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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
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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:
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title | outline of a pyana module |
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import numpy as np
import matplotlib.pyplot as plt
from pypdsdata import xtc
class mypyana(object):
def __init__(self,source=""):
self.source = source
self.counter = None
self.array = [] # really just a list
def beginjob(self,evt,env):
self.counter = 0
def event(self,evt,env):
self.counter += 1
# snippet code goes here
thedata = evt.get(xtc.TypeId.Type.Id_SomeType, self.source )
self.array.append( thedata.somevalue )
def endjob(self,evt,env):
print "Job done! Processed %d events. " % self.counter
# place for plotting etc
# convert from python list to a numpy array
self.array = np.array( self.array )
# plot graph
plt.plot(self.array)
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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:
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def event(self,evt,env):
ebeam = evt.getEBeam()
try :
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
except:
print "No EBeam object found"
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To read out the energy from the front end enclosure (FEE) gas detector, use getFeeGasDet()
. This returns and array of 4 numbers:
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title | getFeeGasDet |
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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
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To read out fit time and charge of the phase cavity, use getPhaseCavity()
which returns a structure with the following fields:
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title | getPhaseCavity |
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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
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def event(self, evt, env):
evrdata = evt.getEvrData("NoDetector-0|Evr-0")
for i in range (evrdata.numFifoEvents()):
print "Event code: ", evrdata.fifoEvent(i).EventCode
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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)
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title | EncoderData |
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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"
return
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The time of the event can be obtained within the event function:
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def event ( self, evt, env ) :
event_time = evt.getTime().seconds() + 1.0e-9*evt.getTime().nanoseconds() )
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Currently there are two data structures that holds data from the same type of devices. Depending on DAQ
configuration, they are either DetInfo type or BldInfo type. Here are examples for extracting both types
in the user module event function:
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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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def event(self, evt, env):
ipm = evt.getSharedIpimbValue("HFX-DG3-IMB-02")
# or equivalently:
# ipm = evt.get(xtc.TypeId.Type.Id_SharedIpimb, "HFX-DG3-IMB-02")
try:
### Raw data ###
# arrays of 4 numbers:
ch = [ipm.ipimbData.channel0(),
ipm.ipimbData.channel1(),
ipm.ipimbData.channel2(),
ipm.ipimbData.channel3()]
ch_volt = [ipm.ipimbData.channel0Volts(),
ipm.ipimbData.channel1Volts(),
ipm.ipimbData.channel2Volts(),
ipm.ipimbData.channel3Volts()]
### Feature-extracted data ###
# array of 4 numbers:
fex_channels = ipm.ipmFexData.channel
# scalars:
fex_sum = ipm.ipmFexData.sum
fex_xpos = ipm.ipmFexData.xpos
fex_ypos = ipm.ipmFexData.ypos
except:
pass
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In each event, we add the image array returned from the getPrincetonValue function:
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title | getPrincetonValue |
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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()
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PnCCD image
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title | getPnCcdValue |
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def event(self,evt,env):
try:
frame = evt.getPnCcdValue( self.source, env )
image = frame.data()
except:
pass
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These all use the generic getFrameValue function:
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title | getFrameValue |
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def event(self,evt,env):
try:
frame = evt.getFrameValue( self.source )
image = frame.data()
except:
pass
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The Fast CCD is read out as two 8-bit images, therefore you need this extra line to convert it to the right format.
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title | getFrameValue |
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def event(self,evt,env):
try:
frame = evt.getFrameValue( self.source )
image = frame.data()
except:
pass
# convert to 16-bit integer
image.dtype = np.uint16
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Here's an example of getting CsPad data from an event:
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title | getCsPadQuads |
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def event(self,evt,env):
quads = evt.getCsPadQuads(self.img_source, env)
if not quads :
print '*** cspad information is missing ***'
return
# dump information about quadrants
print "Number of quadrants: %d" % len(quads)
for q in quads:
print " Quadrant %d" % q.quad()
print " virtual_channel: %s" % q.virtual_channel()
print " lane: %s" % q.lane()
print " tid: %s" % q.tid()
print " acq_count: %s" % q.acq_count()
print " op_code: %s" % q.op_code()
print " seq_count: %s" % q.seq_count()
print " ticks: %s" % q.ticks()
print " fiducials: %s" % q.fiducials()
print " frame_type: %s" % q.frame_type()
print " sb_temp: %s" % map(q.sb_temp, range(4))
# image data as 3-dimentional array
data = q.data()
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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:
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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 )
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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 here
Epics Process Variables and ControlConfig
EPICS data is different from DAQ event data. It stores the conditions and settings of the instruments, but values typically change more slowly than your
average shot-by-shot data, and EPICS data is typically updated only when it changes, or every second, or similar. It is not stored in the 'evt' (event) object,
but in the 'env' (environment) object. You typically would read it only at the beginning of each job or if your doing a scan, you'd read it in every calibration cycle:
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title | env.epicsStore() |
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def begincalibcycle(self,evt,env):
## The returned value should be of the type epics.EpicsPvTime.
pv = env.epicsStore().value( pv_name )
if not pv:
logging.warning('EPICS PV %s does not exist', pv_name)
else:
value = pv.value
status = pv.status
alarm_severity = pv.severity
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title | ControlConfig |
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def begincalibcycle(self,evt,env):
ctrl_config = env.getConfig(xtc.TypeId.Type.Id_ControlConfig)
nControls = ctrl_config.npvControls()
for ic in range (0, nControls ):
cpv = ctrl_config.pvControl(ic)
name = cpv.name()
value = cpv.value()
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