@@ -96,9 +96,9 @@ pos = SkyCoord(ra=ra, dec=dec, unit='deg')
9696## 2. Discover COSMOS images
9797
9898``` {code-cell} ipython3
99- # Search the Virtual Observatory Registry for image services at IRSA associated with the COSMOS survey.
99+ # Search the Virtual Observatory Registry for SIAv1 image services at IRSA associated with the COSMOS survey.
100100image_services = regsearch(
101- servicetype='sia1 ',
101+ servicetype='sia ',
102102 keywords=['cosmos', 'irsa']
103103)
104104
@@ -107,16 +107,16 @@ for i, r in enumerate(image_services):
107107 print(f"{i:2d} {r.short_name:20s} {r.res_title}")
108108
109109# Turn the result into a usable image access service
110- resource = image_services[0]
111- cosmos_service = resource.get_service("sia1 ")
110+ resource = image_services[0]
111+ cosmos_service = resource.get_service("sia ")
112112```
113113
114114## 3. Search for images
115115Which images in the COSMOS dataset include our target of interest?
116116
117117``` {code-cell} ipython3
118118# Get a table of all images that cover this position.
119- # Choose the size of the returned image.
119+ # Choose the size of the returned image.
120120im_results = cosmos_service.search(pos=pos, size=150*u.arcsec)
121121
122122# Convert the PyVO result to an Astropy Table
@@ -167,10 +167,10 @@ print(image_url)
167167# Use Astropy to examine the header of the URL from the previous step,
168168# and grab the data and wcs from the header.
169169with fits.open(image_url, memmap=False) as hdul:
170- hdul.info()
170+ hdul.info()
171171 data = hdul[0].data
172172 wcs = WCS(hdul[0].header)
173-
173+
174174```
175175
176176``` {code-cell} ipython3
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