def make_container():
"""Create the container to test"""
size = 5
cube = CubeModel((size, size, size))
cube.meta.target.proposer_name = 'JWST regression test'
container = cube.to_container()
return cube, container
def test_miri_slitless_wcs(_bigdata):
"""
Regression test of creating a WCS object and doing pixel to sky transformation.
"""
suffix = 'assignwcsstep'
output_file_base, output_file = add_suffix('miri_slitless_wcs_output.fits',
suffix)
try:
os.remove(output_file)
except:
pass
input_file = os.path.join(
_bigdata, 'miri', 'test_wcs', 'slitless',
'jw80600012001_02101_00003_mirimage_rateints.fits')
ref_file = os.path.join(
_bigdata, 'miri', 'test_wcs', 'slitless',
'jw80600012001_02101_00003_mirimage_assign_wcs.fits')
AssignWcsStep.call(input_file, output_file=output_file_base, suffix=suffix)
im = CubeModel(output_file)
imref = CubeModel(ref_file)
x, y = np.mgrid[:1031, :1024]
ra, dec, lam = im.meta.wcs(x, y)
raref, decref, lamref = imref.meta.wcs(x, y)
utils.assert_allclose(ra, raref)
utils.assert_allclose(dec, decref)
utils.assert_allclose(lam, lamref)
def miri_mrs_short_tso():
"""Set up MIRI MRS SHORT TSO data"""
image = CubeModel((5, 1024, 1032))
image.data = np.random.random((5, 1024, 1032))
image.meta.instrument.name = 'MIRI'
image.meta.instrument.detector = 'MIRIFUSHORT'
image.meta.exposure.type = 'MIR_MRS'
image.meta.instrument.channel = '12'
image.meta.instrument.band = 'SHORT'
image.meta.filename = 'test_miri_short_tso.fits'
image.meta.observation.date = '2019-01-01'
image.meta.observation.time = '10:10:10'
return image
def create_model_3d():
im = CubeModel()
im.meta.wcsinfo.crpix1 = 2.5
im.meta.wcsinfo.crpix2 = 3
im.meta.wcsinfo.crval1 = 5.6
im.meta.wcsinfo.crval2 = -72.3
im.meta.wcsinfo.wcsaxes = 2
im.meta.wcsinfo.cunit1 = 'deg'
im.meta.wcsinfo.cunit2 = 'deg'
im.meta.wcsinfo.ctype1 = 'RA---TAN'
im.meta.wcsinfo.ctype2 = 'DEC--TAN'
im.meta.wcsinfo.pc1_1 = 1.
im.meta.wcsinfo.pc1_2 = 0
im.meta.wcsinfo.pc2_1 = 0.
im.meta.wcsinfo.pc2_2 = 1.
im.meta.wcsinfo.crpix3 = 1
im.meta.wcsinfo.crval3 = 100
im.meta.wcsinfo.wcsaxes = 3
im.meta.wcsinfo.cunit3 = 'um'
im.meta.wcsinfo.ctype3 = 'WAVE'
im.meta.wcsinfo.pc3_1 = 0.
im.meta.wcsinfo.pc3_2 = 0
im.meta.wcsinfo.pc3_3 = 1
im.meta.wcsinfo.pc1_3 = 0
im.meta.wcsinfo.pc2_3 = 0.
return im
def create_tso_wcsimage(filtername="F277W", subarray=False):
"""Help create tsgrism GWCS object."""
if subarray:
subarray = "SUBGRISM256"
else:
subarray = "FULL"
hdul = create_hdul(exptype='NRC_TSGRISM',
pupil='GRISMR',
filtername=filtername,
detector='NRCALONG',
subarray=subarray,
wcskeys=wcs_tso_kw)
hdul['sci'].header['SUBSIZE1'] = NIRCAM_TSO_WIDTH
if subarray:
hdul['sci'].header['SUBSIZE2'] = 256
subsize = 256
else:
hdul['sci'].header['SUBSIZE2'] = 2048
subsize = 2048
hdul['sci'].data = np.ones((2, subsize, NIRCAM_TSO_WIDTH))
im = CubeModel(hdul)
im.meta.wcsinfo.siaf_xref_sci = 887.0
im.meta.wcsinfo.siaf_yref_sci = 35.0
aswcs = AssignWcsStep()
return aswcs.process(im)
def create_tso_wcs(filtername=tsgrism_filters[0], subarray="SUBGRISM256"):
"""Help create tsgrism GWCS object."""
hdul = create_hdul(exptype='NRC_TSGRISM', pupil='GRISMR',
filtername=filtername, detector='NRCALONG',
subarray=subarray, wcskeys=wcs_tso_kw)
im = CubeModel(hdul)
ref = get_reference_files(im)
pipeline = nircam.create_pipeline(im, ref)
wcsobj = wcs.WCS(pipeline)
return wcsobj
def test_miri_slitless_wcs(self):
"""
Regression test of creating a WCS object and doing pixel to sky transformation.
"""
input_file = self.get_data(self.test_dir,
"jw80600012001_02101_00003_mirimage_rateints.fits")
ref_file = self.get_data(*self.ref_loc,
"jw80600012001_02101_00003_mirimage_assign_wcs.fits")
result = AssignWcsStep.call(input_file)
output_file = result.meta.filename
result.save(output_file)
result.close()
im = CubeModel(output_file)
imref = CubeModel(ref_file)
x, y = np.mgrid[:1031, :1024]
ra, dec, lam = im.meta.wcs(x, y)
raref, decref, lamref = imref.meta.wcs(x, y)
utils.assert_allclose(ra, raref)
utils.assert_allclose(dec, decref)
utils.assert_allclose(lam, lamref)
def _dm(nints, ysize, xsize):
# create the data arrays
csize = (nints, ysize, xsize)
data = np.random.randint(low=1, high=50, size=csize)
err = np.random.randint(low=0.1, high=5.0, size=csize)
var_p = err * err
var_r = np.ones(csize) * 12
# create a JWST datamodel
dm = CubeModel(data=data, err=err, var_poisson=var_p, var_rnoise=var_r)
dm.meta.instrument.name = 'NIRSPEC'
dm.meta.date = '2018-01-01'
dm.meta.instrument.detector = 'NRS1'
dm.meta.observation.date = '2018-01-01'
dm.meta.exposure.gain_factor = 2
return dm
def _add_missing_key(missing_key=None):
tso_kw = wcs_tso_kw.copy()
if missing_key is not None:
tso_kw[missing_key] = None
hdu = create_hdul(
exptype='NRC_TSGRISM',
pupil='GRISMR',
filtername=request.param,
detector='NRCALONG',
subarray='SUBGRISM256',
wcskeys=tso_kw,
channel='LONG',
module='A',
)
image_model = CubeModel(hdu)
return image_model, get_reference_files(image_model)
def test_miri_slitless_wcs(self):
"""
Regression test of creating a WCS object and doing pixel to sky transformation.
"""
input_file = self.get_data(self.test_dir,
"jw80600012001_02101_00003_mirimage_rateints.fits")
result = AssignWcsStep.call(input_file, save_results=True)
cwd = os.path.abspath('.')
os.makedirs('truth', exist_ok=True)
os.chdir('truth')
truth_file = self.get_data(*self.ref_loc,
"jw80600012001_02101_00003_mirimage_assignwcsstep.fits")
os.chdir(cwd)
truth = CubeModel(truth_file)
x, y = grid_from_bounding_box(result.meta.wcs.bounding_box)
ra, dec, lam = result.meta.wcs(x, y)
raref, decref, lamref = truth.meta.wcs(x, y)
assert_allclose(ra, raref)
assert_allclose(dec, decref)
assert_allclose(lam, lamref)
