def get_VLASS_images(position, radius, showgrid=False, savefile=''):
cadc = Cadc()
result = cadc.query_region(position, collection='VLASS')
if len(result) == 0:
print('No Data at CADC at position: {}'.format(
position.to_string('hmsdms')))
else:
urls = cadc.get_data_urls(result)
for url in urls:
cutout_url = construct_cadc_url(url, position, radius)
plot_http_fits(cutout_url, showgrid, savefile)
def test_query_region(self):
cadc = Cadc()
result = cadc.query_region('08h45m07.5s +54d18m00s', collection='CFHT')
# do some manipulation of the results. Below it's filtering out based
# on target name but other manipulations are possible.
assert len(result) > 0
urls = cadc.get_data_urls(result[result['target_name'] == 'Nr3491_1'])
assert len(urls) > 0
# urls are a subset of the results that match target_name==Nr3491_1
assert len(result) >= len(urls)
urls_data_only = len(urls)
# now get the auxilary files too
urls = cadc.get_data_urls(result[result['target_name'] == 'Nr3491_1'],
include_auxiliaries=True)
assert urls_data_only <= len(urls)
# the same result should be obtained by querying the entire region
# and filtering out on the CFHT collection
result2 = cadc.query_region('08h45m07.5s +54d18m00s')
assert len(result) == len(result2[result2['collection'] == 'CFHT'])
# search for a target
results = cadc.query_region(SkyCoord.from_name('M31'), radius=0.016)
assert len(results) > 20
def test_query_region(self):
cadc = Cadc()
result = cadc.query_region('08h45m07.5s +54d18m00s', collection='CFHT')
# do some manipulation of the results. Below it's filtering out based
# on target name but other manipulations are possible.
assert len(result) > 0
urls = cadc.get_data_urls(result[result['target_name'] == 'Nr3491_1'])
assert len(urls) > 0
# urls are a subset of the results that match target_name==Nr3491_1
assert len(result) >= len(urls)
urls_data_only = len(urls)
# now get the auxilary files too
urls = cadc.get_data_urls(result[result['target_name'] == 'Nr3491_1'],
include_auxiliaries=True)
assert urls_data_only <= len(urls)
# the same result should be obtained by querying the entire region
# and filtering out on the CFHT collection
result2 = cadc.query_region('08h45m07.5s +54d18m00s')
assert len(result) == len(result2[result2['collection'] == 'CFHT'])
# search for a target
results = cadc.query_region(SkyCoord.from_name('M31'))
assert len(results) > 20
parser.add_argument("dec",
help="DEC of the source in +00d00m00.00s format",
type=str)
parser.add_argument("radius",
help="radius around ra dec center",
type=str,
default="3 arcmin")
args = parser.parse_args()
ra = args.ra
dec = args.dec
radius = args.radius
cadc = Cadc()
coords = ra + " " + dec
results = cadc.query_region(coords, radius, collection='VLASS')
image_list = cadc.get_image_list(results, coords, radius)
if (len(image_list) > 1):
print("The coordinates entered are present in more than one field!")
for i in range(len(image_list)):
print(i, " : ", image_list[i])
field_id = input("Enter field you would like to download : ")
field_id = int(field_id)
sel_image = image_list[field_id]
filename = sel_image.split("/")[-1].split("&")[0][21:]
print(filename)
print("Downloading VLASS image : ", filename)
urlretrieve(sel_image, filename)
else:
sel_image = image_list[0]
##--------------------------------------------------------------------------##
for nn, tinfo in enumerate(targets, 1):
targ, tname = tinfo
sys.stderr.write("%s\n" % fulldiv)
sys.stderr.write("Target %d of %d: %s\n" % (nn, len(targets), tname))
# ensure output folder exists:
save_dir = os.path.join(context.output_dir, tname)
if not os.path.isdir(save_dir):
os.mkdir(save_dir)
# retrieve query results
sys.stderr.write("Querying CFHT database ... ")
#hits = cadc.query(coord=targ, size=context.search_rad_deg, dataset=1)
hits = cadc.query_region(targ, radius=srch_deg, collection='CFHT')
hits.sort('productID')
sys.stderr.write("done.\n")
# select useful subset:
sys.stderr.write("Selecting useful subset ... ")
useful = pick_favorites(hits)
useful['ibase'] = ['%s.fits.fz' % x for x in useful['productID']]
useful['isave'] = [os.path.join(save_dir, x) for x in useful['ibase']]
sys.stderr.write("done. Identified %d images.\n" % len(useful))
# exclude images already retrieved:
already_have = np.array([os.path.isfile(x) for x in useful['isave']])
nfound = np.sum(already_have)
sys.stderr.write("Excluding %d already-retrieved images.\n" % nfound)
useful = useful[~already_have]
