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Introduction

XTCAV is a detector that is used to determine the laser-power vs. time of each LCLS shot.  Alvaro Sanchez-Gonzalez has written psana-python code to do the rather complex analysis of images from the XTCAV camera to determine these quantities.  Some detailed documentation from Tim Maxwell on this device is Here.

Analysis Setup

Two things must be done before XTCAV analysis will function: a "dark run" must be analyzed to get the pedestal values for cameras, and a "no lasing" run must be analyzed to generate sets of "no lasing" images (the latter is quite a complex process).  An example of a dark-run analysis is:

#!/usr/bin/env python
from xtcav.GenerateDarkBackground import *
GDB=GenerateDarkBackground();
GDB.experiment='amoc8114'
GDB.runs='85'
GDB.maxshots=150
GDB.SetValidityRange(85,109)
GDB.Generate();

An example of a non-lasing run is:

#!/usr/bin/env python
from xtcav.GenerateLasingOffReference import *
GLOC=GenerateLasingOffReference();
GLOC.experiment='amoc8114'
GLOC.runs='86'
GLOC.maxshots=401
GLOC.nb=1
GLOC.groupsize=5
GLOC.SetValidityRange(86,91)
GLOC.Generate();

Once the above has been completed, the user can analyze the lasing-on events.

Example Analysis Script

This script assumes that dark/lasing-off data has been analyzed (see above)

import psana
from xtcav.ShotToShotCharacterization import *
maxshots=5             #Maximum number of valid shots to process
experiment='amoc8114'  #Experiment label
runs='87'              #Runs
#Loading the dataset from the "dark" run, this way of working should be compatible with both xtc and hdf5 files
dataSource=psana.DataSource("exp=%s:run=%s:idx" % (experiment,runs))
#XTCAV Retrieval (setting the data source is useful to get information such as experiment name)
XTCAVRetrieval=ShotToShotCharacterization();
XTCAVRetrieval.SetDataSource(dataSource)
for r,run in enumerate(dataSource.runs()):
    times = run.times()
    for t in times:
        evt = run.event(t)
        if not XTCAVRetrieval.SetCurrentEvent(evt):
            continue
        t,power,ok=XTCAVRetrieval.XRayPower()  
        agreement,ok=XTCAVRetrieval.ReconstructionAgreement()

How Often to Take a Lasing Off Run

(courtesy of Tim Maxwell)

That's a very good question. For very stable accelerator conditions, you might not really need to but every hour or two. But, for example with that AMO experiment it drifted measurably over as short as twenty minutes as the beam was a trick setup and some feedbacks needed disabling.

There's not really a hard, fast rule here. When necessary or when time allows has been the practical answer so far.

Lasing-off Analysis Parameters

-NB: Number of bunches. This one is obvious. Just as a note for the future, if at some point you want to do two bunch partial reconstruction (i.e. without lasing off reference), you will need to specify explicitly the number of bunches in an undocumented way (i.e. changing an attribute without a get/set method. Example:

XTCAVRetrieval=ShotToShotCharacterization();
XTCAVRetrieval.SetDataSource(dataSource)
XTCAVRetrieval._nb=2
If you do this, but then it happens that there is a reference available,
and the number of bunches is different, it will take the number of
bunches in the reference file.

-n: number of images: in principle the bigger the better, but around 1400 used to work fine. If you select a bigger number, you will get more references, but it will also take longer to find the right reference shot to shot.

-groupsize: 5 is a good number. Increasing this number will make better references, but they may also make them less accurate, as you would be averaging a larger number of profiles. If you decide to increase this number by a factor, then I would also increase n by the same factor, so in the end the total number of reference is the same.

-roexpand and roiwaistthres: Call the method 'ProcessedXTCAVImage'. If the image does not look clipped, the parameters are fine.

-snrfilter: this one is really sensitive for two bunches, because it sets a threshold based on the noise to higher as the parameter goes up. This means that it is the factor that can separate the two island in case of two bunches, so for two bunch it needs some tweaking until the two bunches are separated for most of the shots. Bottom line:

  • For single bunch: As low as possible while still removing the noise (i.e.) not getting noise current profiles.
  • For double bunch: As low as possible while separating the two bunches. Call the 'ProcessedXTCAVImage' method again, and look at the size of axis 0: this will be the number of bunches detected. You can probably write a program to automatize the determination of this parameter, until you get lets say a 95% of two bunch detection.
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