#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
lambda_files = siteUtils.datacatalog_glob('*_lambda_flat_*.fits',
testtype='LAMBDA',
imgtype='FLAT',
description='Lambda files:')
mask_files = eotestUtils.glob_mask_files()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
# @todo Set correction image when it becomes available.
correction_image = None
task = sensorTest.PrnuTask()
task.run(sensor_id, lambda_files, mask_files, gains, correction_image)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
# Use Fe55 exposures and the overscan region instead of the bias
# frames since the vendor data are not guaranteed to have the same
# gains for the bias frames.
bias_files = siteUtils.datacatalog_glob('*_fe55_fe55_*.fits',
testtype="FE55",
imgtype="FE55",
description='Bias files (using overscan):')
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
system_noise_files = siteUtils.dependency_glob('noise_*.fits',
jobname=siteUtils.getProcessName('system_noise'))
if not system_noise_files:
system_noise_files = None
mask_files = eotestUtils.glob_mask_files()
task = sensorTest.ReadNoiseTask()
task.run(sensor_id, bias_files, gains,
system_noise_files=system_noise_files, mask_files=mask_files,
use_overscan=True)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
dark_files = siteUtils.datacatalog_glob('*_dark_dark_*.fits',
testtype='DARK',
imgtype='DARK',
description='Dark files:')
mask_files = eotestUtils.glob_mask_files()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
task = sensorTest.DarkCurrentTask()
task.run(sensor_id, dark_files, mask_files, gains)
#!/usr/bin/env python
import os
import lsst.eotest.sensor as sensorTest
import siteUtils
sensor_id = siteUtils.getUnitId()
fe55_files = siteUtils.datacatalog_glob('*_fe55_fe55_*.fits',
testtype="FE55",
imgtype="FE55",
description='Fe55 files:')
# Roll-off defects mask needs an input file to get the vendor
# geometry and will be used for all analyses.
rolloff_mask_file = '%s_rolloff_defects_mask.fits' % sensor_id
sensorTest.rolloff_mask(fe55_files[0], rolloff_mask_file)
task = sensorTest.Fe55Task()
task.run(sensor_id, fe55_files, (rolloff_mask_file,), accuracy_req=0.01)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
ccd_vendor = siteUtils.getCcdVendor()
flat_files = siteUtils.datacatalog_glob('*_flat*flat?_*.fits',
testtype='FLAT',
imgtype='FLAT',
description='Flat files:')
mask_files = eotestUtils.glob_mask_files()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
task = sensorTest.FlatPairTask()
task.run(sensor_id, flat_files, mask_files, gains)
if ccd_vendor == 'ITL':
#
# Perform linearity analysis using special dataset from ITL
try:
flat_files = siteUtils.datacatalog_glob('*_linearity_flat*.fits',
testtype='LINEARITY',
imgtype='FLAT',
description='ITL linearity files:')
if flat_files:
task = sensorTest.LinearityTask()
task.run(sensor_id, flat_files, mask_files, gains)
except:
#!/usr/bin/env python
import os
import lsst.eotest.sensor as sensorTest
import siteUtils
sensor_id = siteUtils.getUnitId()
fe55_files = siteUtils.datacatalog_glob('*_fe55_fe55_*.fits',
testtype="FE55",
imgtype="FE55",
description='Fe55 files:')
# Roll-off defects mask needs an input file to get the vendor
# geometry and will be used for all analyses.
rolloff_mask_file = '%s_rolloff_defects_mask.fits' % sensor_id
sensorTest.rolloff_mask(fe55_files[0], rolloff_mask_file)
task = sensorTest.Fe55Task()
task.run(sensor_id, fe55_files, (rolloff_mask_file, ), accuracy_req=0.01)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
sflat_files = siteUtils.datacatalog_glob('*_sflat_500_flat_H*.fits',
testtype='SFLAT_500',
imgtype='FLAT',
description='Superflat files:')
mask_files = eotestUtils.glob_mask_files()
task = sensorTest.DarkPixelsTask()
task.run(sensor_id, sflat_files, mask_files)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
sflat_high_files = siteUtils.datacatalog_glob('*_sflat_500_flat_H*.fits',
testtype='SFLAT_500',
imgtype='FLAT',
description='Superflat high files:')
task = sensorTest.CteTask()
task.run(sensor_id, sflat_high_files, flux_level='high', gains=gains)
sflat_low_files = siteUtils.datacatalog_glob('*_sflat_500_flat_L*.fits',
testtype='SFLAT_500',
imgtype='FLAT',
description='Superflat low files:')
task = sensorTest.CteTask()
task.run(sensor_id, sflat_low_files, flux_level='low', gains=gains)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
# Use Fe55 exposures and the overscan region instead of the bias
# frames since the vendor data are not guaranteed to have the same
# gains for the bias frames.
bias_files = siteUtils.datacatalog_glob(
'*_fe55_fe55_*.fits',
testtype="FE55",
imgtype="FE55",
description='Bias files (using overscan):')
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
system_noise_files = siteUtils.dependency_glob(
'noise_*.fits', jobname=siteUtils.getProcessName('system_noise'))
if not system_noise_files:
system_noise_files = None
mask_files = eotestUtils.glob_mask_files()
task = sensorTest.ReadNoiseTask()
task.run(sensor_id,
bias_files,
gains,
system_noise_files=system_noise_files,
mask_files=mask_files,
use_overscan=True)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
ccd_vendor = siteUtils.getCcdVendor()
flat_files = siteUtils.datacatalog_glob('*_flat*flat?_*.fits',
testtype='FLAT',
imgtype='FLAT',
description='Flat files:')
mask_files = eotestUtils.glob_mask_files()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
task = sensorTest.FlatPairTask()
task.run(sensor_id, flat_files, mask_files, gains)
if ccd_vendor == 'ITL':
#
# Perform linearity analysis using special dataset from ITL
try:
flat_files = siteUtils.datacatalog_glob(
'*_linearity_flat*.fits',
testtype='LINEARITY',
imgtype='FLAT',
description='ITL linearity files:')
if flat_files:
task = sensorTest.LinearityTask()
task.run(sensor_id, flat_files, mask_files, gains)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
dark_files = siteUtils.datacatalog_glob('*_dark_dark_*.fits',
testtype='DARK',
imgtype='DARK',
description='Dark files:')
mask_files = eotestUtils.glob_mask_files()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
task = sensorTest.DarkCurrentTask()
task.run(sensor_id, dark_files, mask_files, gains)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
flat_files = siteUtils.datacatalog_glob('*_flat*flat?_*.fits',
testtype='FLAT',
imgtype='FLAT',
description='Flat files:')
mask_files = eotestUtils.glob_mask_files()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
task = sensorTest.PtcTask()
task.run(sensor_id, flat_files, mask_files, gains)
#!/usr/bin/env python
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
sensor_id = siteUtils.getUnitId()
trap_file = siteUtils.datacatalog_glob('*_trap_ppump_*.fits',
testtype='TRAP',
imgtype='PPUMP',
description='Trap file:')[0]
mask_files = eotestUtils.glob_mask_files()
gains = eotestUtils.getSensorGains(jobname='fe55_offline')
task = sensorTest.TrapTask()
task.run(sensor_id, trap_file, mask_files, gains)