def test_miri_ifu_wcs(_bigdata):
"""
Regression test of creating a WCS object and doing pixel to sky transformation.
"""
try:
os.remove("miri_ifu_wcs_output.fits")
except:
pass
input_file = os.path.join(
_bigdata, 'miri', 'test_wcs', 'ifu',
'jw00024001001_01101_00001_MIRIFUSHORT_uncal_MiriSloperPipeline.fits')
ref_file = os.path.join(
_bigdata, 'miri', 'test_wcs', 'ifu',
'jw00024001001_01101_00001_MIRIFUSHORT_assign_wcs.fits')
AssignWcsStep.call(input_file, output_file='miri_ifu_wcs', suffix='output')
im = ImageModel('miri_ifu_wcs_output.fits')
imref = ImageModel(ref_file)
# Get the region file
region = RegionsModel(crds_client.get_reference_file(im, 'regions'))
# inputs
shape = region.regions.shape
y, x = np.mgrid[:shape[0], :shape[1]]
# Get indices where pixels == 0. These should be NaNs in the output.
ind_zeros = region.regions == 0
ra, dec, lam = im.meta.wcs(x, y)
raref, decref, lamref = imref.meta.wcs(x, y)
utils.assert_allclose(ra, raref, equal_nan=True)
utils.assert_allclose(dec, decref, equal_nan=True)
utils.assert_allclose(lam, lamref, equal_nan=True)
# Test that we got NaNs at ind_zero
assert (np.isnan(ra).nonzero()[0] == ind_zeros.nonzero()[0]).all()
assert (np.isnan(ra).nonzero()[1] == ind_zeros.nonzero()[1]).all()
# Test the inverse transform
x1, y1 = im.meta.wcs.backward_transform(ra, dec, lam)
assert (np.isnan(x1).nonzero()[0] == ind_zeros.nonzero()[0]).all()
assert (np.isnan(x1).nonzero()[1] == ind_zeros.nonzero()[1]).all()
# Also run a smoke test with values outside the region.
dec[100][200] = -80
ra[100][200] = 7
lam[100][200] = 15
x2, y2 = im.meta.wcs.backward_transform(ra, dec, lam)
assert np.isnan(x2[100][200])
assert np.isnan(x2[100][200])
def test_miri_ifu_wcs(self):
"""
Regression test of creating a WCS object and doing pixel to sky transformation.
"""
input_file = self.get_data(
self.test_dir,
'jw00024001001_01101_00001_MIRIFUSHORT_uncal_MiriSloperPipeline.fits'
)
result = AssignWcsStep.call(input_file, save_results=True)
# Get the region file
region = RegionsModel(crds_client.get_reference_file(
result, 'regions'))
# Choose the same plane as in the miri.py file (hardcoded for now).
regions = region.regions[7, :, :]
# inputs
x, y = grid_from_bounding_box(result.meta.wcs.bounding_box)
# Get indices where pixels == 0. These should be NaNs in the output.
ind_zeros = regions == 0
cwd = os.path.abspath('.')
os.makedirs('truth', exist_ok=True)
os.chdir('truth')
truth_file = self.get_data(
*self.ref_loc,
'jw00024001001_01101_00001_MIRIFUSHORT_assign_wcs.fits')
os.chdir(cwd)
truth = ImageModel(truth_file)
ra, dec, lam = result.meta.wcs(x, y)
raref, decref, lamref = truth.meta.wcs(x, y)
assert_allclose(ra, raref, equal_nan=True)
assert_allclose(dec, decref, equal_nan=True)
assert_allclose(lam, lamref, equal_nan=True)
# Test that we got NaNs at ind_zero
assert (np.isnan(ra).nonzero()[0] == ind_zeros.nonzero()[0]).all()
assert (np.isnan(ra).nonzero()[1] == ind_zeros.nonzero()[1]).all()
# Test the inverse transform
x1, y1 = result.meta.wcs.backward_transform(ra, dec, lam)
assert (np.isnan(x1).nonzero()[0] == ind_zeros.nonzero()[0]).all()
assert (np.isnan(x1).nonzero()[1] == ind_zeros.nonzero()[1]).all()
# Also run a smoke test with values outside the region.
dec[100][200] = -80
ra[100][200] = 7
lam[100][200] = 15
x2, y2 = result.meta.wcs.backward_transform(ra, dec, lam)
assert np.isnan(x2[100][200])
assert np.isnan(x2[100][200])