def match_to_gaia(imcat, refcat, product, output, searchrad=5.0):
"""Create a catalog with sources matched to GAIA sources
Parameters
----------
imcat : str or obj
Filename or astropy.Table of source catalog written out as ECSV file
refcat : str
Filename of GAIA catalog files written out as ECSV file
product : str
Filename of drizzled product used to derive the source catalog
output : str
Rootname for matched catalog file to be written as an ECSV file
"""
if isinstance(imcat, str):
imtab = Table.read(imcat, format='ascii.ecsv')
imtab.rename_column('X-Center', 'x')
imtab.rename_column('Y-Center', 'y')
else:
imtab = imcat
if 'X-Center' in imtab.colnames:
imtab.rename_column('X-Center', 'x')
imtab.rename_column('Y-Center', 'y')
reftab = Table.read(refcat, format='ascii.ecsv')
# define WCS for matching
tpwcs = tweakwcs.FITSWCS(HSTWCS(product, ext=1))
# define matching parameters
tpmatch = tweakwcs.TPMatch(searchrad=searchrad)
# perform match
ref_indx, im_indx = tpmatch(reftab, imtab, tpwcs)
print('Found {} matches'.format(len(ref_indx)))
# Obtain tangent plane positions for both image sources and reference sources
im_x, im_y = tpwcs.det_to_tanp(imtab['x'][im_indx], imtab['y'][im_indx])
ref_x, ref_y = tpwcs.world_to_tanp(reftab['RA'][ref_indx], reftab['DEC'][ref_indx])
if 'RA' not in imtab.colnames:
im_ra, im_dec = tpwcs.det_to_world(imtab['x'][im_indx], imtab['y'][im_indx])
else:
im_ra = imtab['RA'][im_indx]
im_dec = imtab['DEC'][im_indx]
# Compile match table
match_tab = Table(data=[im_x, im_y, im_ra, im_dec,
ref_x, ref_y,
reftab['RA'][ref_indx], reftab['DEC'][ref_indx]],
names=['img_x','img_y', 'img_RA', 'img_DEC',
'ref_x', 'ref_y', 'ref_RA', 'ref_DEC'])
if not output.endswith('.ecsv'):
output = '{}.ecsv'.format(output)
match_tab.write(output, format='ascii.ecsv')
def test_generate_catalog(self,input_filenames, truth_file):
""" Verify whether sources from astrometric catalogs can be extracted from images.
Success Criteria
-----------------
* Initially, source catalog matches >80% of 'truth' catalog sources
"""
self.input_loc = 'catalog_tests'
self.curdir = os.getcwd()
truth_path = [self.input_repo, self.tree, self.input_loc, *self.ref_loc]
if not isinstance(input_filenames, list):
input_filenames = [input_filenames]
try:
# Make local copies of input files
local_files = []
for infile in input_filenames:
downloaded_files = self.get_input_file(infile, docopy=True)
local_files.extend(downloaded_files)
test_image = local_files[0]
print("Testing with {}".format(test_image))
imghdu = fits.open(test_image)
instrume = imghdu[0].header['instrume'].lower()
detector = imghdu[0].header['detector'].lower()
instr_pars = detector_specific_params[instrume][detector]
reference_wcs = amutils.build_reference_wcs(local_files)
imcat = amutils.generate_sky_catalog(imghdu, reference_wcs, **instr_pars)
imcat.rename_column('xcentroid', 'x')
imcat.rename_column('ycentroid', 'y')
# create FITS WCS corrector object
wcs_corrector = tweakwcs.FITSWCS(reference_wcs)
# get reference catalog as 'truth' files
reference_catalog = get_bigdata(*truth_path, truth_file, docopy=True)
if os.path.basename(reference_catalog).endswith('ecsv'):
tab_format = 'ascii.ecsv'
else:
tab_format = 'ascii.fast_commented_header'
reference_table = Table.read(reference_catalog, format=tab_format)
num_expected = len(reference_table)
# Perform matching
match = tweakwcs.TPMatch(searchrad=200, separation=0.1, tolerance=5, use2dhist=True)
ridx, iidx = match(reference_table, imcat, wcs_corrector)
nmatches = len(ridx)
except Exception:
exc_type, exc_value, exc_tb = sys.exc_info()
traceback.print_exception(exc_type, exc_value, exc_tb, file=sys.stdout)
sys.exit()
assert (nmatches > 0.8*num_expected)
def test_multichip_fitswcs_alignment():
h1 = fits.Header.fromfile(get_pkg_data_filename('data/wfc3_uvis1.hdr'))
w1 = wcs.WCS(h1)
imcat1 = tweakwcs.FITSWCS(w1)
imcat1.meta['catalog'] = table.Table.read(
get_pkg_data_filename('data/wfc3_uvis1.cat'),
format='ascii.csv',
delimiter=' ',
names=['x', 'y'])
imcat1.meta['group_id'] = 1
imcat1.meta['name'] = 'ext1'
h2 = fits.Header.fromfile(get_pkg_data_filename('data/wfc3_uvis2.hdr'))
w2 = wcs.WCS(h2)
imcat2 = tweakwcs.FITSWCS(w2)
imcat2.meta['catalog'] = table.Table.read(
get_pkg_data_filename('data/wfc3_uvis2.cat'),
format='ascii.csv',
delimiter=' ',
names=['x', 'y'])
imcat2.meta['group_id'] = 1
imcat2.meta['name'] = 'ext4'
refcat = table.Table.read(get_pkg_data_filename('data/ref.cat'),
format='ascii.csv',
delimiter=' ',
names=['RA', 'DEC'])
tweakwcs.align_wcs([imcat1, imcat2],
refcat,
match=_match,
nclip=None,
sigma=3,
fitgeom='general')
fi1 = imcat1.meta['fit_info']
fi2 = imcat2.meta['fit_info']
w1 = imcat1.wcs
w2 = imcat2.wcs
assert np.allclose(w1.wcs.crval, (83.206917667519, -67.73275818507248),
rtol=0)
assert np.allclose(
w1.wcs.cd,
np.array([[3.93222694902149e-06, -1.0106698270131359e-05],
[-1.0377001075437075e-05, -4.577945148472431e-06]]),
atol=0.0,
rtol=1e-8)
assert np.allclose(w2.wcs.crval, (83.15167050722597, -67.74220306069903),
rtol=0)
assert np.allclose(
w2.wcs.cd,
np.array([[3.834449806681195e-06, -9.996495217498745e-06],
[-1.0348147451241423e-05, -4.503496019301529e-06]]),
atol=0.0,
rtol=1e-8)
assert np.allclose(fi1['<scale>'], 1.0025, rtol=0, atol=2e-8)
assert np.allclose(fi2['<scale>'], 1.0025, rtol=0, atol=2e-8)
assert fi1['rmse'] < 5e-5
assert fi2['rmse'] < 5e-5
cat1 = imcat1.meta['catalog']
ra1, dec1 = w1.all_pix2world(cat1['x'], cat1['y'], 0)
cat2 = imcat2.meta['catalog']
ra2, dec2 = w2.all_pix2world(cat2['x'], cat2['y'], 0)
ra = np.concatenate([ra1, ra2])
dec = np.concatenate([dec1, dec2])
rmse_ra = np.sqrt(np.mean((ra - refcat['RA'])**2))
rmse_dec = np.sqrt(np.mean((dec - refcat['DEC'])**2))
assert rmse_ra < 1e-9
assert rmse_dec < 1e-9
def test_different_ref_tpwcs_fitswcs_alignment(wcsno, refscale, dra, ddec):
# This test was designed to check that the results of alignment,
# in particular and most importantly, the sky positions of sources in
# aligned images do not depend on the tangent reference plane used
# for alignment. [#125]
h1 = fits.Header.fromfile(get_pkg_data_filename('data/wfc3_uvis1.hdr'))
w1 = wcs.WCS(h1)
imcat1 = tweakwcs.FITSWCS(w1)
imcat1.meta['catalog'] = table.Table.read(
get_pkg_data_filename('data/wfc3_uvis1.cat'),
format='ascii.csv',
delimiter=' ',
names=['x', 'y'])
imcat1.meta['group_id'] = 1
imcat1.meta['name'] = 'ext1'
h2 = fits.Header.fromfile(get_pkg_data_filename('data/wfc3_uvis2.hdr'))
w2 = wcs.WCS(h2)
imcat2 = tweakwcs.FITSWCS(w2)
imcat2.meta['catalog'] = table.Table.read(
get_pkg_data_filename('data/wfc3_uvis2.cat'),
format='ascii.csv',
delimiter=' ',
names=['x', 'y'])
imcat2.meta['group_id'] = 1
imcat2.meta['name'] = 'ext4'
refcat = table.Table.read(get_pkg_data_filename('data/ref.cat'),
format='ascii.csv',
delimiter=' ',
names=['RA', 'DEC'])
refwcses = [wcs.WCS(h1), wcs.WCS(h2)]
refwcs = refwcses[wcsno]
# change pointing of the reference WCS (alignment tangent plane):
refwcs.wcs.crval = refwcses[1 - wcsno].wcs.crval + np.asarray([dra, ddec])
rotm = tweakwcs.linearfit.build_fit_matrix(*refscale)
refwcs.wcs.cd = np.dot(refwcs.wcs.cd, rotm)
refwcs.wcs.set()
ref_tpwcs = tweakwcs.FITSWCS(refwcs)
tweakwcs.align_wcs([imcat1, imcat2],
refcat,
ref_tpwcs=ref_tpwcs,
match=_match,
nclip=None,
sigma=3,
fitgeom='general')
fi1 = imcat1.meta['fit_info']
fi2 = imcat2.meta['fit_info']
w1 = imcat1.wcs
w2 = imcat2.wcs
assert fi1['rmse'] < 1e-4
assert fi2['rmse'] < 1e-4
cat1 = imcat1.meta['catalog']
ra1, dec1 = w1.all_pix2world(cat1['x'], cat1['y'], 0)
cat2 = imcat2.meta['catalog']
ra2, dec2 = w2.all_pix2world(cat2['x'], cat2['y'], 0)
ra = np.concatenate([ra1, ra2])
dec = np.concatenate([dec1, dec2])
rmse_ra = np.sqrt(np.mean((ra - refcat['RA'])**2))
rmse_dec = np.sqrt(np.mean((dec - refcat['DEC'])**2))
assert rmse_ra < 5e-9
assert rmse_dec < 5e-9