read_noise_data = data['READ_NOISE']
system_noise_data = data['SYSTEM_NOISE']
total_noise_data = data['TOTAL_NOISE']
for amp, read_noise, system_noise, total_noise in zip(amps, read_noise_data,
system_noise_data,
total_noise_data):
results.append(lcatr.schema.valid(lcatr.schema.get('read_noise'),
amp=amp, read_noise=read_noise,
system_noise=system_noise,
total_noise=total_noise))
results.extend(siteUtils.jobInfo())
results.append(eotestUtils.eotestCalibrations())
fe55_acq_job_id = siteUtils.get_prerequisite_job_id('*_fe55_fe55_*.fits',
jobname=siteUtils.getProcessName('fe55_acq'))
md = dict(system_noise_file=dict(JOB_ID=fe55_acq_job_id))
results.extend(eotestUtils.eotestCalibsPersist('system_noise_file',
metadata=md))
files = glob.glob('*read_noise?*.fits')
for fitsfile in files:
eotestUtils.addHeaderData(fitsfile, LSST_NUM=sensor_id, TESTTYPE='FE55',
DATE=eotestUtils.utc_now_isoformat(),
CCD_MANU=siteUtils.getCcdVendor().upper())
data_products = [lcatr.schema.fileref.make(item) for item in files]
results.extend(data_products)
lcatr.schema.write_file(results)
lcatr.schema.validate_file()
results = siteUtils.jobInfo()
results.append(eotestUtils.eotestCalibrations())
sensor_id = siteUtils.getUnitId()
qe_data = pyfits.open('%s_QE.fits' % sensor_id)['QE_BANDS'].data
QE = OrderedDict((band, []) for band in qe_data.field('BAND'))
for amp in range(1, 17):
values = qe_data.field('AMP%02i' % amp)
for band, value in zip(QE, values):
QE[band].append(value)
for band in QE:
results.append(lcatr.schema.valid(lcatr.schema.get('qe_analysis'),
band=band, QE=np.mean(QE[band])))
qe_acq_job_id = siteUtils.get_prerequisite_job_id('*_lambda_flat_*.fits',
jobname=siteUtils.getProcessName('qe_acq'))
md = dict(photodiode_ratio_file=dict(JOB_ID=qe_acq_job_id),
illumination_non_uniformity_file=dict(JOB_ID=qe_acq_job_id))
results.extend(eotestUtils.eotestCalibsPersist('photodiode_ratio_file',
'illumination_non_uniformity_file',
metadata=md))
qe_files = glob.glob('*QE*.*')
for item in qe_files:
if item.endswith('.fits'):
eotestUtils.addHeaderData(item, LSST_NUM=sensor_id, TESTTYPE='LAMBDA',
DATE=eotestUtils.utc_now_isoformat(),
CCD_MANU=siteUtils.getCcdVendor().upper())
results.extend([lcatr.schema.fileref.make(item) for item in qe_files])
lcatr.schema.write_file(results)
lcatr.schema.validate_file()
TESTTYPE='LAMBDA',
DATE=eotestUtils.utc_now_isoformat(),
CCD_MANU=ccd_vendor)
results.extend(
[siteUtils.make_fileref(item, folder=slot) for item in qe_files])
# Persist the png files.
metadata = dict(CCD_MANU=ccd_vendor,
LSST_NUM=sensor_id,
TESTTYPE='LAMBDA',
TEST_CATEGORY='EO')
results.extend(
siteUtils.persist_png_files('%s*.png' % sensor_id,
sensor_id,
folder=slot,
metadata=metadata))
sensor_id = raft.sensor_names[0]
qe_acq_job_id = siteUtils.get_prerequisite_job_id(
('S*/%s_lambda_flat_*.fits' % sensor_id),
jobname=siteUtils.getProcessName('qe_raft_acq'))
md = dict(photodiode_ratio_file=dict(JOB_ID=qe_acq_job_id),
illumination_non_uniformity_file=dict(JOB_ID=qe_acq_job_id))
results.extend(
eotestUtils.eotestCalibsPersist('photodiode_ratio_file',
'illumination_non_uniformity_file',
metadata=md))
results.extend(siteUtils.jobInfo())
lcatr.schema.write_file(results)
lcatr.schema.validate_file()
total_noise_data = data['TOTAL_NOISE']
for amp, read_noise, system_noise, total_noise in zip(amps, read_noise_data,
system_noise_data,
total_noise_data):
results.append(
lcatr.schema.valid(lcatr.schema.get('read_noise'),
amp=amp,
read_noise=read_noise,
system_noise=system_noise,
total_noise=total_noise))
results.extend(siteUtils.jobInfo())
results.append(eotestUtils.eotestCalibrations())
fe55_acq_job_id = siteUtils.get_prerequisite_job_id(
'*_fe55_fe55_*.fits', jobname=siteUtils.getProcessName('fe55_acq'))
md = dict(system_noise_file=dict(JOB_ID=fe55_acq_job_id))
results.extend(
eotestUtils.eotestCalibsPersist('system_noise_file', metadata=md))
files = glob.glob('*read_noise?*.fits')
for fitsfile in files:
eotestUtils.addHeaderData(fitsfile,
LSST_NUM=sensor_id,
TESTTYPE='FE55',
DATE=eotestUtils.utc_now_isoformat(),
CCD_MANU=siteUtils.getCcdVendor().upper())
data_products = [lcatr.schema.fileref.make(item) for item in files]
results.extend(data_products)
total_noise_data = data['TOTAL_NOISE']
for amp, read_noise, system_noise, total_noise in zip(
amps, read_noise_data, system_noise_data, total_noise_data):
print "sensor = %s amp = %d read_noise = %f" % (sensor_id, amp,
read_noise)
# results.append(lcatr.schema.valid(lcatr.schema.get('read_noise'),
# amp=amp, read_noise=read_noise,
# system_noise=system_noise,
# total_noise=total_noise))
results.extend(siteUtils.jobInfo())
results.append(eotestUtils.eotestCalibrations())
fe55_acq_job_id = siteUtils.get_prerequisite_job_id(
'*/%s_fe55_fe55_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('fe55_acq'))
md = dict(system_noise_file=dict(JOB_ID=fe55_acq_job_id))
results.extend(
eotestUtils.eotestCalibsPersist('system_noise_file', metadata=md))
files = glob.glob('*read_noise?*.fits')
for fitsfile in files:
eotestUtils.addHeaderData(fitsfile,
LSST_NUM=sensor_id,
TESTTYPE='FE55',
DATE=eotestUtils.utc_now_isoformat(),
CCD_MANU=siteUtils.getCcdVendor().upper())
data_products = [lcatr.schema.fileref.make(item) for item in files]
results.extend(data_products)
sensor_id = siteUtils.getUnitId()
qe_data = pyfits.open('%s_QE.fits' % sensor_id)['QE_BANDS'].data
QE = OrderedDict((band, []) for band in qe_data.field('BAND'))
for amp in range(1, 17):
values = qe_data.field('AMP%02i' % amp)
for band, value in zip(QE, values):
QE[band].append(value)
for band in QE:
results.append(
lcatr.schema.valid(lcatr.schema.get('qe_analysis'),
band=band,
QE=np.mean(QE[band])))
qe_acq_job_id = siteUtils.get_prerequisite_job_id(
'*_lambda_flat_*.fits', jobname=siteUtils.getProcessName('qe_acq'))
md = dict(photodiode_ratio_file=dict(JOB_ID=qe_acq_job_id),
illumination_non_uniformity_file=dict(JOB_ID=qe_acq_job_id))
results.extend(
eotestUtils.eotestCalibsPersist('photodiode_ratio_file',
'illumination_non_uniformity_file',
metadata=md))
qe_files = glob.glob('*QE*.*')
for item in qe_files:
if item.endswith('.fits'):
eotestUtils.addHeaderData(item,
LSST_NUM=sensor_id,
TESTTYPE='LAMBDA',
DATE=eotestUtils.utc_now_isoformat(),
CCD_MANU=siteUtils.getCcdVendor().upper())
results.extend([lcatr.schema.fileref.make(item) for item in qe_files])
read_noise_data = data['READ_NOISE']
system_noise_data = data['SYSTEM_NOISE']
total_noise_data = data['TOTAL_NOISE']
for amp, read_noise, system_noise, total_noise in zip(amps, read_noise_data,
system_noise_data,
total_noise_data):
results.append(lcatr.schema.valid(lcatr.schema.get('read_noise_raft'),
amp=amp, read_noise=read_noise,
system_noise=system_noise,
total_noise=total_noise,
slot=slot,
sensor_id=wgSlotName))
# sensor_id=sensor_id))
# fe55_acq_job_id = siteUtils.get_prerequisite_job_id('S*/%s_fe55_fe55_*.fits' % sensor_id,
fe55_acq_job_id = siteUtils.get_prerequisite_job_id('S*/%s_fe55_fe55_*.fits' % wgSlotName,
jobname=siteUtils.getProcessName('fe55_raft_acq'))
# files = glob.glob('%s_read_noise?*.fits' % sensor_id)
files = glob.glob('%s_read_noise?*.fits' % wgSlotName)
for fitsfile in files:
eotestUtils.addHeaderData(fitsfile, LSST_NUM=sensor_id, TESTTYPE='FE55',
DATE=eotestUtils.utc_now_isoformat(),
CCD_MANU=ccd_vendor)
data_products = [siteUtils.make_fileref(item, folder=slot)
for item in files]
results.extend(data_products)
# Persist the png files.
metadata = dict(CCD_MANU=ccd_vendor, LSST_NUM=sensor_id,
TESTTYPE='FE55', TEST_CATEGORY='EO')
