This page holds a few example code-snippets for use in pyana analysis. The analysis is written in python and uses MatPlotLib.PyPlot for plotting of data. Compare with myana user examples to see how the same things can be done using the myana analysis framework.
Acqiris waveform data
This method can be used for any detector/device that has Acqiris waveform data. Edit the self.address field to get the detector of your choice.
Initialize class members:
def __init__ ( self ):
# initialize data
self.address = "AmoITof-0|Acqiris-0"
self.data = []
self.counter = 0
If you're curious to see any of the Acqiris configuration, e.g. how many channels do we have, you can inspect the AcqConfig object:
def beginjob ( self, evt, env ) :
cfg = env.getConfig( _pdsdata.xtc.TypeId.Type.Id_AcqConfig, self.address )
self.num = cfg.nbrChannels()
The read the event waveform data (an array) and append it to the self.data list:
def event ( self, evt, env ) :
channel = 0
acqData = evt.getAcqValue( self.address, channel, env)
if acqData :
self.counter+=1
wf = acqData.waveform()
self.data.append(wf)
At the end of the job, take the average and plot it:
def endjob( self, env ) :
data = np.array(self.data) # this is an array of shape (Nevents, nSamples)
# take the mean of all events for each sampling time
xs = np.mean(data, axis=0)
plt.plot(xs)
plt.xlabel('Seconds')
plt.ylabel('Volts')
plt.show()
Which gives you a plot like this
Beamline data (Bld)
To read out energy, charge and position of the beam from the beamline data, use getEBeam(). It returns a class/structure that has the following members/fields:
ebeam = evt.getEBeam()
if ebeam :
beamChrg = ebeam.fEbeamCharge
beamEnrg = ebeam.fEbeamL3Energy
beamPosX = ebeam.fEbeamLTUPosX
beamPosY = ebeam.fEbeamLTUPosY
beamAngX = ebeam.fEbeamLTUAngX
beamAngY = ebeam.fEbeamLTUAngY
beamPkCr = ebeam.fEbeamPkCurrBC2
print "ebeam: ", beamChrg, beamEnrg, beamPosX, beamPosY, beamAngX, beamAngY, beamPkCr
else :
print "No EBeam object found"
To read out the energy from the front end enclosure (FEE) gas detector, use getFeeGasDet(). This returns and array of 4 numbers:
fee_energy_array = evt.getFeeGasDet()
gdENRC11 = fee_energy_array[0]
gdENRC12 = fee_energy_array[1]
gdENRC21 = fee_energy_array[2]
gdENRC22 = fee_energy_array[3]
print "GasDet energy ", gdENRC11, gdENRC12, gdENRC21, gdENRC22
To read out fit time and charge of the phase cavity, use getPhaseCavity() which returns a structure with the following fields:
pc = evt.getPhaseCavity()
if pc :
pcFitTime1 = pc.fFitTime1
pcFitTime2 = pc.fFitTime2
pcCharge1 = pc.fCharge1
pcCharge2 = pc.fCharge2
print "PhaseCavity: ", pcFitTime1, pcFitTime2, pcCharge1, pcCharge2
else :
print "No Phase Cavity object found"
Display images from princeton camera
When plotting with MatPlotLib, we don't need to set the limits of the histogram manually, thus we don't need to read the Princeton configuration for this. If we want to sum the image from several events, we must first define and initialize some variables:
def __init__ ( self ):
# initialize data
self.address = "SxrEndstation-0|Princeton-0"
self.data = None
In each event, we add the image array returned from the getPrincetonValue function:
def event ( self, evt, env ) :
frame = evt.getPrincetonValue( self.address, env)
if frame :
# accumulate the data
if self.data is None :
self.data = np.float_(frame.data())
else :
self.data += frame.data()
At the end of the job, display/save the array:
def endjob( self, env ) :
plt.imshow( self.data/self.countpass, origin='lower')
plt.colorbar()
plt.show()
# save the full image to a png file
plt.imsave(fname="pyana_princ_image.png",arr=self.data, origin='lower')
Note that imsave saves the image only, pixel by pixel. If you want a view of the figure itself, lower resolution, you can save it from the interactive window you get from plt.show().
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