def test_nrs_msa_spec2(self):
"""
Regression test of calwebb_spec2 pipeline performed on NIRSpec MSA data.
"""
input = 'f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod.fits'
input_file = self.get_data(self.test_dir, input)
self.get_data(self.test_dir, 'jw95065006001_0_short_msa.fits')
# define step for use in test
step = Spec2Pipeline()
step.save_results = True
step.save_bsub = False
step.output_use_model = True
step.resample_spec.save_results = True
step.extract_1d.save_results = True
step.extract_1d.smoothing_length = 0
step.extract_1d.bkg_order = 0
step.run(input_file)
outputs = [
('f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod_cal.fits',
'f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod_cal_ref.fits'
),
('f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod_s2d.fits',
'f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod_s2d_ref.fits'
),
('f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod_x1d.fits',
'f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod_x1d_ref.fits'
)
]
self.compare_outputs(outputs)
def test_mrs_spec2(self):
"""
Regression test of calwebb_spec2 pipeline performed on MIRI MRS data.
"""
self.rtol = 0.000001
input_file = self.get_data(self.test_dir,
'jw10001001001_01101_00001_mirifushort_rate.fits')
step = Spec2Pipeline()
step.save_bsub=True,
step.save_results=True
step.resample_spec.save_results = True
step.cube_build.save_results = True
step.extract_1d.save_results = True
step.run(input_file)
outputs = [('jw10001001001_01101_00001_mirifushort_cal.fits',
'jw10001001001_01101_00001_mirifushort_cal_ref.fits',
['primary','sci','err','dq','relsens2d']),
('jw10001001001_01101_00001_mirifushort_s3d.fits',
'jw10001001001_01101_00001_mirifushort_s3d_ref.fits',
['primary','sci','err','dq','wmap']),
('jw10001001001_01101_00001_mirifushort_x1d.fits',
'jw10001001001_01101_00001_mirifushort_x1d_ref.fits',
['primary','extract1d'])
]
self.compare_outputs(outputs)
def test_miri_lrs_slit_1(self):
"""
Regression test of calwebb_spec2 pipeline performed on a single
MIRI LRS fixed-slit exposure.
"""
input_file = self.get_data(self.test_dir,
'jw00035001001_01101_00001_MIRIMAGE_rate.fits')
step = Spec2Pipeline()
step.save_bsub=True,
step.save_results=True
step.resample_spec.save_results = True
step.cube_build.save_results = True
step.extract_1d.save_results = True
step.run(input_file)
outputs = [('jw00035001001_01101_00001_MIRIMAGE_cal.fits',
'jw00035001001_01101_00001_MIRIMAGE_cal_ref.fits',
['primary','sci','err','dq','relsens']),
('jw00035001001_01101_00001_MIRIMAGE_x1d.fits',
'jw00035001001_01101_00001_MIRIMAGE_x1d_ref.fits',
['primary','extract1d'])
]
self.compare_outputs(outputs)
def test_mrs2pipeline1(self):
"""
Regression test of calwebb_spec2 pipeline performed on MIRI MRS data.
"""
test_dir = 'test_mrs2pipeline'
self.ref_loc = ['test_mrs2pipeline', 'truth']
input_file = self.get_data(test_dir,
'jw80500018001_02101_00002_MIRIFUSHORT_rate.fits')
step = Spec2Pipeline()
step.save_bsub=True,
step.save_results=True
step.resample_spec.save_results = True
step.cube_build.save_results = True
step.extract_1d.save_results = True
step.run(input_file)
outputs = [('jw80500018001_02101_00002_MIRIFUSHORT_cal.fits',
'jw80500018001_02101_00002_MIRIFUSHORT_cal_ref.fits',
['primary','sci','err','dq']),
('jw80500018001_02101_00002_MIRIFUSHORT_s3d.fits',
'jw80500018001_02101_00002_MIRIFUSHORT_s3d_ref.fits',
['primary','sci','err','dq','wmap']),
('jw80500018001_02101_00002_MIRIFUSHORT_x1d.fits',
'jw80500018001_02101_00002_MIRIFUSHORT_x1d_ref.fits',
['primary','extract1d'])
]
self.compare_outputs(outputs)
def test_nrs2_nodata_api(envopt, _jail):
"""
Regression test of handling NRS2 detector that has no data.\
"""
# Only need to ensure that assing_wcs is run.
# This still will fail and should cause the pipeline to halt.
step = Spec2Pipeline()
step.assign_wcs.skip = False
with pytest.raises(NoDataOnDetectorError):
step.run(
get_bigdata('jwst-pipeline', envopt, 'nirspec', 'test_assignwcs',
'jw84700006001_02101_00001_nrs2_rate.fits'))
def test_nrs_fs_multi_spec2(self, input, outputs):
"""
Regression test of calwebb_spec2 pipeline performed on NIRSpec data.
"""
input_file = self.get_data(self.test_dir, input)
step = Spec2Pipeline()
step.save_bsub = True
step.save_results = True
step.resample_spec.save_results = True
step.cube_build.save_results = True
step.extract_1d.save_results = True
step.run(input_file)
self.compare_outputs(outputs)
def test_nirspec_nrs2_nodata_api(_jail, rtdata, fitsdiff_default_kwargs):
"""
Test of calwebb_spec2 pipeline performed on NIRSpec IFU exposure
that has a filter/grating combination that produces no data on
the NRS2 detector. Pipeline should raise an exception.
"""
# Get the input file
rtdata.get_data('nirspec/ifu/jw84700006001_02101_00001_nrs2_rate.fits')
# Call the Spec2Pipeline
step = Spec2Pipeline()
step.assign_wcs.skip = False
with pytest.raises(NoDataOnDetectorError):
step.run(rtdata.input)
def test_nrs_fs_single_spec2(self):
"""
Regression test of calwebb_spec2 pipeline performed on NIRSpec fixed-slit data
that uses a single-slit subarray (S200B1).
"""
input_file = self.get_data(self.test_dir,
'jw84600002001_02101_00001_nrs2_rate.fits')
step = Spec2Pipeline()
step.save_bsub = True
step.save_results = True
step.resample_spec.save_results = True
step.cube_build.save_results = True
step.extract_1d.save_results = True
step.run(input_file)
outputs = [('jw84600002001_02101_00001_nrs2_cal.fits',
'jw84600002001_02101_00001_nrs2_cal_ref.fits'),
('jw84600002001_02101_00001_nrs2_s2d.fits',
'jw84600002001_02101_00001_nrs2_s2d_ref.fits'),
('jw84600002001_02101_00001_nrs2_x1d.fits',
'jw84600002001_02101_00001_nrs2_x1d_ref.fits')]
self.compare_outputs(outputs)
def test_miri_lrs_bkgnod(self):
"""
Regression test of calwebb_spec2 pipeline performed on an association
of nodded MIRI LRS fixed-slit exposures.
"""
asn_file = self.get_data(self.test_dir,
'lrs_bkgnod_asn.json')
for file in raw_from_asn(asn_file):
self.get_data(self.test_dir, file)
step = Spec2Pipeline()
step.save_bsub=True,
step.save_results=True
step.resample_spec.save_results = True
step.cube_build.save_results = True
step.extract_1d.save_results = True
step.run(asn_file)
outputs = [('test_lrs1_bsub.fits', 'test_lrs1_bsub_ref.fits',
['primary','sci','err','dq']),
('test_lrs2_bsub.fits','test_lrs2_bsub_ref.fits',
['primary','sci','err','dq']),
('test_lrs3_bsub.fits','test_lrs3_bsub_ref.fits',
['primary','sci','err','dq']),
('test_lrs4_bsub.fits','test_lrs4_bsub_ref.fits',
['primary','sci','err','dq']),
('test_lrs1_cal.fits', 'test_lrs1_cal_ref.fits',
['primary','sci','err','dq','relsens']),
('test_lrs2_cal.fits', 'test_lrs2_cal_ref.fits',
['primary','sci','err','dq','relsens']),
('test_lrs3_cal.fits', 'test_lrs3_cal_ref.fits',
['primary','sci','err','dq','relsens']),
('test_lrs4_cal.fits', 'test_lrs4_cal_ref.fits',
['primary','sci','err','dq','relsens'])
]
self.compare_outputs(outputs)
def test_miri_lrs_slit_1b(self):
"""
Regression test of calwebb_spec2 pipeline performed on a single
MIRI LRS fixed-slit exposure with multiple integrations. Compare _calints.
"""
input_file = self.get_data(self.test_dir,
'jw00035001001_01101_00001_MIRIMAGE_rateints.fits')
step = Spec2Pipeline()
step.save_bsub=True,
step.save_results=True
step.extract_1d.save_results = True
step.run(input_file)
outputs = [('jw00035001001_01101_00001_MIRIMAGE_calints.fits',
'jw00035001001_01101_00001_MIRIMAGE_calints_ref.fits',
['primary','sci','err','dq','relsens']),
('jw00035001001_01101_00001_MIRIMAGE_x1dints.fits',
'jw00035001001_01101_00001_MIRIMAGE_x1dints_ref.fits',
['primary', ('extract1d', 1), ('extract1d', 2), ('extract1d', 3), ('extract1d', 4)]
)
]
self.compare_outputs(outputs)
def test_nrs_msa_spec2b(self):
"""
Regression test of calwebb_spec2 pipeline performed on NIRSpec MSA data,
including barshadow correction.
"""
input = 'jw95065_nrs_msaspec_barshadow.fits'
input_file = self.get_data(self.test_dir, input)
self.get_data(self.test_dir, 'jwst_nirspec_shutters_barshadow.fits')
step = Spec2Pipeline()
step.output_file = 'jw95065_nrs_msaspec_barshadow_cal.fits'
step.save_bsub = False
step.save_results = True
step.resample_spec.save_results = True
step.extract_1d.save_results = True
step.run(input_file)
outputs = [('jw95065_nrs_msaspec_barshadow_cal.fits',
'jw95065_nrs_msaspec_barshadow_cal_ref.fits'),
('jw95065_nrs_msaspec_barshadow_s2d.fits',
'jw95065_nrs_msaspec_barshadow_s2d_ref.fits'),
('jw95065_nrs_msaspec_barshadow_x1d.fits',
'jw95065_nrs_msaspec_barshadow_x1d_ref.fits')]
self.compare_outputs(outputs)
def calibrate(self, configdir=None, outdir=None, **kwargs):
"""
Pipeline process the file
Parameters
----------
configdir: str
The directory containing the configuration files
outdir: str
The directory to put the calibrated files into
"""
# Get config directory
if configdir is None:
configdir = resource_filename('specialsoss', 'files')
# Get output directory
if outdir is None:
outdir = os.path.dirname(self.file)
# Get basename
basename = os.path.basename(self.file)
file = os.path.join(outdir, basename)
# Dict for new files
new_files = {}
if self.ext == 'uncal':
# Create Detector1Pipeline instance
cfg1_file = os.path.join(configdir, 'calwebb_tso1.cfg')
from jwst.pipeline import Detector1Pipeline
tso1 = Detector1Pipeline.call(self.file,
save_results=True,
config_file=cfg1_file,
output_dir=outdir)
# Calibrated files
new_files['ramp'] = os.path.join(
outdir, file.replace('_uncal.fits', '_ramp.fits'))
new_files['rate'] = os.path.join(
outdir, file.replace('_uncal.fits', '_rate.fits'))
new_files['rateints'] = os.path.join(
outdir, file.replace('_uncal.fits', '_rateints.fits'))
if self.ext in ['rate', 'rateints']:
# SPEC2 Pipeline
cfg2_file = os.path.join(configdir, 'calwebb_tso-spec2.cfg')
from jwst.pipeline import Spec2Pipeline
tso2 = Spec2Pipeline(save_results=True,
config_file=cfg2_file,
output_dir=outdir)
# Configure steps
tso2.cube_build.skip = True
tso2.extract_2d.skip = True
tso2.bkg_subtract.skip = True
tso2.msa_flagging.skip = True
tso2.barshadow.skip = True
tso2.extract_1d.save_results = True
# Run the pipeline
tso2.run(self.file)
# Calibrated files
new_files['calints'] = os.path.join(
outdir, file.replace('_rateints.fits', '_calints.fits'))
new_files['x1dints'] = os.path.join(
outdir, file.replace('_rateints.fits', '_x1dints.fits'))
else:
print("Not sure how to calibrate a '{}' file right now.".format(
self.ext))
return new_files