def read_data():
d = ixppy.dataset('/reg/g/xpp/data/example_data/diode/time_tool/hdf5/xppi0412-r0113.h5',['timeTool','ipm2','ipm3','diodeU','opal0','eventCode'])
# scanning motor
print d.scanMot
# number of scansteps
print d.noofsteps
return d
def __init__(self,data=None,Iref=None,Imat=None,fina=None):
self.data = data
self.Iref = Iref
self.refDataFilter = 1
if fina is not None:
assert fina[-7:]=='.ixp.h5', "File name has to be of extension ... .ixp.h5"
self.dataset = dataset(fina)
if 'corrNonLin_I0' in self.dataset.__dict__:
self.I0 = self.dataset['corrNonLin_I0']
else:
self.I0 = None
if 'corrNonLin_Imat' in self.dataset.__dict__:
self.Imat = self.dataset['corrNonLin_Imat']
else:
self.Imat = None
else:
self.dataset = None
def extractData(run,calibcycles=None,Nmax=None):
f=open("run%03d_extract.txt" % run,"w")
sys.stderr = f
sys.stout = f
dets = ['ipm2','ipm3',"diodeU","diode3","timeTool","opal0"]
d=ixppy.dataset(('xpp52512',run),dets)
d.filtTimestamps()
ixppy.TTextractProfiles(d.opal0,d.ipm2.sum,Nmax=Nmax,refthreshold=0.01,profileLimits=roiTT,profileLimitsRef=roiTTref,calibcycles=calibcycles)
h=h5.openOrCreateFile("run%03d_extract.h5" % run,"w")
h.attrs["ScanMot"] = d.scanMot
h.attrs["ScanVec"] = d.scanVec
my_steps = []
x=np.arange(1024)
n=200
N=800
fitrange=100
h.attrs["TTfitinfo"] = "from %s to %s (fitrange %d)" % (n,N,fitrange)
for i in range(len(d.opal0.TTtraces)):
my_stepsc=[]
for s in range(len(d.opal0.TTtraces[i])):
if (d.ipm2.sum[i][s] < 0.01):
my_stepsc.append([0,0,0])
else:
y = d.opal0.TTtraces[i][s][n:N]
(step,amp,sig,xfit,yfit)=ttfit(x[n:N],y,fitrange=fitrange)
my_stepsc.append( [step,amp,sig] )
my_steps.append ( np.array(my_stepsc) )
for i in range(len(d.opal0.TTtraces)):
h5w(h,"/c%03d/TTtraces" % i,d.opal0.TTtraces[i].value)
h5w(h,"/c%03d/ipm2" % i,d.ipm2.data[i])
h5w(h,"/c%03d/ipm3" % i,d.ipm3.data[i])
h5w(h,"/c%03d/diodeU" % i,d.diodeU.data[i])
h5w(h,"/c%03d/diode3" % i,d.diode3.data[i])
h5w(h,"/c%03d/TTXPP/pos" % i,d.timeTool.fltpos[i])
h5w(h,"/c%03d/TTXPP/ampl" % i,d.timeTool.ampl[i])
h5w(h,"/c%03d/TTXPP/fwhm" % i,d.timeTool.fltposfwhm[i])
h5w(h,"/c%03d/TTERF/pos" % i,my_steps[i][:,0])
h5w(h,"/c%03d/TTERF/amp" % i,my_steps[i][:,1])
h5w(h,"/c%03d/TTERF/fwhm" % i,my_steps[i][:,2]*2.35)
f.close()
sys.exit(0)
def createWireMask(self,data=None):
if data==None:
import ixppy
d = ixppy.dataset('/reg/g/xpp/data/example_data/cspad/liquid_scattering/hdf5/xpp43512-r0004.h5',['cspad'])
data = d.cspad.rdStepData(0,range(10))
i = np.mean(data,axis=0)
ib = self.bin(i)
tools.imagesc(self.xVec,self.yVec,ib)
tools.clim_std()
pl.draw()
print "Roughly select wire end pairs, press middle mouse button when finished."
wires = []
tpos = np.array(pl.ginput(2))
pointno = 0
while not tpos==[]:
tpos = np.array(tpos)
pl.plot(tpos[:,0],tpos[:,1],'go-')
for pno in range(2):pl.text(tpos[pno,0],tpos[pno,1],str(pointno),color='r')
wires.append(tpos)
pointno += 1
tpos = pl.ginput(2)
refwires = []
for pos in wires:
refwires.append(self._refinePoints(pos,ib))
wirewidths = []
print refwires
for refwire in refwires:
trad = self._getOneWire(refwire,i,rmax=1000)
wirewidths.append(trad)
masked = np.zeros(np.shape(i),dtype=bool)
ax = self.xpx
ay = self.ypx
for refwire,wirewidth in zip(refwires,wirewidths):
points = refwire
m = np.diff(points[:,1])/np.diff(points[:,0])
c = points[0,1] - points[0,0]*m
m_ = -1/m
dist_perp = (ay-m*ax-c)/np.sqrt(m**2+1)
dist_par = (ay-m_*ax)/np.sqrt(m_**2+1)
masked[np.abs(dist_perp)<wirewidth] = True
np.save('cspad_last_pixel_mask.npy',masked)
def readDataFile(fina,fieldname=None):
name,extension = os.path.splitext(fina)
if extension=='.m':
if fieldname is not None:
return loadmat(fina)[fieldname]
else:
return loadmat(fina)
elif extension=='.npy':
return np.load(fina)
elif extension=='.h5':
sname,sext = os.path.splitext(name)
if sext=='.ixp':
return ixppy.dataset(fina)
return h5py.File(fina)
else:
try:
return np.loadtxt(fina)
except Exception(e):
logbook("could not read that file. \nError ---->\n ")
logbook(e)
def timeTool_calibration():
d = ixppy.dataset(('xppi0412',115),['timeTool'])
nfigure('step Timetool hist')
for t in d.timeTool.fltpos:
clf()
hist(t)
def extractFromRunList(runlist,exp,datasetname='opal2',profileLimits=None,xrayoffCode=None,laseroffCode=None,filter=None,save=False):
for run in runlist:
d = ixppy.dataset((exp,run))
logbook("TT extracting from run %d" %run)
extractFromRun(d,datasetname=datasetname,profileLimits=profileLimits,xrayoffCode=xrayoffCode,laseroffCode=laseroffCode,filter=filter,save=save)
logbook("done!")
def calcScan(run,correctnonlin=True):
dark_limit = 0.01
d=ixppy.dataset(('xpp52512',run),['ipm2','ipm3',"diodeU","diode3"])
d.filtTimestamps()
Ncal = len(d.ipm2.sum)
mon2 = d.ipm2.__sum()
mon3 = d.ipm3.__sum()
xpos = d.ipm3.__xpos()
fluo = d.diodeU.__channel0()
tra = d.diode3.__channel0()
mon = mon2
x = d.scanVec
if (d.scanMot == "ccmE_vernier"):
correctnonlin=False
kt.nfigure("Data run %s" % run,figsize=(8,4))
p.clf()
p.subplots_adjust(wspace=0.4, hspace=0.6)
if (correctnonlin):
M = np.hstack(mon[-4:-1])
D = np.hstack(fluo[-4:-1])
idx = (D<1.7) & (M>0.01) & (D>0.01) & (np.abs(D/M -np.median(D/M)) < 0.1)
idx = (D<1.7) & (M>0.01); # & (D>0.01) & (np.abs(D/M -np.median(D/M)) < 0.1)
nonLinFluo.use(M[idx],D[idx])
D = np.hstack(tra[1:4])
idx = (D<1.7) & (M>0.01) & (D>0.01) & (np.abs(D/M -np.median(D/M)) < 0.1)
idx = (D<1.7) & (M>0.01);# & (D>0.01) & (np.abs(D/M -np.median(D/M)) < 0.1)
nonLinTra.use(M[idx],D[idx])
outF=[]
outFinfo=[]
outT=[]
outTinfo=[]
for i in range(Ncal):
m = mon[i]
f = fluo[i]
t = tra[i]
A = utils.myAveragingAndFilter()
A.addFilter( m>dark_limit,"mon > %s" % (dark_limit))
A.addFilter( f<1.7,"fluo<1.7")
# F.add( np.abs(TTs-np.median(TTs))<2*kt.mad(TTs),"TTs 1 sigma")
# print F.info()
if (correctnonlin):
if (i==0):
p.subplot("222",title="Non lin correction")
p.plot(m,f/m,"+",label="fluo before");
p.plot(m,t/m,"+",label="tra before")
(m,f) = nonLinFluo.correct(m,f)
(m,t) = nonLinTra.correct(m,t)
if (i==0):
p.subplot("222",title="Non lin correction")
p.plot(m,f/m,"o",label="fluo after")
p.plot(m,t/m,"o",label="tra after")
p.legend(bbox_to_anchor = (0.8,-0.2))
p.xlabel("mon")
p.ylabel("[fluo|tra]/mon")
(vF,infoF) = A.calcDiodeNormalized(m,f)
outF.append(vF);
outFinfo.append(infoF)
(vT,infoT) = A.calcDiodeNormalized(m,t)
outT.append(vT);
outTinfo.append(infoT)
f=open(g_outdir+"plotScan_run%s_fluo.txt" % run,"w")
f.write("%s " % d.scanMot)
H=A.header()
for h in H:
f.write("%s " % h)
f.write("info\n")
for i in range(Ncal):
f.write("%s " % x[i])
for j in range(len(outF[i])):
f.write("%s " % (outF[i][j]))
f.write("%s\n" % outFinfo[i])
outF=np.array(outF)[:,0]
outT=np.array(outT)[:,0]
f.close()
sub1 = p.subplot("221",title="Fluo run %s" % run)
print x.shape,outF.shape
p.plot(x,outF)
p.subplot("223",title="Tra run %s" % run,sharex=sub1)
p.xlabel(d.scanMot)
p.plot(x,outT,label="run %s" % run)
p.savefig(g_outdir+"plotScan_run%s.pdf" % run,trasparent=True,papertype="a4")
PdfPlots.savefig(trasparent=True,papertype="a4")
for i in range(Ncal):
f.write("%s " % x[i])
for j in range(len(outF[i])):
f.write("%s " % (outF[i][j]))
f.write("%s\n" % outFinfo[i])
outF=np.array(outF)[:,0]
outT=np.array(outT)[:,0]
f.close()
sub1 = p.subplot("221",title="Fluo run %s" % run)
print x.shape,outF.shape
p.plot(x,outF)
p.subplot("223",title="Tra run %s" % run,sharex=sub1)
p.xlabel(d.scanMot)
p.plot(x,outT,label="run %s" % run)
p.savefig(g_outdir+"plotScan_run%s.pdf" % run,trasparent=True,papertype="a4")
PdfPlots.savefig(trasparent=True,papertype="a4")
#format =
#crystal2 = (34,185,"c2 hscan",
# 35,185,"c2
runs = (213,214,215,216,218,219)
runs = (40,41,164,165)
runs = range(40,90)
for r in runs:
print r
d=ixppy.dataset(('xpp52512',r),['ipm2','ipm3',"diodeU","diode3"])
if (hasattr(d,"scanMot") and (d.scanMot == "ccmE_vernier")):
print "|||",r
calcScan(r)
PdfPlots.close()
def _getAttachDropObj(self):
if self._res is None:
self._res = ixppy.dataset(self.resultFile)
self._res['det'] = ixppy.tools.dropObject()
return self._res
