def run_read_noise_task(sensor_id):
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
bias_files = siteUtils.dependency_glob(
'S*/%s_fe55_fe55_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('fe55_raft_acq'),
description='Fe55 files for read noise:')
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
system_noise = None
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
task = sensorTest.ReadNoiseTask()
task.config.temp_set_point = -100.
task.run(sensor_id,
bias_files,
gains,
system_noise=system_noise,
mask_files=mask_files,
use_overscan=True)
# Compute amp-amp correlated noise.
_, corr_fig, _ = correlated_noise(bias_files,
target=0,
make_plots=True,
title=sensor_id)
plt.figure(corr_fig.number)
plt.savefig('%s_correlated_noise.png' % file_prefix)
def run_dark_pixels_task(sensor_id):
"Single sensor execution of the dark pixels task."
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
acq_jobname = siteUtils.getProcessName('sflat_raft_acq')
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
sflat_files = siteUtils.dependency_glob('S*/%s_sflat_500_flat_H*.fits' % sensor_id,
jobname=acq_jobname,
description='Superflat files:')
bias_files = siteUtils.dependency_glob('S*/%s_sflat_bias*.fits' % sensor_id,
jobname=acq_jobname,
description='Bias files:')
bias_frame = eotestUtils.make_median_bias_frame(bias_files, sensor_id,
'sflat_raft_acq')
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
task = sensorTest.DarkPixelsTask()
task.run(sensor_id, sflat_files, mask_files, bias_frame=bias_frame)
siteUtils.make_png_file(sensorTest.plot_flat,
'%s_superflat_dark_defects.png' % file_prefix,
'%s_median_sflat.fits' % sensor_id,
title='%s, superflat for dark defects analysis' % sensor_id,
annotation='ADU/pixel', flatten=True, binsize=4)
def run_trap_task(sensor_id):
"""Run the traps analysis for a single sensor."""
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
trap_file = siteUtils.dependency_glob(
'S*/%s_trap_ppump_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('ppump_raft_acq'),
description='Trap file:')[0]
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
# Omit rolloff defects mask since a trap in the rolloff edge region can
# affect the entire column.
bias_frame = siteUtils.dependency_glob('%s_sflat*median_bias.fits' %
sensor_id,
description='Super bias frame:')[0]
mask_files = [
item for item in mask_files if item.find('rolloff_defects') == -1
]
print("Using mask files:")
for mask_file in mask_files:
print(" " + mask_file)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
task = sensorTest.TrapTask()
task.run(sensor_id, trap_file, mask_files, gains, bias_frame=bias_frame)
def run_dark_pixels_task(sensor_id):
print("run_dark_pixels_task: sensor_id = ", sensor_id)
# raft_id = os.environ['LCATR_UNIT_ID']
# raft = camera_components.Raft.create_from_etrav(raft_id)
# wgSlotName = siteUtils.getWGSlotNames(raft)[sensor_id];
"Single sensor execution of the dark pixels task."
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
sflat_files = siteUtils.dependency_glob(
'S*/%s_sflat_500_flat_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('sflat_raft_acq'),
description='Superflat files:')
print("sflat query: ", 'S*/%s_sflat_500_flat_H*.fits' % sensor_id)
print("sflat_files = ", sflat_files)
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
task = sensorTest.DarkPixelsTask()
task.run(sensor_id, sflat_files, mask_files)
siteUtils.make_png_file(sensorTest.plot_flat,
'%s_superflat_dark_defects.png' % file_prefix,
'%s_median_sflat.fits' % sensor_id,
title='%s, superflat for dark defects analysis' %
sensor_id,
annotation='ADU/pixel')
def run_ptc_task(sensor_id):
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
flat_files = siteUtils.dependency_glob(
'S*/%s_flat*flat?_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('flat_pair_raft_acq'),
description='Flat files:')
bias_frame = siteUtils.dependency_glob('%s_sflat*median_bias.fits' %
sensor_id,
description='Super bias frame:')[0]
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
task = sensorTest.PtcTask()
task.run(sensor_id, flat_files, mask_files, gains, bias_frame=bias_frame)
results_file = '%s_eotest_results.fits' % sensor_id
plots = sensorTest.EOTestPlots(sensor_id, results_file=results_file)
siteUtils.make_png_file(plots.ptcs,
'%s_ptcs.png' % file_prefix,
ptc_file='%s_ptc.fits' % sensor_id)
def run_dark_current_task(sensor_id):
"Single sensor execution of dark current analysis."
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
dark_files = siteUtils.dependency_glob(
'S*/%s_dark_dark_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('dark_raft_acq'),
description='Dark files:')
bias_frame = siteUtils.dependency_glob('%s_sflat*median_bias.fits' %
sensor_id,
description='Super bias frame:')[0]
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
task = sensorTest.DarkCurrentTask()
task.config.temp_set_point = -100.
dark_curr_pixels, dark95s \
= task.run(sensor_id, dark_files, mask_files, gains,
bias_frame=bias_frame)
results_file \
= siteUtils.dependency_glob('%s_eotest_results.fits' % sensor_id,
jobname='read_noise_raft')[0]
plots = sensorTest.EOTestPlots(sensor_id, results_file=results_file)
siteUtils.make_png_file(plots.total_noise,
'%s_noise.png' % file_prefix,
dark95s=dark95s)
def run_bf_task(sensor_id):
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
flat_files = siteUtils.dependency_glob(
'S*/%s_flat*flat1*.fits' % sensor_id,
jobname=siteUtils.getProcessName('flat_pair_raft_acq'),
description='Flat files:')
bias_frame = siteUtils.dependency_glob('%s_sflat*median_bias.fits' %
sensor_id,
description='Superbias files:')[0]
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
task = sensorTest.BFTask()
task.run(sensor_id,
flat_files,
mask_files=mask_files,
bias_frame=bias_frame)
results_file = '%s_eotest_results.fits' % sensor_id
plots = sensorTest.EOTestPlots(sensor_id, results_file=results_file)
siteUtils.make_png_file(plots.bf_curves,
'%s_brighter-fatter.png' % file_prefix,
bf_file='%s_bf.fits' % sensor_id)
def run_qe_task(sensor_id):
try:
if hw_objects[sensor_id] :
return
except:
hw_objects[sensor_id] = True
print("hw_objects = ",hw_objects)
"Single sensor execution of the QE task."
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
lambda_files = siteUtils.dependency_glob('S*/%s_lambda_flat_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('qe_raft_acq'),
description='Lambda files:')
pd_ratio_file = eotestUtils.getPhotodiodeRatioFile()
if pd_ratio_file is None:
message = ("The test-stand specific photodiode ratio file is " +
"not given in config/%s/eotest_calibrations.cfg."
% siteUtils.getSiteName())
raise RuntimeError(message)
correction_image = eotestUtils.getIlluminationNonUniformityImage()
if correction_image is None:
print()
print("WARNING: The correction image file is not given in")
print("config/%s/eotest_calibrations.cfg." % siteUtils.getSiteName())
print("No correction for non-uniform illumination will be applied.")
print()
sys.stdout.flush()
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
task = sensorTest.QeTask()
task.config.temp_set_point = -100.
task.run(sensor_id, lambda_files, pd_ratio_file, mask_files, gains,
correction_image=correction_image)
results_file \
= siteUtils.dependency_glob('%s_eotest_results.fits' % sensor_id,
jobname='fe55_raft_analysis',
description='Fe55 results file')[0]
plots = sensorTest.EOTestPlots(sensor_id, results_file=results_file)
siteUtils.make_png_file(plots.qe,
'%s_qe.png' % file_prefix,
qe_file='%s_QE.fits' % sensor_id)
try:
plots.flat_fields(os.path.dirname(lambda_files[0]),
annotation='e-/pixel, gain-corrected, bias-subtracted')
except Exception as eobj:
print("Exception raised while creating flat fields:")
print(str(eobj))
def run_flat_pair_task(sensor_id):
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
flat_files = siteUtils.dependency_glob(
'S*/%s_flat*flat?_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('flat_pair_raft_acq'),
description='Flat files:')
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
use_exptime = True
if siteUtils.getSiteName() == 'SLAC':
# Since slit-width can be set individually for each exposure
# on TS-8 at IR-2 (LSSTTD-1231), we need to use the MONDIODE
# keyword for computing the integrated incident flux.
use_exptime = False
task = sensorTest.FlatPairTask()
task.run(sensor_id,
flat_files,
mask_files,
gains,
linearity_spec_range=(1e4, 9e4),
use_exptime=use_exptime)
results_file = '%s_eotest_results.fits' % sensor_id
plots = sensorTest.EOTestPlots(sensor_id, results_file=results_file)
Ne_bounds = (1e4, 9e4)
detresp_file = '%s_det_response.fits' % sensor_id
siteUtils.make_png_file(plots.linearity,
'%s_linearity.png' % file_prefix,
detresp_file=detresp_file,
max_dev=0.03,
use_exptime=use_exptime,
Ne_bounds=Ne_bounds)
siteUtils.make_png_file(plots.linearity_resids,
'%s_linearity_resids.png' % file_prefix,
detresp_file=detresp_file,
max_dev=0.03,
Ne_bounds=Ne_bounds,
use_exptime=use_exptime)
def run_trap_task(sensor_id):
trap_file = siteUtils.dependency_glob(
'S*/%s_trap_ppump_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('ppump_raft_acq'),
description='Trap file:')[0]
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
# Omit rolloff defects mask since a trap in the rolloff edge region can
# affect the entire column.
mask_files = [
item for item in mask_files if item.find('rolloff_defects') == -1
]
print("Using mask files:")
for mask_file in mask_files:
print(" " + mask_file)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
task = sensorTest.TrapTask()
task.run(sensor_id, trap_file, mask_files, gains)
def run_bright_pixels_task(sensor_id):
"Single sensor execution of the bright pixels task."
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
dark_files = siteUtils.dependency_glob(
'S*/%s_dark_dark_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('dark_raft_acq'),
description='Dark files:')
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
task = sensorTest.BrightPixelsTask()
task.config.temp_set_point = -100.
task.run(sensor_id, dark_files, mask_files, gains)
siteUtils.make_png_file(
sensorTest.plot_flat,
'%s_medianed_dark.png' % file_prefix,
'%s_median_dark_bp.fits' % sensor_id,
title='%s, medianed dark for bright defects analysis' % sensor_id,
annotation='e-/pixel, gain-corrected, bias-subtracted')
def run_dark_current_task(sensor_id):
"Single sensor execution of dark current analysis."
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
dark_files = siteUtils.dependency_glob(
'S*/%s_dark_dark_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('dark_raft_acq'),
description='Dark files:')
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
task = sensorTest.DarkCurrentTask()
task.config.temp_set_point = -100.
dark_curr_pixels, dark95s \
= task.run(sensor_id, dark_files, mask_files, gains)
results_file \
= siteUtils.dependency_glob('%s_eotest_results.fits' % sensor_id,
jobname='read_noise_raft')[0]
eo_results = sensorTest.EOTestResults(results_file)
read_noise = dict(
pair for pair in zip(eo_results['AMP'], eo_results['TOTAL_NOISE']))
siteUtils.make_png_file(sensorTest.total_noise_histograms,
'%s_total_noise_hists.png' % file_prefix,
dark_curr_pixels,
read_noise,
dark95s,
exptime=16,
title=sensor_id)
plots = sensorTest.EOTestPlots(sensor_id, results_file=results_file)
siteUtils.make_png_file(plots.total_noise,
'%s_noise.png' % file_prefix,
dark95s=dark95s)
#!/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()
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)
from __future__ import print_function
import sys
import lsst.eotest.sensor as sensorTest
import siteUtils
import eotestUtils
import camera_components
raft_id = siteUtils.getUnitId()
raft = camera_components.Raft.create_from_etrav(raft_id)
for sensor_id in raft.sensor_names:
lambda_files = siteUtils.dependency_glob('S*/%s_lambda_flat_*.fits' % sensor_id,
jobname=siteUtils.getProcessName('qe_raft_acq'),
description='Lambda files:')
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
correction_image = eotestUtils.getIlluminationNonUniformityImage()
if correction_image is None:
print()
print("WARNING: The correction image file is not given in")
print("config/%s/eotest_calibrations.cfg." % siteUtils.getSiteName())
print("No correction for non-uniform illumination will be applied.")
print()
sys.stdout.flush()
task = sensorTest.PrnuTask()
task.run(sensor_id, lambda_files, mask_files, gains, correction_image)
def run_cte_task(sensor_id):
"Single sensor execution of the cte task."
file_prefix = '%s_%s' % (sensor_id, siteUtils.getRunNumber())
mask_files = \
eotestUtils.glob_mask_files(pattern='%s_*mask.fits' % sensor_id)
gains = eotestUtils.getSensorGains(jobname='fe55_raft_analysis',
sensor_id=sensor_id)
# Omit rolloff defects mask since it would mask some of the edges used
# in the eper method.
mask_files = [
item for item in mask_files if item.find('rolloff_defects') == -1
]
print("Using mask files:")
for mask_file in mask_files:
print(" " + mask_file)
results_file \
= siteUtils.dependency_glob('%s_eotest_results.fits' % sensor_id,
jobname='fe55_raft_analysis',
description='Fe55 results file')[0]
shutil.copy(results_file, os.path.basename(results_file))
results_file = os.path.basename(results_file)
sflat_high_files = \
siteUtils.dependency_glob('S*/%s_sflat_500_flat_H*.fits' % sensor_id,
jobname=siteUtils.getProcessName('sflat_raft_acq'),
description='Superflat high flux files:')
task = sensorTest.CteTask()
task.run(sensor_id,
sflat_high_files,
flux_level='high',
gains=gains,
mask_files=mask_files)
sflat_low_files = \
siteUtils.dependency_glob('S*/%s_sflat_500_flat_L*.fits' % sensor_id,
jobname=siteUtils.getProcessName('sflat_raft_acq'),
description='Superflat low flux files:')
task.run(sensor_id,
sflat_low_files,
flux_level='low',
gains=gains,
mask_files=mask_files)
plots = sensorTest.EOTestPlots(sensor_id, results_file=results_file)
superflat_files = sorted(glob.glob('%s_superflat_*.fits' % sensor_id))
mask_files = [
x for x in glob.glob('%s*mask.fits' % sensor_id)
if x.find('rolloff') == -1
]
for sflat_file in superflat_files:
flux_level = 'low'
if sflat_file.find('high') != -1:
flux_level = 'high'
siteUtils.make_png_file(
sensorTest.plot_flat,
sflat_file.replace('.fits',
'.png').replace(sensor_id, file_prefix),
sflat_file,
title=('%s, CTE supeflat, %s flux ' % (sensor_id, flux_level)),
annotation='ADU/pixel')
siteUtils.make_png_file(plots.cte_profiles,
('%s_serial_oscan_%s.png' %
(file_prefix, flux_level)),
flux_level,
sflat_file,
mask_files,
serial=True)
siteUtils.make_png_file(plots.cte_profiles,
('%s_parallel_oscan_%s.png' %
(file_prefix, flux_level)),
flux_level,
sflat_file,
mask_files,
serial=False)
