)(xx))
print fit
def start(self):
smallcoils=float(self.smallC.text())
addcoil=float(self.addC.text())
text=self.bigC.text()
if text=='auto':
try:
bigcoil=readHdf5.getAttr(self.fileName,'magnetic',self.env)
except:
text='2000'
self.smallC.setText('2000')
if not(text=='auto'):
bigcoil=float(text)
file = open('2015_07_22_MFC_003_adBcoil.FEM', 'r')
i=1
for line in file:
if i==55:
line=line.split('=')[0]+'='+str(smallcoils)+'\n'
if i==61:
line=line.split('=')[0]+'='+str(-smallcoils)+'\n'
if i==67:
line=line.split('=')[0]+'='+str(bigcoil)+'\n'
if i==73:
line=line.split('=')[0]+'='+str(-bigcoil)+'\n'
if i==79:
line=line.split('=')[0]+'='+str(addcoil)+'\n'
if i==85:
line=line.split('=')[0]+'='+str(-addcoil)+'\n'
i=i+1
command="C:"+os.sep+"femm42"+os.sep+"bin"+os.sep+"femm.exe"
path=r"D:"+os.sep+"DATA"+os.sep+"IShTAR_Process"
script1="-lua-script="+path+os.sep+"LUA_code_003.lua"
script2=" -windowhide"
command=command+' '+script1+' '+script2
print command
print script1,script2
call(command,shell=True)
def start(self):
def calibr(x):
slope=(76.-23.)/(400.-1400.)
return (x-400.)*slope+76.-33
def calibr2(x):
return 10**(((x-0.02- 2.2503)/0.0520+10)/10)
pos=[]
data1=[]
data2=[]
data3=[]
data4=[]
data1max=[]
data2max=[]
data3max=[]
data4max=[]
data1min=[]
data2min=[]
data3min=[]
data4min=[]
for x in self.fileName:
try:
pos.append(readHdf5.getAttr(x,'positionSpace',self.env))
except:
continue
try:
attr=self.l1.text()
print attr
if attr=='':
data1.append(0.)
data1min.append(0.)
data1max.append(0.)
else:
# attr2=attr
# if attr=='VplasmaHP' or attr=='VplasmaLP':
# attr2='density'+attr[-1:-2]
# if attr=='VfloatHP' or attr=='VfloatLP':
#
# attr2='density'+attr[-1:-2]
# if attr=='tempHP' or attr=='tempLP':
# attr2='density'+attr[-1:-2]
# data=readHdf5.getAttr(x,attr2,self.env)
# attr=attr2
data=readHdf5.getAttr(x,attr,self.env)
# if (attr=='fastHP' or attr=='fastLP' or attr=='slowLP' or attr=='slowHP'):
# data=calibr2(data[0])
# if attr=='densityHP' or attr=='densityLP':
# data=data[1]
# if attr=='vplasmaHP' or attr=='vplasmaLP':
# data=data[3]
# if attr=='vfloatHP' or attr=='vfloatLP':
#
# data=data[2]
# if attr=='tempHP' or attr=='tempLP':
# data=data[0]
data1.append(data[0])
data1max.append(data[1])
data1min.append(data[2])
except:
pass
try:
attr=self.l2.text()
if attr=='':
data2.append(0.)
data2min.append(0.)
data2max.append(0.)
else:
data=readHdf5.getAttr(x,attr,self.env)
data2.append(data[0])
data2max.append(data[1])
data2min.append(data[2])
except:
pass
try:
attr=self.l3.text()
if attr=='':
data3.append(0.)
data3min.append(0.)
data3max.append(0.)
else:
data=readHdf5.getAttr(x,attr,self.env)
data3.append(data[0])
data3max.append(data[1])
data3min.append(data[2])
except:
pass
try:
attr=self.l4.text()
if attr=='':
data4.append(0.)
data4min.append(0.)
data4max.append(0.)
else:
data=readHdf5.getAttr(x,attr,self.env)
data4.append(data[0])
data4max.append(data[1])
data4min.append(data[2])
except:
pass
#self.p1.plot(title='Fast Wave profile High Power')
self.p0.clear()
self.p0.plot(pos,data1,pen=None,symbolPen='w')
self.p0.setLabel('bottom', "Position/Center (cm)")
self.p1.clear()
self.p1.plot(pos,data2,pen=None,symbolPen='w')
self.p1.setLabel('bottom', "Position/Center (cm)")
self.p2.clear()
self.p2.plot(pos,data3,pen=None,symbolPen='w')
self.p2.setLabel('bottom', "Position/Center (cm)")
self.p3.clear()
self.p3.plot(pos,data4,pen=None,symbolPen='w')
self.p3.setLabel('bottom', "Position/Center (cm)")
self.p1.setXLink(self.p0)
self.p2.setXLink(self.p0)
self.p3.setXLink(self.p0)
err = pg.ErrorBarItem(x=np.array(pos), y=np.array(data1), top=np.array(data1max), bottom=np.array(data1min), beam=0.5)
self.p0.addItem(err)
err = pg.ErrorBarItem(x=np.array(pos), y=np.array(data2), top=np.array(data2max), bottom=np.array(data2min), beam=0.5)
self.p1.addItem(err)
err = pg.ErrorBarItem(x=np.array(pos), y=np.array(data3), top=np.array(data3max), bottom=np.array(data3min), beam=0.5)
self.p2.addItem(err)
err = pg.ErrorBarItem(x=np.array(pos), y=np.array(data4), top=np.array(data4max), bottom=np.array(data4min), beam=0.5)
self.p3.addItem(err)
# indices = np.argsort(pos)
# pos=np.array(pos)[indices]
# pos,idx=np.unique(pos,return_index=True)
# fast=np.array(fast)[indices]
# fast=fast[idx]
# tck = splrep(pos,fast,s=100 )
# x2 = np.linspace(pos[0], pos[-1], 200)
# y2 = splev(x2, tck)
# p1.plot(x2,y2,pen=(255,0,0))
self.show()
def convertGenerator(fileN, firstShot, lastShot, env):
# filename=r'D:\DATA\IShTAR_Process\data_20150119_20150715.csv'
filename = os.path.normpath(fileN)
shotstart = firstShot
shotend = lastShot
included_cols = [1, 2, 3, 11, 12]
df = pd.read_csv(filename, sep="\t", parse_dates=[0])
print df.dtypes
df.loc[df["ForwardPower[W]"] != 0, "Run"] = 1
#
df["block"] = (df.Run.shift(1) != df.Run).astype(int).cumsum()
df.reset_index().groupby(["Run", "block"])["index"].apply(lambda x: np.array(x))
df = df[df["Run"] == 1]
nbr = np.max(df["block"]) / 2
# print nbr
liste = np.arange(shotstart, shotend)
listefile = []
for x in liste:
listefile.append(str(x).zfill(5) + "_Data")
# print listefile
j = 2
timediff = datetime.timedelta(minutes=1, seconds=0)
timecorrection = datetime.timedelta(minutes=11, seconds=10)
# path=r"D:"+os.sep+"DATA"+os.sep+"Acquired_data"
path = env.path
for x in listefile:
# timei=datetime.datetime.strptime(time.ctime(os.path.getmtime(path+os.sep+x+'.h5')),"%a %b %d %H:%M:%S %Y")
try:
timea = readHdf5.getAttr(x, "date", env)
timei = datetime.datetime.strptime(timea, "%d.%m.%Y %H:%M:%S")
# print x
matched = False
while not (matched):
data0 = df[df["block"] == j]["Time"].values
timef = datetime.datetime.utcfromtimestamp(
(data0[0] - np.datetime64("1970-01-01T00:00:00Z")) / np.timedelta64(1, "s")
)
print timei, (timef + timecorrection), timef
timef = timef + timecorrection
if timei > timef:
deltat = timei - timef
else:
deltat = timef - timei
print deltat
if deltat <= timediff:
data = df[df["block"] == j]["ForwardPower[W]"].values
data2 = df[df["block"] == j]["ReflectedPower[W]"].values
sampling = 1 / (float((data0[1] - data0[0]).item()) * 1e-9)
hdf5 = h5py.File(path + os.sep + x + ".h5", "a")
grouph = hdf5.create_group("Generator")
grouph.create_dataset("Fpower", data=data, compression="gzip")
grouph.create_dataset("Rpower", data=data2, compression="gzip")
grouph.attrs["sampling"] = sampling
j = j + 2
matched = True
print "Generator for " + x
if (deltat > timediff) and (timei > timef) and (j < nbr):
j = j + 2
print "Power without discharge"
if (deltat > timediff) and (timei > timef) and (j >= nbr):
matched = True
if (deltat > timediff) and (timei < timef):
matched = True
print "No generator for " + x
except:
pass
