def test_wcs_keyword_removal_for_wcs_test_files():
"""
Test, for the WCS test files, that keyword removall works as
expected. Those cover a much broader range of WCS types than
test_wcs_keywords_removed_from_header
"""
from astropy.nddata.ccddata import _generate_wcs_and_update_header
from astropy.nddata.ccddata import _KEEP_THESE_KEYWORDS_IN_HEADER
keepers = set(_KEEP_THESE_KEYWORDS_IN_HEADER)
wcs_headers = get_pkg_data_filenames('../../wcs/tests/data',
pattern='*.hdr')
for hdr in wcs_headers:
# Skip the files that are expected to be bad...
if 'invalid' in hdr or 'nonstandard' in hdr or 'segfault' in hdr:
continue
header_string = get_pkg_data_contents(hdr)
wcs = WCS(header_string)
header = wcs.to_header(relax=True)
new_header, new_wcs = _generate_wcs_and_update_header(header)
# Make sure all of the WCS-related keywords have been removed.
assert not (set(new_header) &
set(new_wcs.to_header(relax=True)) -
keepers)
# Check that the new wcs is the same as the old.
new_wcs_header = new_wcs.to_header(relax=True)
for k, v in new_wcs_header.items():
if isinstance(v, str):
assert header[k] == v
else:
np.testing.assert_almost_equal(header[k], v)
def test_wcs_keyword_removal_for_wcs_test_files():
"""
Test, for the WCS test files, that keyword removall works as
expected. Those cover a much broader range of WCS types than
test_wcs_keywords_removed_from_header
"""
from astropy.nddata.ccddata import _generate_wcs_and_update_header
from astropy.nddata.ccddata import _KEEP_THESE_KEYWORDS_IN_HEADER
keepers = set(_KEEP_THESE_KEYWORDS_IN_HEADER)
wcs_headers = get_pkg_data_filenames('../../wcs/tests/data',
pattern='*.hdr')
for hdr in wcs_headers:
# Skip the files that are expected to be bad...
if 'invalid' in hdr or 'nonstandard' in hdr or 'segfault' in hdr:
continue
header_string = get_pkg_data_contents(hdr)
wcs = WCS(header_string)
header = wcs.to_header(relax=True)
new_header, new_wcs = _generate_wcs_and_update_header(header)
# Make sure all of the WCS-related keywords have been removed.
assert not (set(new_header)
& set(new_wcs.to_header(relax=True)) - keepers)
# Check that the new wcs is the same as the old.
new_wcs_header = new_wcs.to_header(relax=True)
for k, v in new_wcs_header.items():
if isinstance(v, str):
assert header[k] == v
else:
np.testing.assert_almost_equal(header[k], v)
def test_solve_astrometry_hdu(tmpdir):
data, index = get_image_index()
hdu = fits.open(data)[0]
header, wcs = _generate_wcs_and_update_header(hdu.header)
hdu.header = header
nwcs = solve_astrometry_hdu(hdu, return_wcs=True)
assert_true(isinstance(nwcs, WCS))
assert_equal(nwcs.naxis, 2)
compare_wcs(wcs, nwcs)
def test_wcs_keyword_removal_for_wcs_test_files():
"""
Test, for the WCS test files, that keyword removal works as
expected. Those cover a much broader range of WCS types than
test_wcs_keywords_removed_from_header.
Includes regression test for #8597
"""
from astropy.nddata.ccddata import _generate_wcs_and_update_header
from astropy.nddata.ccddata import (_KEEP_THESE_KEYWORDS_IN_HEADER,
_CDs, _PCs)
keepers = set(_KEEP_THESE_KEYWORDS_IN_HEADER)
wcs_headers = get_pkg_data_filenames('../../wcs/tests/data',
pattern='*.hdr')
for hdr in wcs_headers:
# Skip the files that are expected to be bad...
if ('invalid' in hdr or 'nonstandard' in hdr or 'segfault' in hdr or
'chandra-pixlist-wcs' in hdr):
continue
header_string = get_pkg_data_contents(hdr)
header = fits.Header.fromstring(header_string)
wcs = WCS(header_string)
header_from_wcs = wcs.to_header(relax=True)
new_header, new_wcs = _generate_wcs_and_update_header(header)
new_wcs_header = new_wcs.to_header(relax=True)
# Make sure all of the WCS-related keywords generated by astropy
# have been removed.
assert not (set(new_header) &
set(new_wcs_header) -
keepers)
# Check that new_header contains no remaining WCS information.
# Specifically, check that
# 1. The combination of new_header and new_wcs does not contain
# both PCi_j and CDi_j keywords. See #8597.
# Check for 1
final_header = new_header + new_wcs_header
final_header_set = set(final_header)
if _PCs & final_header_set:
assert not (_CDs & final_header_set)
elif _CDs & final_header_set:
assert not (_PCs & final_header_set)
# Check that the new wcs is the same as the old.
for k, v in new_wcs_header.items():
if isinstance(v, str):
assert header_from_wcs[k] == v
else:
np.testing.assert_almost_equal(header_from_wcs[k], v)
def test_wcs_keyword_removal_for_wcs_test_files():
"""
Test, for the WCS test files, that keyword removal works as
expected. Those cover a much broader range of WCS types than
test_wcs_keywords_removed_from_header.
Includes regression test for #8597
"""
from astropy.nddata.ccddata import _generate_wcs_and_update_header
from astropy.nddata.ccddata import (_KEEP_THESE_KEYWORDS_IN_HEADER,
_CDs, _PCs)
keepers = set(_KEEP_THESE_KEYWORDS_IN_HEADER)
wcs_headers = get_pkg_data_filenames('../../wcs/tests/data',
pattern='*.hdr')
for hdr in wcs_headers:
# Skip the files that are expected to be bad...
if 'invalid' in hdr or 'nonstandard' in hdr or 'segfault' in hdr:
continue
header_string = get_pkg_data_contents(hdr)
header = fits.Header.fromstring(header_string)
wcs = WCS(header_string)
header_from_wcs = wcs.to_header(relax=True)
new_header, new_wcs = _generate_wcs_and_update_header(header)
new_wcs_header = new_wcs.to_header(relax=True)
# Make sure all of the WCS-related keywords generated by astropy
# have been removed.
assert not (set(new_header) &
set(new_wcs_header) -
keepers)
# Check that new_header contains no remaining WCS information.
# Specifically, check that
# 1. The combination of new_header and new_wcs does not contain
# both PCi_j and CDi_j keywords. See #8597.
# Check for 1
final_header = new_header + new_wcs_header
final_header_set = set(final_header)
if _PCs & final_header_set:
assert not (_CDs & final_header_set)
elif _CDs & final_header_set:
assert not (_PCs & final_header_set)
# Check that the new wcs is the same as the old.
for k, v in new_wcs_header.items():
if isinstance(v, str):
assert header_from_wcs[k] == v
else:
np.testing.assert_almost_equal(header_from_wcs[k], v)
def test_solve_astrometry_image(tmpdir):
data, index = get_image_index()
hdu = fits.open(data)[0]
header, wcs = _generate_wcs_and_update_header(hdu.header)
hdu.header = header
name = tmpdir.join('testimage.fits').strpath
hdu.writeto(name)
nwcs = solve_astrometry_image(name, return_wcs=True)
assert_is_instance(nwcs, WCS)
assert_equal(nwcs.naxis, 2)
compare_wcs(wcs, nwcs)
def test_fit_wcs(tmpdir):
data, index = get_image_index()
hdu = fits.open(data)[0]
imw, imh = hdu.data.shape
header, wcs = _generate_wcs_and_update_header(hdu.header)
hdu.header = header
sources = starfind(hdu.data, 10, np.median(hdu.data), np.std(hdu.data), 4)
sources['ra'], sources['dec'] = wcs.all_pix2world(sources['x'],
sources['y'], 1)
nwcs = fit_wcs(sources['x'], sources['y'], sources['ra'], sources['dec'],
imw, imh)
assert_is_instance(nwcs, WCS)
assert_equal(nwcs.naxis, 2)
compare_wcs(wcs, nwcs)
def test_solve_astrometry_xyl(tmpdir):
data, index = get_image_index()
hdu = fits.open(data)[0]
header, wcs = _generate_wcs_and_update_header(hdu.header)
hdu.header = header
sources = starfind(hdu.data, 10, np.median(hdu.data), np.std(hdu.data), 4)
phot = aperture_photometry(hdu.data, sources['x'], sources['y'])
imw, imh = hdu.data.shape
nwcs = solve_astrometry_xy(phot['x'],
phot['y'],
phot['flux'],
header,
imw,
imh,
return_wcs=True)
assert_is_instance(nwcs, WCS)
assert_equal(nwcs.naxis, 2)
compare_wcs(wcs, nwcs)
def loader_generator(actually_load_data):
# Ideally we would just return a shape instead of an empty data array in
# the case where actually_load_data is false, but we can't use
# `ccdproc.trim_image()` without having a CCDData in hand, so to get the
# right shape we're going to need to create a full CCDData anyway.
for fits_path in glob(join(dirname, '*.fits')):
# `astropy.nddata.ccddata.fits_ccddata_reader` only opens FITS from
# filenames, not from an open HDUList, which means that creating
# multiple CCDDatas from the same FITS file rapidly becomes
# inefficient. So, we emulate its logic.
with fits.open(fits_path) as hdu_list:
for idx, hdu in enumerate(hdu_list):
if idx == 0:
header0 = hdu.header
else:
hdr = hdu.header
hdr.extend(header0, unique=True)
# This ccddata function often generates annoying warnings
with warnings.catch_warnings():
warnings.simplefilter('ignore')
hdr, wcs = ccddata._generate_wcs_and_update_header(
hdr)
# Note: we skip all the unit-handling logic here since the LSST
# sim data I'm using don't have anything useful.
if actually_load_data:
data = hdu.data
else:
data = np.empty(hdu.shape, dtype=np.void)
ccd = ccddata.CCDData(data,
meta=hdr,
unit=unit,
wcs=wcs)
ccd = ccdproc.trim_image(
ccd, fits_section=ccd.header['DATASEC'])
yield (f'{fits_path}:{idx}', ccd)
