def test_find_all_wcs_crash():
"""
Causes a double free without a recent fix in wcslib_wrap.C
"""
with open(get_pkg_data_filename("data/too_many_pv.hdr")) as fd:
header = fd.read()
# We have to set fix=False here, because one of the fixing tasks is to
# remove redundant SCAMP distortion parameters when SIP distortion
# parameters are also present.
with pytest.raises(wcs.InvalidTransformError), pytest.warns(wcs.FITSFixedWarning):
wcs.find_all_wcs(header, fix=False)
def validate_source_input(**kwargs):
if "filename" in kwargs and kwargs["filename"] is not None:
filename = kwargs["filename"]
if utils.find_file(filename) is None:
warnings.warn("filename was not found: {}".format(filename))
if "image" in kwargs and kwargs["image"] is not None:
image_hdu = kwargs["image"]
if not isinstance(image_hdu, (fits.PrimaryHDU, fits.ImageHDU)):
raise ValueError("image must be fits.HDU object with a WCS."
"type(image) == {}".format(type(image_hdu)))
if len(wcs.find_all_wcs(image_hdu.header)) == 0:
warnings.warn("image does not contain valid WCS. {}"
"".format(wcs.WCS(image_hdu)))
if "table" in kwargs and kwargs["table"] is not None:
tbl = kwargs["table"]
if not isinstance(tbl, Table):
raise ValueError("table must be an astropy.Table object:"
"{}".format(type(tbl)))
if not np.all([col in tbl.colnames for col in ["x", "y", "ref"]]):
raise ValueError("table must contain at least column names: "
"'x, y, ref': {}".format(tbl.colnames))
return True
def test_find_all_wcs_crash():
"""
Causes a double free without a recent fix in wcslib_wrap.C
"""
with open(get_pkg_data_filename("data/too_many_pv.hdr")) as fd:
header = fd.read()
# We have to set fix=False here, because one of the fixing tasks is to
# remove redundant SCAMP distortion parameters when SIP distortion
# parameters are also present.
wcses = wcs.find_all_wcs(header, fix=False)
def test_spectra(self):
for filename in self._file_list:
# use the base name of the file, so we get more useful messages
# for failing tests.
filename = os.path.basename(filename)
# Now find the associated file in the installed wcs test directory.
header = get_pkg_data_contents(
os.path.join("data", "spectra", filename), encoding='binary')
# finally run the test.
all_wcs = wcs.find_all_wcs(header)
assert len(all_wcs) == 9
def test_spectra(self):
for filename in self._file_list:
# use the base name of the file, so we get more useful messages
# for failing tests.
filename = os.path.basename(filename)
# Now find the associated file in the installed wcs test directory.
header = get_pkg_data_contents(
os.path.join("data", "spectra", filename), encoding='binary')
# finally run the test.
all_wcs = wcs.find_all_wcs(header)
assert len(all_wcs) == 9
def test_spectrum(filename):
# the test parameter is the base name of the file to use; find
# the file in the installed wcs test directory
filename = os.path.join(ROOT_DIR, "spectra", filename)
fd = open(filename, 'rb')
header = fd.read()
fd.close()
wcsobj = wcs.WCS(header)
all = wcs.find_all_wcs(header)
assert len(all) == 9
def get_cluster_data(clid, *args, **kwargs):
""" Creates a container of all important data related to a cluster
Parameters
----------
clid: int
cluster id
Returns
-------
data: dict
dictionary of all related information
"""
if ('ap' not in clid.lower()):
raise NotImplemented('synthetics not implemented yet.')
apid = int(clid[2:])
# read profile data
profile_image = pyfits.getdata(data_path['image475'].format(apid=apid))
profile_header = pyfits.getheader(data_path['image475'].format(apid=apid))
profile_wcs = wcs.find_all_wcs(profile_header)[0]
# read MATCH data
match_output = np.genfromtxt(data_path['match_output'].format(apid=apid),
skip_header=10,
skip_footer=2)
with open(data_path['match_sfh'].format(apid=apid), 'r') as f:
match_params = f.readlines()
match_cmd = np.loadtxt(data_path['match_cmd'].format(apid=apid),
skiprows=4,
dtype=match_dtype)
match_fakepath = data_path['match_fake'].format(apid=apid)
bg_stars = Table(data_path['match_sky'].format(apid=apid), caseless=True)
match_bg = np.loadtxt(data_path['match_bg'].format(apid=apid),
dtype=[('F475W_VEGA', float), ('F814W_VEGA', float)])
# photometric catalog
phot = Table(data_path['phot'].format(apid=apid), caseless=True)
# convert stars ra,dec to pixels
stars_xy = profile_wcs.wcs_world2pix(
np.column_stack([phot['ra'], phot['dec']]), 0)
sky_xy = profile_wcs.wcs_world2pix(
np.column_stack([bg_stars['ra'], bg_stars['dec']]), 0)
# extract color-mag
keys = ','.join(phot.keys())
if ('vega' in keys) or ('VEGA' in keys):
color_name = 'F475W-F814W'
mag_name = 'F475W'
color = phot('F475W_VEGA-F814W_VEGA')
mag = phot('F475W_VEGA')
sky_color = bg_stars('F475W_VEGA-F814W_VEGA')
sky_mag = bg_stars('F475W_VEGA')
data = {
'apid': apid,
'profile': {
'image': profile_image,
'header': profile_header,
'wcs': profile_wcs
},
'match': {
'output': match_output,
'params': match_params,
'cmd': match_cmd,
'bg': match_bg,
'sky': bg_stars,
'fake': match_fakepath,
'sky_xy': sky_xy,
'sky_color': sky_color,
'sky_mag': sky_mag
},
'phot': {
'cat': phot,
'xy': stars_xy,
'color': color,
'mag': mag,
'color_name': color_name,
'mag_name': mag_name
}
}
return data
