def test_slit_projection_on_detector():
step = assign_wcs_step.AssignWcsStep()
hdul = create_nirspec_fs_file(grating="G395M",
filter="OPAQUE",
lamp="ARGON")
hdul[0].header['DETECTOR'] = 'NRS2'
im = datamodels.ImageModel(hdul)
refs = {}
for reftype in step.reference_file_types:
refs[reftype] = step.get_reference_file(im, reftype)
open_slits = nirspec.get_open_slits(im, refs)
assert len(open_slits) == 1
assert open_slits[0].name == "S200B1"
hdul[0].header['DETECTOR'] = 'NRS1'
im = datamodels.ImageModel(hdul)
open_slits = nirspec.get_open_slits(im, refs)
assert len(open_slits) == 4
names = [s.name for s in open_slits]
assert "S200A1" in names
assert "S200A2" in names
assert "S400A1" in names
assert "S1600A1" in names
def test_open_slits():
""" Test that get_open_slits works with MSA data.
Issue #2321
"""
image = create_nirspec_mos_file()
model = datamodels.ImageModel(image)
msaconfl = get_file_path('msa_configuration.fits')
model.meta.instrument.msa_metadata_file = msaconfl
model.meta.instrument.msa_metadata_id = 12
slits = nirspec.get_open_slits(model)
assert len(slits) == 1
def test_nirspec_mos_wcs(rtdata):
"""Test NIRSpec MOS wcs"""
input_file = 'msa_patt_num.fits'
# Get MSA meta file
rtdata.get_data('nirspec/mos/V9621500100101_short_msa.fits')
rtdata.get_data(f"nirspec/mos/{input_file}")
AssignWcsStep.call(input_file, save_results=True, suffix='assign_wcs')
output = input_file.replace('.fits', '_assign_wcs.fits')
rtdata.output = output
rtdata.get_truth(f"truth/test_nirspec_wcs/{output}")
with datamodels.open(rtdata.output) as im, datamodels.open(
rtdata.truth) as im_truth:
names = [slit.name for slit in nirspec.get_open_slits(im)]
for name in names:
wcs = nirspec.nrs_wcs_set_input(im, name)
wcs_truth = nirspec.nrs_wcs_set_input(im_truth, name)
assert_wcs_grid_allclose(wcs, wcs_truth)
def extract2d(input_model, which_subarray=None):
exp_type = input_model.meta.exposure.type.upper()
log.info('EXP_TYPE is {0}'.format(exp_type))
if exp_type in ['NRS_FIXEDSLIT', 'NRS_MSASPEC']:
if which_subarray is None:
open_slits = nirspec.get_open_slits(input_model)
else:
open_slits = [nirspec.slit_name2id[which_subarray]]
else:
# Set the step status to COMPLETE
output_model.meta.cal_step.extract_2d = 'SKIPPED'
return input_model
log.info('open slits {0}'.format(open_slits))
output_model = models.MultiSlitModel()
output_model.update(input_model)
_, wrange = nirspec.spectral_order_wrange_from_model(input_model)
if exp_type == 'NRS_FIXEDSLIT':
slit_names = [nirspec.slit_id2name[tuple(slit)] for slit in open_slits]
else:
slit_names = [str(slit) for slit in open_slits]
for slit, slit_name in zip(open_slits, slit_names):
slit_wcs = nirspec.nrs_wcs_set_input(input_model.meta.wcs, slit[0],
slit[1], wrange)
if (input_model.meta.subarray.ystart is not None):
xlo, xhi, ylo, yhi = _adjust_subarray(input_model, slit_wcs)
else:
log.info('Subarray ystart metadata value not found')
xlo, xhi = slit_wcs.domain[0]['lower'], slit_wcs.domain[0]['upper']
ylo, yhi = slit_wcs.domain[1]['lower'], slit_wcs.domain[1]['upper']
log.info('Name of subarray extracted: %s', slit_name)
log.info('Subarray x-extents are: %s %s', xlo, xhi)
log.info('Subarray y-extents are: %s %s', ylo, yhi)
ext_data = input_model.data[ylo:yhi + 1, xlo:xhi + 1].copy()
ext_err = input_model.err[ylo:yhi + 1, xlo:xhi + 1].copy()
ext_dq = input_model.dq[ylo:yhi + 1, xlo:xhi + 1].copy()
new_model = models.ImageModel(data=ext_data, err=ext_err, dq=ext_dq)
shape = ext_data.shape
domain = [{
'lower': -0.5,
'upper': shape[1] + 0.5,
'includes_lower': True,
'includes_upper': False
}, {
'lower': -0.5,
'upper': shape[0] + 0.5,
'includes_lower': True,
'includes_upper': False
}]
slit_wcs.domain = domain
new_model.meta.wcs = slit_wcs
output_model.slits.append(new_model)
# set x/ystart values relative to full detector space, so need
# to account for x/ystart values of input if it's a subarray
nslit = len(output_model.slits) - 1
output_model.slits[nslit].name = slit_name
output_model.slits[
nslit].xstart = input_model.meta.subarray.xstart + xlo
output_model.slits[nslit].xsize = xhi - xlo + 1
output_model.slits[
nslit].ystart = input_model.meta.subarray.ystart + ylo
output_model.slits[nslit].ysize = yhi - ylo + 1
del input_model
#del output_model.meta.wcs
# Set the step status to COMPLETE
output_model.meta.cal_step.extract_2d = 'COMPLETE'
return output_model