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Merge pull request #1968 from tinumide/ned-doc-cleanup
Ned documentation cleanup
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‎docs/ned/ned.rst

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@@ -1,5 +1,3 @@
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.. doctest-skip-all
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.. _astroquery.ned:
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******************************
@@ -15,21 +13,23 @@ and spectra queries on the other hand return the results as a list of
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`~astropy.io.fits.HDUList` objects. Below are some working examples that
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illustrate common use cases.
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Query an object
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---------------
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This may be used to query the object *by name* from the NED service. For
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instance if you want to query NGC 224
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.. code-block:: python
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.. doctest-remote-data::
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>>> from astroquery.ned import Ned
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>>> result_table = Ned.query_object("NGC 224")
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>>> print(result_table) # an astropy.table.Table
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No. Object Name RA(deg) ... Redshift Points Diameter Points Associations
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No. Object Name RA ... Redshift Points Diameter Points Associations
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degrees ...
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--- ----------- ---------- ... --------------- --------------- ------------
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1 MESSIER 031 10.68479 ... 26 7 2
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1 MESSIER 031 10.68479 ... 37 7 2
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Query a region
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--------------
@@ -43,38 +43,32 @@ be specified as a string in which case it will be parsed using
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arcmin. Another optional parameter is the equinox if coordinates are
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specified. By default this is J2000.0 but can also be set to B1950.0.
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.. code-block:: python
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.. doctest-remote-data::
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>>> from astroquery.ned import Ned
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>>> import astropy.units as u
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>>> result_table = Ned.query_region("3c 273", radius=0.05 * u.deg)
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>>> print(result_table)
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No. Object Name RA ... Diameter Points Associations
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degrees ...
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--- -------------------------- ---------- ... --------------- ------------
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1 WISEA J122855.03+020309.1 187.22917 ... 0 0
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2 SSTSL2 J122855.02+020313.7 187.22925 ... 0 0
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3 SSTSL2 J122855.23+020341.5 187.23013 ... 0 0
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4 SSTSL2 J122855.36+020346.9 187.23068 ... 0 0
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... ... ... ... ... ...
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863 SSTSL2 J122918.24+020330.7 187.326 ... 0 0
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864 SDSS J122918.38+020323.4 187.3266 ... 4 0
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865 SSTSL2 J122918.52+020338.9 187.32718 ... 0 0
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866 SSTSL2 J122918.64+020326.7 187.32767 ... 0 0
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Length = 866 rows
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No. Object Name ... Diameter Points Associations
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--- ------------------------ ... --------------- ------------
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1 3C 273:[PWC2011] 3640 ... 0 0
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2 3C 273:[PWC2011] 3592 ... 0 0
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3 3C 273:[PWC2011] 3593 ... 0 0
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4 3C 273:[PWC2011] 3577 ... 0 0
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5 SDSS J122856.35+020325.3 ... 3 0
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6 3C 273:[PWC2011] 3553 ... 0 0
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7 3C 273:[PWC2011] 3544 ... 0 0
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8 3C 273:[PWC2011] 3521 ... 0 0
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... ... ... ... ...
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346 3C 273:[PWC2011] 2370 ... 0 0
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347 SDSS J122917.00+020436.3 ... 4 0
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348 3C 273:[PWC2011] 2338 ... 0 0
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349 3C 273:[PWC2011] 2349 ... 0 0
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350 SDSS J122917.52+020301.5 ... 4 0
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351 3C 273:[PWC2011] 2326 ... 0 0
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352 SDSS J122917.72+020356.8 ... 3 0
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353 SDSS J122918.38+020323.4 ... 4 0
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Instead of using the name, the target may also be specified via
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coordinates. Any of the coordinate systems available in `astropy.coordinates`
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may be used (ICRS, Galactic, FK4, FK5). Note also the use of the equinox keyword argument:
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.. code-block:: python
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.. doctest-remote-data::
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>>> from astroquery.ned import Ned
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>>> import astropy.units as u
@@ -83,14 +77,20 @@ may be used (ICRS, Galactic, FK4, FK5). Note also the use of the equinox keyword
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... unit=(u.deg, u.deg), frame='fk4')
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>>> result_table = Ned.query_region(co, radius=0.1 * u.deg, equinox='B1950.0')
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>>> print(result_table)
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No. Object Name RA ... Diameter Points Associations
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degrees ...
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--- ------------------------- ---------- ... --------------- ------------
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1 WISEA J035137.90+384313.7 57.90793 ... 0 0
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2 WISEA J035138.59+384305.6 57.91062 ... 0 0
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3 WISEA J035139.28+384324.4 57.91371 ... 0 0
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4 WISEA J035139.77+384507.4 57.91572 ... 0 0
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... ... ... ... ... ...
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631 WISEA J035237.78+384519.3 58.15743 ... 0 0
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632 WISEA J035238.62+384431.9 58.16083 ... 0 0
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633 WISEA J035238.74+384352.1 58.16145 ... 0 0
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634 WISEA J035238.84+384437.0 58.16177 ... 0 0
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Length = 634 rows
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No. Object Name ... Diameter Points Associations
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--- ----------------------- ... --------------- ------------
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1 2MASX J03514350+3841573 ... 2 0
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2 2MASX J03514563+3839573 ... 2 0
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3 NVSS J035158+384747 ... 0 0
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4 2MASX J03521115+3849288 ... 2 0
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5 2MASX J03521844+3840179 ... 2 0
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Query in the IAU format
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^^^^^^^^^^^^^^^^^^^^^^^
@@ -104,19 +104,25 @@ queries). It defaults to ``B1950`` but again it may be set to ``J2000.0``. Note
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that Ned report results by searching in a 15 arcmin radius around the specified
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target.
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.. code-block:: python
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.. doctest-remote-data::
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109109
>>> from astroquery.ned import Ned
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>>> result_table = Ned.query_region_iau('1234-423', frame='SuperGalactic', equinox='J2000.0')
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>>> print(result_table)
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No. Object Name RA ... Diameter Points Associations
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degrees ...
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--- ------------------------- ---------- ... --------------- ------------
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1 WISEA J123639.37-423822.9 189.16406 ... 0 0
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2 WISEA J123639.47-423656.3 189.16458 ... 0 0
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3 WISEA J123639.61-423637.9 189.16506 ... 0 0
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4 WISEA J123639.91-423709.9 189.1663 ... 0 0
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... ... ... ... ... ...
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760 2MASS J12374631-4236174 189.44299 ... 0 0
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761 WISEA J123746.44-423727.9 189.44359 ... 0 0
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762 WISEA J123746.48-423838.1 189.4437 ... 0 0
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763 WISEA J123747.07-423742.9 189.44616 ... 0 0
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Length = 763 rows
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No. Object Name RA(deg) ... Diameter Points Associations
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--- ----------------------- ---------- ... --------------- ------------
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1 SUMSS J123651-423554 189.21425 ... 0 0
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2 SUMSS J123658-423457 189.245 ... 0 0
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3 SUMSS J123711-424119 189.29663 ... 0 0
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4 2MASX J12373141-4239342 189.38083 ... 2 0
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5 2MASX J12373567-4239122 189.39908 ... 2 0
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Query a reference code for objects
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -125,42 +131,36 @@ These queries can be used to retrieve all objects that appear in the specified
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19 digit reference code. These are similar to the
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:meth:`~astroquery.simbad.SimbadClass.query_bibobj` queries.
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.. code-block:: python
134+
.. doctest-remote-data::
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130136
>>> from astroquery.ned import Ned
131137
>>> result_table = Ned.query_refcode('1997A&A...323...31K')
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>>> print(result_table)
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No. Object Name RA ... Diameter Points Associations
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degrees ...
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--- ------------------------- ---------- ... --------------- ------------
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1 NGC 0262 12.19642 ... 8 0
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2 NGC 0449 19.0302 ... 7 0
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3 NGC 0591 23.38028 ... 7 0
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4 UGC 01214 25.99084 ... 7 0
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... ... ... ... ... ...
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33 WISEA J202325.39+113134.6 305.85577 ... 2 0
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34 UGC 12149 340.28163 ... 8 0
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35 MRK 0522 345.07954 ... 4 0
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36 NGC 7674 351.98635 ... 8 0
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Length = 36 rows
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No. Object Name RA(deg) ... Diameter Points Associations
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--- ----------------------- ---------- ... --------------- ------------
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1 NGC 0262 12.19642 ... 8 0
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2 NGC 0449 19.0302 ... 7 0
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3 NGC 0591 23.38028 ... 7 0
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4 UGC 01214 25.99084 ... 7 0
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5 2MASX J01500266-0725482 27.51124 ... 2 0
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6 MESSIER 077 40.66963 ... 8 0
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7 MRK 0599 41.94759 ... 6 0
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8 MRK 1058 42.46596 ... 4 0
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... ... ... ... ... ...
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30 NGC 5643 218.16977 ... 18 0
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31 SBS 1439+537 220.1672 ... 2 3
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32 MRK 1388 222.65772 ... 6 0
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33 2MASX J20232535+1131352 305.85577 ... 2 0
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34 UGC 12149 340.28163 ... 8 0
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35 MRK 0522 345.07954 ... 4 0
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36 NGC 7674 351.98635 ... 8 0
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Image and Spectra Queries
154155
^^^^^^^^^^^^^^^^^^^^^^^^^
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The image queries return a list of `~astropy.io.fits.HDUList` objects for the
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specified name. For instance:
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159-
.. code-block:: python
160+
.. doctest-remote-data::
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161162
>>> from astroquery.ned import Ned
162-
>>> images = Ned.get_images("m1")
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>>> images = Ned.get_images("m1") # doctest: +IGNORE_OUTPUT
164164
Downloading http://ned.ipac.caltech.edu/dss1B2/Bb/MESSIER_001:I:103aE:dss1.fits.gz
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|===========================================| 32k/ 32k (100.00%) 00s
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Downloading http://ned.ipac.caltech.edu/img5/1995RXCD3.T...0000C/p083n22a:I:0.1-2.4keV:cop1995.fits.gz
@@ -171,9 +171,7 @@ specified name. For instance:
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|===========================================| 52k/ 52k (100.00%) 01s
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Downloading http://ned.ipac.caltech.edu/img5/1998RXCD8.T...0000C/h083n22a:I:0.1-2.4keV:cps1998.fits.gz
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|===========================================| 35k/ 35k (100.00%) 00s
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>>> images # may be used to do further processing on individual cutouts
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>>> images # doctest: +IGNORE_OUTPUT
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[[<astropy.io.fits.hdu.image.PrimaryHDU at 0x4311890>],
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[<astropy.io.fits.hdu.image.PrimaryHDU at 0x432b350>],
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[<astropy.io.fits.hdu.image.PrimaryHDU at 0x3e9c5d0>],
@@ -182,49 +180,47 @@ specified name. For instance:
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To get the URLs of the downloadable FITS images:
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.. code-block:: python
183+
.. doctest-remote-data::
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187185
>>> from astroquery.ned import Ned
188186
>>> image_list = Ned.get_image_list("m1")
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>>> image_list
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>>> image_list # doctest: +NORMALIZE_WHITESPACE
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['http://ned.ipac.caltech.edu/dss1B2/Bb/MESSIER_001:I:103aE:dss1.fits.gz',
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'http://ned.ipac.caltech.edu/img5/1995RXCD3.T...0000C/p083n22a:I:0.1-2.4keV:cop1995.fits.gz',
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'http://ned.ipac.caltech.edu/img5/1996RXCD6.T...0000C/p083n22a:I:0.1-2.4keV:cps1996.fits.gz',
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'http://ned.ipac.caltech.edu/img5/1995RXCD3.T...0000C/p084n22a:I:0.1-2.4keV:cop1995.fits.gz',
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'http://ned.ipac.caltech.edu/img5/1998RXCD8.T...0000C/h083n22a:I:0.1-2.4keV:cps1998.fits.gz']
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'http://ned.ipac.caltech.edu/img/1995RXCD3.T...0000C/p084n22a:I:0.1-2.4keV:cop1995.fits.gz',
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'http://ned.ipac.caltech.edu/img/1996RXCD6.T...0000C/p083n22a:I:0.1-2.4keV:cps1996.fits.gz',
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'http://ned.ipac.caltech.edu/img/1998RXCD8.T...0000C/h083n22a:I:0.1-2.4keV:cps1998.fits.gz',
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'http://ned.ipac.caltech.edu/img/1995RXCD3.T...0000C/p083n22a:I:0.1-2.4keV:cop1995.fits.gz']
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Spectra can also be fetched in the same way:
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.. code-block:: python
197+
.. doctest-remote-data::
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201199
>>> from astroquery.ned import Ned
202-
>>> spectra = Ned.get_spectra('3c 273')
203-
200+
>>> spectra = Ned.get_spectra('3c 273') # doctest: +IGNORE_OUTPUT
204201
Downloading http://ned.ipac.caltech.edu/spc1/2009A+A...495.1033B/3C_273:S:B:bcc2009.fits.gz
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|===========================================| 7.8k/7.8k (100.00%) 00s
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Downloading http://ned.ipac.caltech.edu/spc1/1992ApJS...80..109B/PG_1226+023:S:B_V:bg1992.fits.gz
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|===========================================| 5.0k/5.0k (100.00%) 00s
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Downloading http://ned.ipac.caltech.edu/spc1/2009A+A...495.1033B/3C_273:S:RI:bcc2009.fits.gz
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|===========================================| 9.4k/9.4k (100.00%) 00s
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>>> spectra
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207+
>>> spectra # doctest: +IGNORE_OUTPUT
213208
[[<astropy.io.fits.hdu.image.PrimaryHDU at 0x41b4190>],
214209
[<astropy.io.fits.hdu.image.PrimaryHDU at 0x41b0990>],
215210
[<astropy.io.fits.hdu.image.PrimaryHDU at 0x430a450>]]
216211

212+
217213
Similarly the list of URLs for spectra of a particular object may be fetched:
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219-
.. code-block:: python
215+
.. doctest-remote-data::
220216

221217
>>> from astroquery.ned import Ned
222-
>>> image_list = Ned.get_image_list("3c 273", item='spectra')
223-
>>> image_list
218+
>>> spectra_list = Ned.get_image_list("3c 273", item='spectra')
219+
>>> spectra_list
220+
['http://ned.ipac.caltech.edu/spc1/1992/1992ApJS...80..109B/PG_1226+023:S:B_V:bg1992.fits.gz',
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'http://ned.ipac.caltech.edu/spc1/2009/2009A+A...495.1033B/3C_273:S:B:bcc2009.fits.gz',
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'http://ned.ipac.caltech.edu/spc1/2009/2009A+A...495.1033B/3C_273:S:RI:bcc2009.fits.gz']
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['http://ned.ipac.caltech.edu/spc1/2009A+A...495.1033B/3C_273:S:B:bcc2009.fits.gz',
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'http://ned.ipac.caltech.edu/spc1/1992ApJS...80..109B/PG_1226+023:S:B_V:bg1992.fits.gz',
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'http://ned.ipac.caltech.edu/spc1/2009A+A...495.1033B/3C_273:S:RI:bcc2009.fits.gz']
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Fetching other data tables for an object
230226
----------------------------------------
@@ -235,26 +231,25 @@ queries. These take a keyword argument ``table``, which may be set to one of
235231
instance the ``table=photometry`` will fetch all the relevant photometric data
236232
for the specified object. We look at a simple example:
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.. code-block:: python
234+
.. doctest-remote-data::
239235

240236
>>> from astroquery.ned import Ned
241237
>>> result_table = Ned.get_table("3C 273", table='positions')
242238
>>> print(result_table)
239+
No. RA ... Published Frequence Mode Qualifiers
240+
...
241+
--- -------------- ... ------------------------ -------------------------
242+
0 12h29m06.6997s ...
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1 12h29m06.7000s ... Uncertain origin
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2 12h29m06.7000s ... Uncertain origin
245+
3 12h29m06.7000s ... Uncertain origin
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... ... ... ... ...
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113 12h29m07.9s ... Uncertain origin
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114 12h29m04s ... Uncertain origin
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115 12h29m06s ... Uncertain origin
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116 12h29m08s ... Uncertain origin
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Length = 117 rows
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No. RA DEC ... Published Frame Published Frequence Mode Qualifiers
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--- -------------- -------------- ... --------------- ------------------------- --------------------------------------------------------------
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0 12h29m06.6997s +02d03m08.598s ...
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1 12h29m06.6997s +02d03m08.598s ... ICR Multiple line measurement From new, raw data
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2 12h29m06.699s +02d03m08.59s ... ICR Broad-band measurement From new, raw data
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3 12h29m06.64s +02d03m09.0s ... FK4 Broad-band measurement From reprocessed raw data; Corrected for contaminating sources
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4 12h29m06.79s +02d03m08.0s ... FK5 Broad-band measurement From new, raw data; Systematic errors in RA and Dec corrected
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5 12h29m06.05s +02d02m57.1s ... FK4 Broad-band measurement From new, raw data
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6 12h29m05.60s +02d03m09.0s ... FK5 Broad-band measurement From new, raw data
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7 12h29m04.5s +02d03m03s ... Broad-band measurement From new, raw data
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8 12h29m07.55s +02d03m02.3s ... FK4 Broad-band measurement From reprocessed raw data
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9 12h29m06.05s +02d03m11.3s ... FK4 Broad-band measurement From new, raw data
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10 12h29m06.5s +02d02m53s ... FK4 Broad-band measurement From new, raw data
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11 12h29m06.5s +02d02m52s ... FK4 Broad-band measurement From reprocessed raw data
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Reference/API
260255
=============

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