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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 (some of) the same things can be done using the myana analysis framework. The most reliable place for up-to-date information about all the event getters in pyana, see: https://confluence.slac.stanford.edu/display/PCDS/Pyana+Reference+Manual#PyanaReferenceManual-Classpyana.event.Event^{Image Removed}

For all the examples, you may assume that the pyana module contains a class with at least 'beginjob', 'event' and 'endjob' functions that starts something like this:

...

    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]

    energy = (gdENRC21 -+ gdENRC22) / 2.0
    # or use the first two that has a different gain:
    energy = (gdENRC11 -+ gdENRC12) / 2.0

BeamLine Data: Phase Cavity

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     pc = evt.getPhaseCavity()
     try:
         pcFitTime1 = pc.fFitTime1
         pcFitTime2 = pc.fFitTime2
         pcCharge1 = pc.fCharge1
         pcCharge2 = pc.fCharge2
         print "PhaseCavity: ", pcFitTime1,  pcFitTime2, pcCharge1, pcCharge2
      except :
         print "No Phase Cavity object found"

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Event code

def event(self, evt, env):
    try: evrdata = evt.getEvrData("NoDetector-0|Evr-0")
    
    for i encoderin =range evt(evrdata.get(xtc.TypeId.Type.Id_EncoderData, self.enc_source )
numFifoEvents()):
        print "Event code: ", evrdata.fifoEvent(i).EventCode

In the example above, the address of the EvrData object is given as "NoDetector-0|Evr-0". The address may be different in other cases, so make sure you have the correct address. If you don't know what it is, you can use 'pyxtcreader -vv <xtcfile> | less' to browse your xtcfile and look for it. Look for a lines with 'contains=EvrConfig_V' or 'contains=EvrData_V'. The address will be found on the same line in 'src=DetInfo(<address>)'

Encoder data (delay scanner)

def event(self,evt,env):
    try:
        encoder = evt.get(xtc.TypeId.Type.Id_EncoderData, self.enc_source )
        encoder_value = encoder.value()
    except:
        print "No encoder found in this event"
         encoder_value = encoder.value()
    except:
        print "No encoder found in this event"
        return

You could combine it with phase cavity time, and compute a time delay from it, for example (I don't know the origin of these parameters!):

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def event(self, evt, env):
    # raw data
    ipmRaw = evt.get(xtc.TypeId.Type.Id_IpimbData, source )
    try:
        ch = [ipmRaw.channel0(),
              ipmRaw.channel1(),
              ipmRaw.channel2(),
              ipmRaw.channel3() ]
                
        ch_volt = [ipmRaw.channel0Volts(),
                   ipmRaw.channel1Volts(),
                   ipmRaw.channel2Volts(),
                   ipmRaw.channel3Volts() ]
    except:
        pass

    # feature-extracted data
    ipmFex = evt.get(xtc.TypeId.Type.Id_IpmFex, source )
    try:
         # array of 4 numbers
         fex_channel = ipmFex.channel 

         # scalar values
         fex_sum = ipmFex.sum 
         fex_xpos = ipmFex.xpos
         fex_ypos = ipmFex.ypos

     except:
         pass

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So far so good. 'quads' is a list of CsPad Element objects, and not necessarily ordered in the expected way. So you'll need to use q.quad() to obtain the quad number.
q.data() gives you a 3D numpy array [row][col][sec]. Here sections will be ordered as expected, but be aware in case of missing sections, that you may need to check the
configuration object. You can get that from the env object, typically something you do in beginjob:

def beginjob(self,evt,env):
    config = env.getConfig(xtc.TypeId.Type.Id_CspadConfig, self.img_source)
    if not config:
        print '*** cspad config object is missing ***'
        return        
    print "Cspad configuration"
    print "  N quadrants   : %d" % config.numQuads()
    print "  Quad mask     : %#x" % config.quadMask()
    print "  payloadSize   : %d" % config.payloadSize()
    print "  badAsicMask0  : %#x" % config.badAsicMask0()
    print "  badAsicMask1  : %#x" % config.badAsicMask1()
    print "  asicMask      : %#x" % config.asicMask()
    print "  numAsicsRead  : %d" % config.numAsicsRead()

   # get the indices of sections in use:
   qn = range(0,config.numQuads())               
   self.sections = map(config.sections, qn  )        
   self.sections = map(config.sections, qn )        

If you want to draw the whole CsPad image, there's currently no pyana function that does this. Pyana only supplies the pixels in a numpy array, and the
exact location of each pixel depends on the conditions at the time of data collection. A simplified way of making the image can be seen in cspad_simple.py(newer version (cspad.py) available if you check out the XtcExplorer package).

CSPad pixel coordinates.

The CSPad detector image can be drawn by positioning the sections from the data array into a large image array. This is done in cspad_simple.py above. The positions are extracted from optical meterology measurements and additional calibrations. Alternatively one can find the coordinate of each individual pixel from a pixel map, based on the same optical metrology measurements. This is described in details hereIf you want to draw the whole CsPad image, there's currently no pyana function that does this. Pyana only supplies the pixels in a numpy array, and the
exact location of each pixel depends on the conditions at the time of data collection. A simplified way of making the image can be seen in cspad_simple.py

Epics Process Variables and ControlConfig

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