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These scripts use some XTCAV data that was made public so they should be runnable by all users. The scripts can be found in /reg/g/psdm/tutorials/examplePython/xtcav/ *** in the files xtcavDark.py, xtcavLasingOff.py, xtcavLasingOn.py.
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This script assumes that dark/lasing-off data has been analyzed (see above). Unlike the previous two scripts it reads dark/lasing-off constants from the official calibration-directory. This script can be found in /reg/g/psdm/tutorials/examplePython/xtcav/xtcavLasingOn.py:
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from psana import *
import matplotlib.pyplot as plt
from xtcav.LasingOnCharacterization import *
experiment = 'xpptut15'
run = '302'
mode = 'smd'
ds = psana.DataSource("exp=%s:run=%s:%s" % (experiment, run, mode))
ngood = 0
XTCAVRetrieval=LasingOnCharacterization()
for evt in ds.events():
if not XTCAVRetrieval.processEvent(evt):
continue # continue to next image if analysis fails for some reason
# time and power are lists, with each entry corresponding to
# a bunch number. The number of bunches is set by the GLOC.nb
# parameter in the lasing-off analysis. In general, one should
# also cut on the "agreement" value, which measures the agreement
# between the first and second moment analysis (larger is better).
time, power = XTCAVRetrieval.xRayPower(method='RMS')
agreement = XTCAVRetrieval.reconstructionAgreement()
ngood += 1
print 'Agreement: %g%% ' % (agreement*100)
plt.plot(time[0],power[0])
plt.xlabel('Time (fs)')
plt.ylabel('Lasing Power (GW)')
plt.title('Agreement %4.2f'%agreement)
plt.show()
if ngood > 1:
break |
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