def test_open():
with stdatamodels.open():
pass
with stdatamodels.open((50, 50)):
pass
with pytest.warns(stdatamodels.util.NoTypeWarning):
with stdatamodels.open(FITS_FILE) as dm:
assert isinstance(dm, QuadModel)
def test_from_hdulist():
from astropy.io import fits
warnings.simplefilter("ignore")
with fits.open(FITS_FILE, memmap=False) as hdulist:
with stdatamodels.open(hdulist) as dm:
dm.data
assert not hdulist.fileinfo(0)['file'].closed
def test_open_fits():
"""Test opening a model from a FITS file"""
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "model_type not found")
fits_file = t_path('test.fits')
with stdatamodels.open(fits_file) as model:
assert isinstance(model, DataModel)
def test_open_asdf_s3(s3_root_dir):
"""Test opening a model from an ASDF file on S3"""
path = str(s3_root_dir.join("test.asdf"))
with DataModel() as dm:
dm.save(path)
with stdatamodels.open("s3://test-s3-data/test.asdf") as m:
assert isinstance(m, DataModel)
def test_open_from_pathlib():
"""Test opening a PurePath object"""
path = Path(t_path('test.fits'))
assert isinstance(path, PurePath)
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "model_type not found")
with stdatamodels.open(path) as model:
assert isinstance(model, DataModel)
def test_open_hdulist():
hdulist = fits.HDUList()
data = np.empty((50, 50), dtype=np.float32)
primary = fits.PrimaryHDU()
hdulist.append(primary)
science = fits.ImageHDU(data=data, name='SCI')
hdulist.append(science)
with stdatamodels.open(hdulist) as model:
assert type(model) == ImageModel
def test_open_association():
"""Test for opening an association"""
asn_file = t_path('association.json')
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "model_type not found")
with stdatamodels.open(asn_file) as c:
assert isinstance(c, ModelContainer)
for model in c:
assert model.meta.asn.table_name == "association.json"
assert model.meta.asn.pool_name == "pool"
def test_open_cube(tmpdir):
"""Open 3D data as CubeModel"""
path = str(tmpdir.join("ramp.fits"))
shape = (2, 3, 4)
with fits.HDUList(fits.PrimaryHDU()) as hdulist:
hdulist.append(fits.ImageHDU(data=np.zeros(shape), name="SCI", ver=1))
hdulist.writeto(path)
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "model_type not found")
with stdatamodels.open(path) as model:
assert isinstance(model, CubeModel)
def test_open_warning():
with warnings.catch_warnings(record=True) as warners:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
with stdatamodels.open(FITS_FILE) as model:
pass
class_name = model.__class__.__name__
j = None
for i, w in enumerate(warners):
if class_name in str(w.message):
j = i
assert j is not None
def test_open_asdf_readonly(tmpdir):
tmpfile = str(tmpdir.join('readonly.asdf'))
with DistortionModel() as model:
model.meta.telescope = 'JWST'
model.meta.instrument.name = 'NIRCAM'
model.meta.instrument.detector = 'NRCA4'
model.meta.instrument.channel = 'SHORT'
model.save(tmpfile)
os.chmod(tmpfile, 0o440)
assert os.access(tmpfile, os.W_OK) == False
with stdatamodels.open(tmpfile) as model:
assert model.meta.telescope == 'JWST'
def test_open_fits_readonly(tmpdir):
"""Test opening a FITS-format datamodel that is read-only on disk"""
tmpfile = str(tmpdir.join('readonly.fits'))
data = np.arange(100, dtype=np.float).reshape(10, 10)
with ImageModel(data=data) as model:
model.meta.telescope = 'JWST'
model.meta.instrument.name = 'NIRCAM'
model.meta.instrument.detector = 'NRCA4'
model.meta.instrument.channel = 'SHORT'
model.save(tmpfile)
os.chmod(tmpfile, 0o440)
assert os.access(tmpfile, os.W_OK) == False
with stdatamodels.open(tmpfile) as model:
assert model.meta.telescope == 'JWST'
def test_open_reffiles(tmpdir, model_class, shape):
"""Try opening files with a REFTYPE keyword and different data/dq shapes"""
path = str(tmpdir.join("reffile.fits"))
with fits.HDUList(fits.PrimaryHDU()) as hdulist:
hdulist["PRIMARY"].header.append(("REFTYPE", "foo"))
if shape is not None:
hdulist.append(
fits.ImageHDU(data=np.zeros(shape), name="SCI", ver=1))
hdulist.append(
fits.ImageHDU(data=np.zeros(shape, dtype=np.uint),
name="DQ",
ver=1))
hdulist.writeto(path)
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "model_type not found")
with stdatamodels.open(path) as model:
assert isinstance(model, model_class)
def test_open_illegal():
with pytest.raises(ValueError):
init = 5
stdatamodels.open(init)
def test_open_image():
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "model_type not found")
image_name = t_path('jwst_image.fits')
with stdatamodels.open(image_name) as model:
assert type(model) == ImageModel
def test_open_shape():
init = (200, 200)
with stdatamodels.open(init) as model:
assert type(model) == ImageModel
def test_container_open_asn_with_sourcecat():
path = t_path("association_w_cat.json")
with stdatamodels.open(path, asn_exptypes="science") as c:
for model in c:
assert model.meta.asn.table_name == "association_w_cat.json"
def test_init_with_array():
array = np.empty((50, 50))
with stdatamodels.open(array) as dm:
assert dm.data.shape == (50, 50)
assert isinstance(dm, ImageModel)
