Thank you very much for the quick reply. However, this does not seem to work. The code in the new notebook appears identical to the old one. The code snippet below fails to produce a cutout:
from pyvo.dal import sia
import numpy as np
DEF_ACCESS_URL = "https://datalab.noao.edu/sia/des_dr1"
svc = sia.SIAService(DEF_ACCESS_URL)
fov=0.01
ra=7.7923125
dec=-41.3655
def download_deepest_images(ra,dec,fov=0.01,bands=list('gri')):
imgTable = svc.search((ra,dec), (fov/np.cos(dec*np.pi/180), fov), verbosity=2).to_table() #.votable #.get_first_table()
print("The full image list contains {:d} entries.".format(len(imgTable)))
sel0 = (imgTable['proctype'] == b'Stack') & (imgTable['prodtype']==b'image') # basic selection
images = []
for band in bands:
print("Band {:s}: ".format(band), end='')
sel = sel0 & (imgTable['obs_bandpass'] == band.encode()) # add 'band' to selection
Table = imgTable[sel] # select
row = Table[np.argmax(Table['exptime'].data.data.astype('float'))] # pick image with longest exposure time
url = row['access_url'] # get the download URL
print('downloading deepest stacked image...')
img = io.fits.getdata(utils.data.download_file(url.decode(),cache=True,show_progress=False,timeout=120)) # .decode() b/c in Python 3 url is of "byte" type and getdata() expects "string" type
images.append(img)
print("Downloaded {:d} images.".format(len(images)))
return images
img = download_deepest_images(ra,dec,fov=0.01,bands=['r'])