Image Access#
In this notebook, we show how to search for and retrieve images from VO services using the Registry and the Simple Image Access (SIA) protocol.
*Note: for all of these notebooks, the results depend on real-time queries. Sometimes there are problems, either because a given service has changed, is undergoing maintenance, or the internet connectivity is having problems, etc. Always retry a couple of times, come back later and try again, and only then send us the problem report to investigate.
import warnings
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
import pyvo as vo
from astropy.io import fits
import astropy.coordinates as coord
# For downloading files
from astropy.utils.data import download_file
from IPython.display import Image as ipImage, display
# There are a number of relatively unimportant warnings that show up, so for now, suppress them:
warnings.filterwarnings("ignore", module="astropy.io.votable.*")
warnings.filterwarnings("ignore", module="pyvo.utils.xml.*")
1. Finding SIA resources from the Registry#
First, how do we find out what services are available? These are listed in a registry at STScI (see here). Our Registry function gives a simple interface for how to search for services.
Let’s search for services providing images in the ultraviolet bands:
uv_services = vo.regsearch(servicetype='sia',waveband='uv')
uv_services.to_table()['ivoid','short_name','res_title']
Table length=18
| ivoid | short_name | res_title |
|---|---|---|
| object | object | object |
| ivo://archive.stsci.edu/sia/galex | GALEX | Galaxy Evolution Explorer (GALEX) |
| ivo://archive.stsci.edu/siap/hla | HLA | Hubble Legacy Archive |
| ivo://irsa.ipac/mast/scrapbook | MAST-Scrapbook | The MAST Image Scrapbook |
| ivo://mast.stsci/acsggct | HST.ACSGGCT | ACS Galactic Globular Cluster Survey (ACSGGCT) |
| ivo://mast.stsci/angrrr | HST.ANGRRR | Archive of Nearby Galaxies: Reduce, Reuse, Recycle (ANGRRR) |
| ivo://mast.stsci/candels | CANDELS | Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) |
| ivo://mast.stsci/clash | HST.CLASH | Cluster Lensing And Supernova survey with Hubble (CLASH) |
| ivo://mast.stsci/hippies | HST.HIPPIES | Hubble Infrared Pure Parallel Imaging Extragalactic Survey (HIPPIES) |
| ivo://mast.stsci/phat | PHAT | Panchromatic Hubble Andromeda Treasury (PHAT) |
| ivo://mast.stsci/siap/galex_atlas | GALEX_Atlas | GALEX Atlas of Nearby Galaxies |
| ivo://mast.stsci/siap/hst.maoz_atlas | HST.maoz_atlas | HST Ultraviolet Atlas of Nearby Galaxies |
| ivo://mast.stsci/siap/udfuv | HST.udfuv | Hubble Space Telescope Ultraviolet Images of the UDF and HDF |
| ivo://mast.stsci/siap/uit | UIT | Ultraviolet Imaging Telescope (UIT) |
| ivo://nasa.heasarc/skyview/euve | EUVE | Extreme Ultraviolet Explorer: 83 A |
| ivo://nasa.heasarc/skyview/galex | GALEX | Galaxy Explorer All Sky Survey: Near UV |
| ivo://nasa.heasarc/skyview/skyview | SkyView | SkyView Virtual Observatory |
| ivo://nasa.heasarc/skyview/swiftuvot | SWIFTUVOT | Swift UVOT Combined V Intensity Images |
| ivo://nasa.heasarc/skyview/wfcf | WFCF | ROSAT Wide Field Camera: F1 |
This returns an astropy table containing information about the services available. We can then specify the service we want by using the corresponding row. We’ll repeat the search with additional qualifiers to isolate the row we want (note that in the keyword search the “%” character can be used as a wild card):
uvot_services = vo.regsearch(servicetype='sia',waveband='uv',keywords=['swift'])
uvot_services.to_table()['ivoid','short_name','res_title']
Table length=1
| ivoid | short_name | res_title |
|---|---|---|
| object | object | object |
| ivo://nasa.heasarc/skyview/swiftuvot | SWIFTUVOT | Swift UVOT Combined V Intensity Images |
This shows us that the data we are interested in comes from the HEASARC’s SkyView service, but the point of these VO tools is that you don’t need to know that ahead of time or indeed to care where it comes from.
2. Using SIA to retrieve an image#
Now we look for images of our favorite source. See the SIA definition for usage. In short, you can specify the central position and the size (degrees as one or two floats for the RA, DEC directions). It is up to the service to determine how to provide this. Optionally, you can limit it to the format you want, e.g., “image/fits” or “image/png” etc.
What is returned to you is not the image itself but a list of images available and how to access them. This is easiest shown by example:
coords = coord.SkyCoord.from_name("m51")
im_table = uvot_services[0].search(pos=coords,size=0.2,format='image/jpeg')
im_table.to_table()
Table length=6
| Survey | Ra | Dec | Dim | Size | Scale | Format | PixFlags | URL | LogicalName |
|---|---|---|---|---|---|---|---|---|---|
| object | float64 | float64 | int32 | object | object | object | object | object | object |
| swiftuvotvint | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/jpeg | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925032792&nofits=1&quicklook=jpeg&return=jpeg | 1 |
| swiftuvotbint | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/jpeg | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotbint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925033094&nofits=1&quicklook=jpeg&return=jpeg | 2 |
| swiftuvotuint | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/jpeg | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotuint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925034224&nofits=1&quicklook=jpeg&return=jpeg | 3 |
| swiftuvotuvw1int | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/jpeg | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotuvw1int&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925034739&nofits=1&quicklook=jpeg&return=jpeg | 4 |
| swiftuvotuvw2int | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/jpeg | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotuvw2int&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925035263&nofits=1&quicklook=jpeg&return=jpeg | 5 |
| swiftuvotuvm2int | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/jpeg | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotuvm2int&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925035812&nofits=1&quicklook=jpeg&return=jpeg | 6 |
Extract the fields you’re interested in, e.g., the URLs of the images made by skyview. Note that specifying as we did SwiftUVOT, we get a number of different images, e.g., UVOT U, V, B, W1, W2, etc. For each survey, there are two URLs, first the FITS IMAGE and second the JPEG.
Note that different services will return different column names, but all will have a column giving the URL to access the image. Though it has different column names in different services, it can always be accessed through the getdataurl function.
url = im_table[0].getdataurl()
print(url)
https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925032792&nofits=1&quicklook=jpeg&return=jpeg
3. Viewing the resulting image#
JPG images#
Since we have asked for JPEG images, we can display an image in python easily by using its URL. Each row of the result has a getdataurl() method, and you can then hand the URL to an image displayer such as IPython.display:
img = ipImage(url=im_table[0].getdataurl())
display(img)
Fits files#
Or download the FITS image and display it with imshow, or aplpy.
(This often errors off with a time out message. Just try it again, possibly a couple of times.)
# Do the search again asking for FITS
im_table = uvot_services[0].search(pos=coords,size=0.2,format='image/fits')
# Hand the url of the first result to fits.open()
hdu_list = fits.open(im_table[0].getdataurl())
hdu_list.info()
Filename: /home/runner/.astropy/cache/download/url/41856ae32f4e530158f97f295cfa3288/contents
No. Name Ver Type Cards Dimensions Format
0 PRIMARY 1 PrimaryHDU 111 (300, 300) float32
Using imshow#
plt.imshow(hdu_list[0].data, cmap='gray', origin='lower',vmax=0.1)
<matplotlib.image.AxesImage at 0x7fc7758e0c10>
4. Example of data available through multiple services#
Suppose we want Sloan DSS data. A generic query finds us a number of possibilities (note that this doesn’t work for keywords=[‘sdss’]; be flexible and try several search terms):
services = vo.regsearch(servicetype='sia', keywords=['sloan'], waveband='optical')
services.to_table()[np.where(np.isin(services.to_table()['short_name'], 'SDSSDR7'))]['ivoid', 'short_name']
Table length=2
| ivoid | short_name |
|---|---|
| object | object |
| ivo://nasa.heasarc/skyview/sdssdr7 | SDSSDR7 |
| ivo://sdss.jhu/services/siapdr7-images | SDSSDR7 |
So one of these is served by SDSS’s SkyServer and the other by HEASARC’s SkyView.
Using HEASARC#
heasarc_dr7_service = [s for s in services if 'SDSSDR7' in s.short_name and 'heasarc' in s.ivoid][0]
sdss_table_heasarc = heasarc_dr7_service.search(pos=coords,size=0.2,format='image/fits')
sdss_table_heasarc.to_table()
Table length=5
| Survey | Ra | Dec | Dim | Size | Scale | Format | PixFlags | URL | LogicalName |
|---|---|---|---|---|---|---|---|---|---|
| object | float64 | float64 | int32 | object | object | object | object | object | object |
| sdssdr7g | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/fits | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=sdssdr7g&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925043355&return=FITS | 1 |
| sdssdr7i | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/fits | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=sdssdr7i&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925043815&return=FITS | 2 |
| sdssdr7u | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/fits | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=sdssdr7u&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925044370&return=FITS | 3 |
| sdssdr7r | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/fits | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=sdssdr7r&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925044873&return=FITS | 4 |
| sdssdr7z | 202.469575 | 47.19525833 | 2 | [300 300] | [-0.0006666666666666668 0.0006666666666666668] | image/fits | F | https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=sdssdr7z&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1730925045415&return=FITS | 5 |
## If you only run this once, you can do it in memory in one line:
## This fetches the FITS as an astropy.io.fits object in memory
# hdu_list = sdss_table_heasarc[0].getdataobj()
## But if you might run this notebook repeatedly with limited bandwidth,
## download it once and cache it.
# Get the filter g version
file_name=download_file(sdss_table_heasarc[0].getdataurl(), cache=True, timeout=600)
hdu_list = fits.open(file_name)
plt.imshow(hdu_list[0].data, cmap='gray', origin='lower', vmax=1200, vmin=1010)
<matplotlib.image.AxesImage at 0x7fc7759c7e20>
Using SDSS SkyServer#
jhu_dr7_service = [s for s in services if 'SDSSDR7' in s.short_name and 'jhu' in s.ivoid][0]
# Note: jhu_dr7_service access url has hard-wired "format=image/fits".
# If you specify anythign else, it errors. If you specify nothing,
# then the search() method puts "format=all", which errors. So specify "format=None" for now.
sdss_table_jhu=jhu_dr7_service.search(pos=coords,size=0.2, format=None)
sdss_table_jhu.to_table().show_in_notebook(display_length = 5)
WARNING: AstropyDeprecationWarning: show_in_notebook() is deprecated as of 6.1 and to create
interactive tables it is recommended to use dedicated tools like:
- https://github.com/bloomberg/ipydatagrid
- https://docs.bokeh.org/en/latest/docs/user_guide/interaction/widgets.html#datatable
- https://dash.plotly.com/datatable [warnings]
Table length=30
| idx | Title | width | height | size | RA | DEC | scale | format | url | equinox | naxes | naxis | crtype | crpix | crval | cdval |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Sloan Digital Sky Survey - Filter u | 2048 | 1489 | 3049472.0 | 202.439715840115 | 47.1222952774076 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-u6-0100.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.439715840115 47.1222952774076] | [3.57829352076884e-05 0.000157654334590212 0.000107291403325821\n -2.42761847386219e-05] |
| 1 | Sloan Digital Sky Survey - Filter g | 2048 | 1489 | 3049472.0 | 202.438763451233 | 47.1224982411069 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-g6-0100.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.438763451233 47.1224982411069] | [3.57455198349534e-05 0.000157658871914506 0.000107248674325512\n -2.4298297148212e-05] |
| 2 | Sloan Digital Sky Survey - Filter r | 2048 | 1489 | 3049472.0 | 202.440760551524 | 47.1223224530134 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-r6-0100.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.440760551524 47.1223224530134] | [3.57284422970295e-05 0.000157658504949188 0.000107285884319316\n -2.43020165047957e-05] |
| 3 | Sloan Digital Sky Survey - Filter i | 2048 | 1489 | 3049472.0 | 202.440280828514 | 47.1221470640024 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-i6-0100.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.440280828514 47.1221470640024] | [3.57634273620044e-05 0.00015761708892598 0.000107330126376146\n -2.43196618936367e-05] |
| 4 | Sloan Digital Sky Survey - Filter z | 2048 | 1489 | 3049472.0 | 202.439529079822 | 47.1222577816612 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-z6-0100.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.439529079822 47.1222577816612] | [3.57150015372814e-05 0.000157643765195985 0.000107288170305585\n -2.43520424844304e-05] |
| 5 | Sloan Digital Sky Survey - Filter u | 2048 | 1489 | 3049472.0 | 202.471051455651 | 47.3353076054504 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-u6-0117.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.471051455651 47.3353076054504] | [3.59720233632108e-05 0.000158234026889022 0.000107269639460545\n -2.43685414700374e-05] |
| 6 | Sloan Digital Sky Survey - Filter g | 2048 | 1489 | 3049472.0 | 202.470063167219 | 47.3355466663192 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-g6-0117.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.470063167219 47.3355466663192] | [3.59432847686782e-05 0.000158250992709564 0.000107232188959642\n -2.43648103577398e-05] |
| 7 | Sloan Digital Sky Survey - Filter r | 2048 | 1489 | 3049472.0 | 202.472135546076 | 47.3353955051599 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-r6-0117.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.472135546076 47.3353955051599] | [3.59415181020478e-05 0.000158248434019201 0.000107267969211639\n -2.43568204128413e-05] |
| 8 | Sloan Digital Sky Survey - Filter i | 2048 | 1489 | 3049472.0 | 202.471591570338 | 47.3352202087437 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-i6-0117.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.471591570338 47.3352202087437] | [3.59688512209066e-05 0.000158230937820391 0.000107320614280034\n -2.43668898148645e-05] |
| 9 | Sloan Digital Sky Survey - Filter z | 2048 | 1489 | 3049472.0 | 202.470847588819 | 47.3353207915745 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-z6-0117.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.470847588819 47.3353207915745] | [3.59150654057983e-05 0.00015824237549979 0.000107275145174036\n -2.43601106879619e-05] |
| 10 | Sloan Digital Sky Survey - Filter u | 2048 | 1489 | 3049472.0 | 202.225036928579 | 47.1551517933957 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-u6-0099.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.225036928579 47.1551517933957] | [3.53810815495366e-05 0.000157828787897035 0.00010735924586165\n -2.39982457876422e-05] |
| 11 | Sloan Digital Sky Survey - Filter g | 2048 | 1489 | 3049472.0 | 202.224091627324 | 47.1553436740585 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-g6-0099.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.224091627324 47.1553436740585] | [3.53548077171863e-05 0.000157797128208248 0.000107310265876208\n -2.39869405117144e-05] |
| 12 | Sloan Digital Sky Survey - Filter r | 2048 | 1489 | 3049472.0 | 202.226056492917 | 47.1551938665937 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-r6-0099.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.226056492917 47.1551938665937] | [3.53239854402387e-05 0.000157838092689428 0.000107350303498701\n -2.40134094050143e-05] |
| 13 | Sloan Digital Sky Survey - Filter i | 2048 | 1489 | 3049472.0 | 202.225605041055 | 47.1550455961572 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-i6-0099.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.225605041055 47.1550455961572] | [3.53618397919858e-05 0.000157831872925887 0.000107392266900315\n -2.40224681475619e-05] |
| 14 | Sloan Digital Sky Survey - Filter z | 2048 | 1489 | 3049472.0 | 202.224857105949 | 47.1551902252221 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-z6-0099.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.224857105949 47.1551902252221] | [3.53164061106176e-05 0.000157807630023464 0.000107345229703656\n -2.40355209382835e-05] |
| 15 | Sloan Digital Sky Survey - Filter u | 2048 | 1489 | 3049472.0 | 202.65414815634 | 47.0890093294703 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-u6-0101.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.65414815634 47.0890093294703] | [3.6186786701617e-05 0.000157450314868615 0.000107233464444483\n -2.4630072177771e-05] |
| 16 | Sloan Digital Sky Survey - Filter g | 2048 | 1489 | 3049472.0 | 202.653196017819 | 47.0891999862019 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-g6-0101.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.653196017819 47.0891999862019] | [3.61524039632195e-05 0.000157442085661357 0.00010717248715869\n -2.46013858407994e-05] |
| 17 | Sloan Digital Sky Survey - Filter r | 2048 | 1489 | 3049472.0 | 202.655205868145 | 47.0890572388805 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-r6-0101.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.655205868145 47.0890572388805] | [3.61316360915276e-05 0.000157451582422518 0.000107220359933737\n -2.45849902948879e-05] |
| 18 | Sloan Digital Sky Survey - Filter i | 2048 | 1489 | 3049472.0 | 202.654691598783 | 47.0888727037152 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-i6-0101.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.654691598783 47.0888727037152] | [3.61725026693836e-05 0.000157408759294813 0.000107256525899337\n -2.45885571257842e-05] |
| 19 | Sloan Digital Sky Survey - Filter z | 2048 | 1489 | 3049472.0 | 202.653951395476 | 47.0889879470879 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3699/41/corr/6/fpC-003699-z6-0101.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.653951395476 47.0889879470879] | [3.61392099375964e-05 0.000157416042366347 0.000107201860921915\n -2.45540162771507e-05] |
| 20 | Sloan Digital Sky Survey - Filter u | 2048 | 1489 | 3049472.0 | 202.255551477957 | 47.3682645399901 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-u6-0116.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.255551477957 47.3682645399901] | [3.5570382561575e-05 0.000158445038179983 0.000107353085876542\n -2.4081056610898e-05] |
| 21 | Sloan Digital Sky Survey - Filter g | 2048 | 1489 | 3049472.0 | 202.254583463782 | 47.3684765773708 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-g6-0116.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.254583463782 47.3684765773708] | [3.55429049574138e-05 0.000158441335601828 0.0001072954627723\n -2.40523585981171e-05] |
| 22 | Sloan Digital Sky Survey - Filter r | 2048 | 1489 | 3049472.0 | 202.256634298929 | 47.3683388717643 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-r6-0116.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.256634298929 47.3683388717643] | [3.5535391375169e-05 0.000158453355528711 0.000107333345270551\n -2.40576281698322e-05] |
| 23 | Sloan Digital Sky Survey - Filter i | 2048 | 1489 | 3049472.0 | 202.256126709548 | 47.3681700486555 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-i6-0116.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.256126709548 47.3681700486555] | [3.55644270086165e-05 0.000158412619072351 0.000107373910671822\n -2.40626631095901e-05] |
| 24 | Sloan Digital Sky Survey - Filter z | 2048 | 1489 | 3049472.0 | 202.255368258593 | 47.368270602303 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-z6-0116.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.255368258593 47.368270602303] | [3.55222946951901e-05 0.000158417415117325 0.000107324985298729\n -2.40742017372421e-05] |
| 25 | Sloan Digital Sky Survey - Filter u | 2048 | 1489 | 3049472.0 | 202.686295412444 | 47.3019488258879 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-u6-0118.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.686295412444 47.3019488258879] | [3.6396285814486e-05 0.000158057354515325 0.000107211108269374\n -2.46403918053622e-05] |
| 26 | Sloan Digital Sky Survey - Filter g | 2048 | 1489 | 3049472.0 | 202.685332573606 | 47.3021963773602 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-g6-0118.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.685332573606 47.3021963773602] | [3.63470141127271e-05 0.000158088090573589 0.000107165416853572\n -2.46461762773735e-05] |
| 27 | Sloan Digital Sky Survey - Filter r | 2048 | 1489 | 3049472.0 | 202.687369272872 | 47.3020488643411 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-r6-0118.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.687369272872 47.3020488643411] | [3.63474460456217e-05 0.000158040522693102 0.000107200822294116\n -2.46394662940732e-05] |
| 28 | Sloan Digital Sky Survey - Filter i | 2048 | 1489 | 3049472.0 | 202.686842904523 | 47.3018572304656 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-i6-0118.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.686842904523 47.3018572304656] | [3.63775353745344e-05 0.000158080652297321 0.000107250752985642\n -2.46480089191703e-05] |
| 29 | Sloan Digital Sky Survey - Filter z | 2048 | 1489 | 3049472.0 | 202.686073538809 | 47.3020049052475 | [0.000110035211267606] | image/fits | http://das.sdss.org/imaging/3716/42/corr/6/fpC-003716-z6-0118.fit.gz | -- | 2 | [2048 1489] | RA--TAN,DEC--TAN | [744.5 1024.5] | [202.686073538809 47.3020049052475] | [3.63234400825991e-05 0.000158059886386157 0.000107205662505221\n -2.46188155996404e-05] |
# Get the filter g version
file_name=download_file(sdss_table_jhu[1].getdataurl(), cache=True, timeout=600)
hdu_list = fits.open(file_name)
plt.imshow(hdu_list[0].data, cmap='gray', origin='lower',vmax=1200,vmin=1010)
<matplotlib.image.AxesImage at 0x7fc773631f00>
It turns out that SkyView is just getting images by using the SIAP internally to get the data from the SDSS service. The point of the VO protocols is that you don’t need to know where the data are coming from. But they can be processed differently.