Searching for contributed COSMOS images

Searching for contributed COSMOS images#

This notebook tutorial demonstrates the process of querying IRSA’s Simple Image Access (SIA) service for the COSMOS images, making a cutout image (thumbnail), and displaying the cutout.

Learning Goals#

By the end of this tutorial, you will:

  • Learn how to search the NASA Astronomical Virtual Observatory Directory web portal for a service that provides access to IRSA’s COSMOS images.

  • Use the Python pyvo package to identify which of IRSA’s COSMOS images cover a specified coordinate.

  • Download one of the identified images.

  • Create and display a cutout of the downloaded image.

Introduction#

The COSMOS Archive serves data taken for the Cosmic Evolution Survey with HST (COSMOS) project, using IRSA’s general search service, Atlas. COSMOS is an HST Treasury Project to survey a 2 square degree equatorial field with the ACS camera. For more information about COSMOS, see:

https://irsa.ipac.caltech.edu/Missions/cosmos.html

The NASA/IPAC Infrared Science Archive (IRSA) at Caltech is one of the archives for COSMOS images and catalogs. The COSMOS images that are the subject of this tutorial are made accessible via the International Virtual Observatory Alliance (IVOA) Simple Image Access (SIA) protocol. IRSA’s SEIP SIA service is registered in the NASA Astronomical Virtual Observatory (NAVO) Directory. Based on the registered information, the Python package pyvo can be used to query the SIA service for a list of images that meet specified criteria, and standard Python libraries can be used to download and manipulate the images. Other datasets at IRSA are available through other SIA services:

https://irsa.ipac.caltech.edu/docs/program_interface/api_images.html

Imports#

  • pyvo for querying IRSA’s COSMOS SIA service

  • astropy.coordinates for defining coordinates

  • astropy.nddata for creating an image cutout

  • astropy.wcs for interpreting the World Coordinate System header keywords of a fits file

  • astropy.units for attaching units to numbers passed to the SIA service

  • matplotlib.pyplot for plotting

  • astropy.utils.data for downloading files

  • astropy.io to manipulate FITS files

# Uncomment the next line to install dependencies if needed.
# !pip install matplotlib astropy pyvo

import pyvo as vo
from astropy.coordinates import SkyCoord
from astropy.nddata import Cutout2D
from astropy.wcs import WCS
import astropy.units as u
import matplotlib.pyplot as plt
from astropy.utils.data import download_file
from astropy.io import fits

Section 1 - Setup#

Set images to display in the notebook

%matplotlib inline

Define coordinates of a bright source

ra = 149.99986
dec = 2.24875
pos = SkyCoord(ra=ra, dec=dec, unit='deg')

Section 2 - Lookup and define a service for COSMOS images#

Start at STScI VAO Registry at https://vao.stsci.edu/keyword-search/

Limit by Publisher “NASA/IPAC Infrared Science Archive” and Capability Type “Simple Image Access Protocol” then search on “COSMOS”

Locate the SIA2 URL https://irsa.ipac.caltech.edu/cgi-bin/Atlas/nph-atlas?mission=COSMOS&hdr_location=%5CCOSMOSDataPath%5C&collection_desc=Cosmic+Evolution+Survey+with+HST+%28COSMOS%29&SIAP_ACTIVE=1&

cosmos_service = vo.dal.SIAService("https://irsa.ipac.caltech.edu/cgi-bin/Atlas/nph-atlas?mission=COSMOS&hdr_location=%5CCOSMOSDataPath%5C&collection_desc=Cosmic+Evolution+Survey+with+HST+%28COSMOS%29&SIAP_ACTIVE=1&")

Section 3 - Search the service#

Search for images covering within 1 arcsecond of the star

im_table = cosmos_service.search(pos=pos, size=1.0*u.arcsec)

Inspect the table of images that is returned

im_table

<DALResultsTable length=279>
   ra   ...
  deg   ...
float64 ...
------- ...
150.014 ...
150.022 ...
150.014 ...
150.022 ...
149.977 ...
149.977 ...
150.061 ...
150.061 ...
150.116 ...
    ... ...
150.061 ...
150.061 ...
150.061 ...
150.061 ...
150.061 ...
150.061 ...
150.061 ...
150.061 ...
149.995 ...

im_table.to_table().colnames

['ra',
 'dec',
 'cra',
 'cdec',
 'naxis1',
 'naxis2',
 'ctype1',
 'ctype2',
 'crval1',
 'crval2',
 'crpix1',
 'crpix2',
 'cdelt1',
 'cdelt2',
 'crota2',
 'ra1',
 'dec1',
 'ra2',
 'dec2',
 'ra3',
 'dec3',
 'ra4',
 'dec4',
 'equinox',
 'hdu',
 'facility_name',
 'instrument_name',
 'dataproduct_type',
 'file_type',
 'band_name',
 'wavelength',
 'access_estsize',
 's_fov',
 'tile',
 'fname',
 'dataset',
 'cutout',
 'sia_desc',
 'sia_naxes',
 'sia_naxis',
 'sia_scale',
 'sia_cdmatrix',
 'sia_format',
 'sia_url']

View the first ten entries of the table

im_table.to_table()[:10]
Table length=10
radeccracdecnaxis1naxis2ctype1ctype2crval1crval2crpix1crpix2cdelt1cdelt2crota2ra1dec1ra2dec2ra3dec3ra4dec4equinoxhdufacility_nameinstrument_namedataproduct_typefile_typeband_namewavelengthaccess_estsizes_fovtilefnamedatasetcutoutsia_descsia_naxessia_naxissia_scalesia_cdmatrixsia_formatsia_url
degdeg
float64float64objectobjectint32int32objectobjectfloat64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64int32objectobjectobjectobjectobjectfloat64int32float64int32objectobjectobjectobjectint32objectobjectobjectobjectobject
150.0142.22410h 00m 03.41s+02d 13m 27.3s75007500RA---TANDEC--TAN150.01422692.2242473750.03750.0-8.3333333333e-068.3333333333e-06260.2377156149.97810892.1987513150.03974912.188154150.05035592.2497487149.98871322.26034652000.00HSTACSimagescienceI8.0874e-072250430.0625-99images/acs_2.0/I/acs_I_100003+0213_unrot_sci_20.fitsHST-ACSYESCosmic Evolution Survey with HST (COSMOS)2[7500 7500][-8.3333333333e-06 8.3333333333e-06][-8.33333e-06 -0.0 -0.0 8.33333e-06]image/fitshttps://irsa.ipac.caltech.edu:443/cgi-bin/Subimage/nph-subimage?origfile=/irsadata/COSMOS//images%2Facs_2.0%2FI%2Facs_I_100003%2B0213_unrot_sci_20.fits&ra=149.999860&dec=2.248750&xsize=0.000278
150.0222.27610h 00m 05.35s+02d 16m 32.8s75007500RA---TANDEC--TAN150.02230832.27578253750.03750.0-8.3333333333e-068.3333333333e-06260.2376781149.98618892.2502868150.04783122.2396894150.05843852.3012841149.99679362.31188192000.00HSTACSimagescienceI8.0874e-072250430.0625-99images/acs_2.0/I/acs_I_100005+0216_unrot_sci_20.fitsHST-ACSYESCosmic Evolution Survey with HST (COSMOS)2[7500 7500][-8.3333333333e-06 8.3333333333e-06][-8.33333e-06 -0.0 -0.0 8.33333e-06]image/fitshttps://irsa.ipac.caltech.edu:443/cgi-bin/Subimage/nph-subimage?origfile=/irsadata/COSMOS//images%2Facs_2.0%2FI%2Facs_I_100005%2B0216_unrot_sci_20.fits&ra=149.999860&dec=2.248750&xsize=0.000278
150.0142.22410h 00m 03.41s+02d 13m 27.3s75007500RA---TANDEC--TAN150.01422692.2242473750.03750.0-8.3333333333e-068.3333333333e-06260.2377156149.97810892.1987513150.03974912.188154150.05035592.2497487149.98871322.26034652000.00HSTACSimageweightI8.0874e-072250430.0625-99images/acs_2.0/I/acs_I_100003+0213_unrot_wht_20.fitsHST-ACSYESCosmic Evolution Survey with HST (COSMOS)2[7500 7500][-8.3333333333e-06 8.3333333333e-06][-8.33333e-06 -0.0 -0.0 8.33333e-06]image/fitshttps://irsa.ipac.caltech.edu:443/cgi-bin/Subimage/nph-subimage?origfile=/irsadata/COSMOS//images%2Facs_2.0%2FI%2Facs_I_100003%2B0213_unrot_wht_20.fits&ra=149.999860&dec=2.248750&xsize=0.000278
150.0222.27610h 00m 05.35s+02d 16m 32.8s75007500RA---TANDEC--TAN150.02230832.27578253750.03750.0-8.3333333333e-068.3333333333e-06260.2376781149.98618892.2502868150.04783122.2396894150.05843852.3012841149.99679362.31188192000.00HSTACSimageweightI8.0874e-072250430.0625-99images/acs_2.0/I/acs_I_100005+0216_unrot_wht_20.fitsHST-ACSYESCosmic Evolution Survey with HST (COSMOS)2[7500 7500][-8.3333333333e-06 8.3333333333e-06][-8.33333e-06 -0.0 -0.0 8.33333e-06]image/fitshttps://irsa.ipac.caltech.edu:443/cgi-bin/Subimage/nph-subimage?origfile=/irsadata/COSMOS//images%2Facs_2.0%2FI%2Facs_I_100005%2B0216_unrot_wht_20.fits&ra=149.999860&dec=2.248750&xsize=0.000278
149.9772.21009h 59m 54.57s+02d 12m 34.5s40964096RA---TANDEC--TAN150.11632132.2009731-1284.51841.0-4.166666832e-054.166666832e-050.0150.06278462.124243149.89196012.1242277149.89193442.2949346150.06277842.29495122000.00CFHTMegaPrimeimageuncertaintyu3.798e-07671150.17066766images/cfht/u/original_psf/cfht_u_066_rms_50.fitsCFHTNOCosmic Evolution Survey with HST (COSMOS)2[4096 4096][-4.166666832e-05 4.166666832e-05][-4.16667e-05 -0.0 -0.0 4.16667e-05]image/fitshttps://irsa.ipac.caltech.edu:443/data/COSMOS/images/cfht/u/original_psf/cfht_u_066_rms_50.fits
149.9772.21009h 59m 54.57s+02d 12m 34.5s40964096RA---TANDEC--TAN150.11632132.2009731-1284.51841.0-4.166666832e-054.166666832e-050.0150.06278462.124243149.89196012.1242277149.89193442.2949346150.06277842.29495122000.00CFHTMegaPrimeimagescienceu3.798e-07671150.17066766images/cfht/u/original_psf/cfht_u_066_sci_50.fitsCFHTNOCosmic Evolution Survey with HST (COSMOS)2[4096 4096][-4.166666832e-05 4.166666832e-05][-4.16667e-05 -0.0 -0.0 4.16667e-05]image/fitshttps://irsa.ipac.caltech.edu:443/data/COSMOS/images/cfht/u/original_psf/cfht_u_066_sci_50.fits
150.0612.29310h 00m 14.58s+02d 17m 34.5s4809648096RA---TANDEC--TAN150.11632132.200973122715.521841.0-4.1666667e-054.1666667e-050.0151.06285611.290811149.05876461.2907673149.05734233.2942578151.06412923.29436952000.00CFHTMegaPrimeimagesciencei7.684e-0792529072.0040images/cfht/mosaics/COSMOS.i_c.original_psf.v2.fitsCFHTNOCosmic Evolution Survey with HST (COSMOS)2[48096 48096][-4.1666667e-05 4.1666667e-05][-4.16667e-05 -0.0 -0.0 4.16667e-05]image/fitshttps://irsa.ipac.caltech.edu:443/data/COSMOS/images/cfht/mosaics/COSMOS.i_c.original_psf.v2.fits
150.0612.29310h 00m 14.58s+02d 17m 34.5s4809648096RA---TANDEC--TAN150.11632132.200973122715.521841.0-4.1666667e-054.1666667e-050.0151.06285611.290811149.05876461.2907673149.05734233.2942578151.06412923.29436952000.00CFHTWIRCAMimagescienceKs2.146e-0692529072.0040images/cfht/mosaics/COSMOS.Ks.original_psf.v5.fitsCFHTNOCosmic Evolution Survey with HST (COSMOS)2[48096 48096][-4.1666667e-05 4.1666667e-05][-4.16667e-05 -0.0 -0.0 4.16667e-05]image/fitshttps://irsa.ipac.caltech.edu:443/data/COSMOS/images/cfht/mosaics/COSMOS.Ks.original_psf.v5.fits
150.1162.20110h 00m 27.92s+02d 12m 03.4s4533443585RA---TANDEC--TAN150.11632132.200973122667.521793.0-4.166666832e-054.166666832e-050.0151.06085771.2928109149.17182661.292811149.17067553.1084954151.06200883.10849532000.00CFHTMegaPrimeimagescienceu3.798e-0779035351.888920images/cfht/mosaics/COSMOS.u.original_psf.v5.fitsCFHTNOCosmic Evolution Survey with HST (COSMOS)2[45334 43585][-4.166666832e-05 4.166666832e-05][-4.16667e-05 -0.0 -0.0 4.16667e-05]image/fitshttps://irsa.ipac.caltech.edu:443/data/COSMOS/images/cfht/mosaics/COSMOS.u.original_psf.v5.fits
149.9772.21009h 59m 54.57s+02d 12m 34.5s40964096RA---TANDEC--TAN150.11632132.2009731-1284.51841.0-4.1666667e-054.1666667e-050.0150.06278462.124243149.89196012.1242277149.89193442.2949346150.06277842.29495122000.00CFHTWIRCAMimagescienceKs2.146e-06671150.17066766images/cfht/Ks/original_psf/cfht_Ks_066_sci_50.fitsCFHTNOCosmic Evolution Survey with HST (COSMOS)2[4096 4096][-4.1666667e-05 4.1666667e-05][-4.16667e-05 -0.0 -0.0 4.16667e-05]image/fitshttps://irsa.ipac.caltech.edu:443/data/COSMOS/images/cfht/Ks/original_psf/cfht_Ks_066_sci_50.fits

Section 4 - Locate and download an image of interest#

Locate the first image in the band_name of i+

for i in range(len(im_table)):
    if im_table[i]['band_name'] == 'i+':
        break
print(im_table[i].getdataurl())

https://irsa.ipac.caltech.edu:443/data/COSMOS/images/subaru/best_psf/ip/subaru_ip_best-psf_066_rms_20.fits

Download the image

fname = download_file(im_table[i].getdataurl(), cache=True)
image1 = fits.open(fname)

Section 5 - Extract a cutout and plot it#

wcs = WCS(image1[0].header)

Make a cutout centered on the position

cutout = Cutout2D(image1[0].data, pos, (60, 60), wcs=wcs)
wcs = cutout.wcs

fig = plt.figure()

ax = fig.add_subplot(1, 1, 1, projection=wcs)
ax.imshow(cutout.data, cmap='gray_r', origin='lower')
ax.scatter(ra, dec, transform=ax.get_transform('fk5'), s=500, edgecolor='red', facecolor='none')

<matplotlib.collections.PathCollection at 0x7feaa1cbaf50>
../../_images/c72f77de401eeb024e71fbf2da480f2b34d55107250f41445a25ed7a52bbc846.png

About this notebook#

Author: David Shupe, IRSA Scientist, and the IRSA Science Team

Updated On: 2022-02-14

Contact: irsasupport@ipac.caltech.edu or https://jira.ipac.caltech.edu/irsasupport

Citations#

If you use astropy for published research, please cite the authors. Follow these links for more information about citing astropy:

If you use COSMOS ACS imaging data in published research, please cite the dataset Digital Object Identifier (DOI): 10.26131/IRSA178.