.. _astroquery.vizier: ************************************ VizieR Queries (`astroquery.vizier`) ************************************ Getting started =============== This is a python interface for querying the VizieR web service. This supports querying an object as well as querying a region around the target. For region queries, the region dimensions may be specified either for a box or as a radius. Similar to the VizieR web interface, the queries may be further constrained by specifying a choice of catalogs, keywords as well as filters on individual columns before retrieving the results. .. note:: In earlier versions of astroquery (<0.4.8), columns with special characters like ``r'mag`` were renamed into ``r_mag`` and columns starting with a number like ``2MASS`` were prepended with an underscore ``_2MASS``. In astroquery >=0.4.8, the column names are the same in VizieR's webpages and in the tables received (for the two examples: you'll see ``r'mag`` and ``2MASS``). Catalogs exploration -------------------- If you want to search for a set of tables, e.g. based on author name or other keywords, the :meth:`~astroquery.vizier.VizierClass.find_catalogs` tool can be used: .. order is not deterministic .. doctest-remote-data:: >>> from astroquery.vizier import Vizier >>> vizier = Vizier() # this instantiates Vizier with its default parameters >>> catalog_list = vizier.find_catalogs('hot jupiter exoplanet transit') >>> for k, v in catalog_list.items(): # doctest: +IGNORE_OUTPUT ... print(k, ":", v.description) J/A+A/635/A205 : Ultra-hot Jupiter WASP-121b transits (Bourrier+, 2020) J/ApJ/788/39 : Hot Jupiter exoplanets host stars EW and abundances (Teske+, 2014) J/AJ/157/217 : Transit times of five hot Jupiter WASP exoplanets (Bouma+, 2019) J/A+A/635/A122 : CoRoT-30b and CoRoT-31b radial velocity curves (Border+, 2020) From this list, you can either get any catalog completely (all the lines) or make sub-selections with :meth:`~astroquery.vizier.VizierClass.query_region`, or with additional criteria. Get a whole catalog ------------------- From the result of the precedent example, let's select ``J/ApJ/788/39``. We call :meth:`~astroquery.vizier.VizierClass.get_catalogs`. Let's fix the number of returned rows to 1 for now, to minimize the amount of data we download and speed up exploration, while we inspect the result: .. doctest-remote-data:: >>> vizier.ROW_LIMIT = 1 >>> exoplanets = vizier.get_catalogs("J/ApJ/788/39") >>> exoplanets TableList with 2 tables: '0:J/ApJ/788/39/stars' with 7 column(s) and 1 row(s) '1:J/ApJ/788/39/table4' with 48 column(s) and 1 row(s) .. note:: ``ROW_LIMIT`` is set to 50 per default. We see that this catalog has two tables. One named ``J/ApJ/788/39/stars`` and the other one is ``J/ApJ/788/39/table4``. Let's look at the columns of ``J/ApJ/788/39/stars`` from the single row that we just downloaded: .. doctest-remote-data:: >>> exoplanets[0] Name RAJ2000 DEJ2000 Vmag Name1 lines Simbad mag str9 str11 str11 float32 str8 str5 str6 ------- ----------- ----------- ------- ------ ----- ------ CoRoT-2 19 27 06.50 +01 23 01.4 12.57 COROT2 lines Simbad .. note:: The coordinates columns often have the information about the frame and epoch in their descriptions: .. doctest-remote-data:: >>> exoplanets[0]["RAJ2000"].description 'Simbad Hour of Right Ascension (J2000)' When we're ready to download the complete table, we can set the row limit to -1 (for infinity). .. doctest-remote-data:: >>> vizier.ROW_LIMIT = -1 >>> stars = vizier.get_catalogs("J/ApJ/788/39/stars") >>> # stars is a TableList with only one table. Here is its first and only element >>> stars[0]
Name RAJ2000 DEJ2000 Vmag Name1 lines Simbad mag str9 str11 str11 float32 str8 str5 str6 --------- ----------- ----------- ------- -------- ----- ------ CoRoT-2 19 27 06.50 +01 23 01.4 12.57 COROT2 lines Simbad TrES-4 17 53 13.06 +37 12 42.4 11.59 TRES4 lines Simbad TrES-2 19 07 14.04 +49 18 59.1 11.25 TRES2 lines Simbad WASP-2 20 30 54.13 +06 25 46.4 11.98 WASP2 lines Simbad WASP-12 06 30 32.79 +29 40 20.3 11.57 WASP12 lines Simbad HD 149026 16 30 29.62 +38 20 50.3 8.14 HD149026 lines Simbad HAT-P-1 22 57 46.84 +38 40 30.3 10.40 HATP1 lines Simbad XO-2S 07 48 07.48 +50 13 03.3 11.25 XO2S lines Simbad XO-2N 07 48 06.47 +50 13 33.0 11.25 XO2N lines Simbad XO-1 16 02 11.85 +28 10 10.4 11.25 XO1 lines Simbad TRES-3 17 52 07.02 +37 32 46.2 12.40 TRES3 lines Simbad HD 189733 20 00 43.71 +22 42 39.1 7.68 HD189733 lines Simbad HD 80606 09 22 37.58 +50 36 13.4 9.00 HD80606 lines Simbad HAT-P-7 19 28 59.35 +47 58 10.2 10.48 HATP7 lines Simbad HAT-P-13 08 39 31.81 +47 21 07.3 10.42 HATP13 lines Simbad HAT-P-16 00 38 17.56 +42 27 47.2 10.91 HATP16 lines Simbad WASP-32 00 15 50.81 +01 12 01.6 11.26 WASP32 lines Simbad Alternatively, we could have downloaded all the catalogs from the results of :meth:`~astroquery.vizier.VizierClass.find_catalogs`. Be careful when doing so, as this might be huge. .. doctest-remote-data:: >>> vizier.ROW_LIMIT = 50 # we reset to the default value >>> catalogs = vizier.get_catalogs(catalog_list.keys()) >>> print(catalogs) # doctest: +IGNORE_OUTPUT TableList with 10 tables: '0:J/A+A/635/A205/20140119' with 7 column(s) and 50 row(s) '1:J/A+A/635/A205/20140123' with 7 column(s) and 50 row(s) '2:J/A+A/635/A205/20171231' with 7 column(s) and 50 row(s) '3:J/A+A/635/A205/20180114' with 7 column(s) and 50 row(s) '4:J/A+A/635/A205/ccf-mask' with 3 column(s) and 50 row(s) '5:J/ApJ/788/39/stars' with 7 column(s) and 17 row(s) '6:J/ApJ/788/39/table4' with 48 column(s) and 50 row(s) '7:J/AJ/157/217/transits' with 8 column(s) and 50 row(s) '8:J/A+A/635/A122/table2' with 4 column(s) and 18 row(s) '9:J/A+A/635/A122/table3' with 4 column(s) and 17 row(s) We downloaded the 50 first rows of these 10 tables. Get a catalog's associated metadata ----------------------------------- The method `~astroquery.vizier.VizierClass.get_catalog_metadata` retrieves information about VizieR's catalogs. It returns a table with the following columns: - title - authors - abstract - origin_article -- the bibcode of the associated article - webpage -- a link to VizieR, contains more information about the catalog - created -- date of creation of the catalog *in VizieR* - updated -- date of the last modification applied to the entry, this is often about metadata, with no appearance in the history on the webpage but sometimes it is about a data erratum, which will appear in the history tab .. note:: This value can be extra useful to check if you need to download some catalog again from VizieR or if you can work safely with a result you saved previously on disk. Also note that the VizieR team actively maintains the catalogs but if a published erratum was missed we'd gladly receive a notification from you! - waveband - doi -- the catalog doi when it exists .. doctest-remote-data:: >>> from astroquery.vizier import Vizier >>> Vizier(catalog="VII/74A").get_catalog_metadata()
title authors ... waveband doi object object ... object object -------------------------- -------- ... -------- ------ Atlas of Peculiar Galaxies Arp H.C. ... optical -- Query an object --------------- For instance to query Sirius across all catalogs: .. doctest-remote-data:: >>> from astroquery.vizier import Vizier >>> vizier = Vizier(row_limit=10) >>> result = vizier.query_object("sirius") # doctest: +IGNORE_WARNINGS >>> print(result) TableList with ... tables: '0:METAobj' with 5 column(s) and 7 row(s) '1:ReadMeObj' with 5 column(s) and 7 row(s) '2:I/34/greenw2a' with 16 column(s) and 1 row(s) ... All the results are returned as a `~astroquery.utils.TableList` object. This is a container for `~astropy.table.Table` objects. It is basically an extension to `~collections.OrderedDict` for storing a `~astropy.table.Table` against its name. To access an individual table from the `~astroquery.utils.TableList` object: .. doctest-remote-data:: >>> interesting_table = result['IX/8/catalog'] >>> print(interesting_table) 2XRS RAB1950 DEB1950 Xname ... Int _RA.icrs _DE.icrs ... uJy --------- ------------ ------------ ----- ... --- ------------ ------------ 06429-166 06 42 54.000 -16 39 00.00 ... -- 06 45 08.088 -16 42 11.29 06429-166 06 42 54.000 -16 39 00.00 ... -- 06 45 08.088 -16 42 11.29 To do some common processing to all the tables in the returned `~astroquery.utils.TableList` object, do just what you would do for a python dictionary: .. doctest-remote-data:: >>> for table_name in result.keys(): ... table = result[table_name] ... # table is now an `astropy.table.Table` object ... # some code to apply on table Query a region -------------- To query a region either the coordinates or the object name around which to query should be specified along with the value for the radius (or height/width for a box) of the region. For instance to query a large region around the quasar 3C 273: .. doctest-remote-data:: >>> from astroquery.vizier import Vizier >>> from astropy.coordinates import Angle >>> vizier = Vizier() >>> result = vizier.query_region("3C 273", radius=Angle(0.1, "deg"), catalog='GSC') Note that the radius may also be specified as a string in the format expected by `~astropy.coordinates.Angle`. So the above query may also be written as: .. doctest-remote-data:: >>> result = vizier.query_region("3C 273", radius="0d6m0s", catalog='GSC') Or using angular units and quantities from `astropy.units`: .. doctest-remote-data:: >>> import astropy.units as u >>> result = vizier.query_region("3C 273", radius=0.1*u.deg, catalog='GSC') To see the result: .. doctest-remote-data:: >>> print(result) TableList with 5 tables: '0:I/254/out' with 10 column(s) and 17 row(s) '1:I/255/out' with 9 column(s) and 17 row(s) '2:I/271/out' with 11 column(s) and 50 row(s) '3:I/305/out' with 11 column(s) and 50 row(s) '4:I/353/gsc242' with 35 column(s) and 50 row(s) As mentioned earlier, the region may also be mentioned by specifying the height and width of a box. If only one of the height or width is mentioned, then the region is treated to be a square having sides equal to the specified dimension. .. doctest-remote-data:: >>> from astroquery.vizier import Vizier >>> import astropy.units as u >>> import astropy.coordinates as coord >>> vizier = Vizier() >>> result = vizier.query_region(coord.SkyCoord(ra=299.590, dec=35.201, ... unit=(u.deg, u.deg), ... frame='icrs'), ... width="30m", ... catalog=["NOMAD", "UCAC"]) >>> print(result) TableList with 3 tables: '0:I/297/out' with 19 column(s) and 50 row(s) '1:I/322A/out' with 24 column(s) and 50 row(s) '2:I/340/ucac5' with 20 column(s) and 50 row(s) One more thing to note in the above example is that the coordinates may be specified by using the appropriate coordinate object from `astropy.coordinates`. Especially for ICRS coordinates, some support also exists for directly passing a properly formatted string as the coordinate. Finally the ``catalog`` keyword argument may be passed in either :meth:`~astroquery.vizier.VizierClass.query_object` or :meth:`~astroquery.vizier.VizierClass.query_region` methods. This may be a string (if only a single catalog) or a list of strings otherwise. Last but not least, :meth:`~astroquery.vizier.VizierClass.query_region` also supports constraints on the columns of the returned tables by mean of the ``column_filters`` keyword. .. doctest-remote-data:: >>> from astroquery.vizier import Vizier >>> import astropy.units as u >>> from astropy.coordinates import SkyCoord >>> vizier = Vizier() >>> result = vizier.query_region(SkyCoord.from_name('M81'), ... radius=10*u.arcmin, ... catalog='I/345/gaia2', ... column_filters={'Gmag': '<19'}) >>> print(result[0]['Gmag'].max()) 18.9508 Specifying keywords, output columns and constraints on columns -------------------------------------------------------------- To specify keywords on which to search as well as conditions on the output columns, an instance of the `~astroquery.vizier.VizierClass` class specifying these must be first created. All further queries may then be performed on this instance rather than on the Vizier class. .. doctest-remote-data:: >>> vizier = Vizier(columns=['_RAJ2000', '_DEJ2000','B-V', 'Vmag', 'Plx'], ... column_filters={"Vmag":">10"}, keywords=["optical", "xry"]) # doctest: +IGNORE_WARNINGS Note that whenever an unknown keyword is specified (here ``xry``) a warning is emitted and that keyword is discarded from further consideration. The behavior for searching with these keywords is the same as defined for the web interface (`for details see here`_). Now we call the different query methods on this Vizier instance: .. output can be in any order here .. doctest-remote-data:: >>> vizier = Vizier(columns=['_RAJ2000', '_DEJ2000','B-V', 'Vmag', 'Plx'], ... column_filters={"Vmag":">10"}, keywords=["optical"]) >>> result = vizier.query_object("HD 226868", catalog=["NOMAD", "UCAC"]) >>> print(result) TableList with 3 tables: '0:I/297/out' with 3 column(s) and 50 row(s) '1:I/322A/out' with 3 column(s) and 10 row(s) '2:I/340/ucac5' with 2 column(s) and 26 row(s) >>> print(result['I/322A/out']) # doctest: +IGNORE_OUTPUT _RAJ2000 _DEJ2000 Vmag deg deg mag ------------- ------------- ------ 299.572418900 35.194234200 15.986 299.580291200 35.176888900 13.274 299.582571200 35.185225300 14.863 299.594171800 35.179994800 14.690 299.601402100 35.198107800 14.644 299.617668600 35.186998700 14.394 299.561497700 35.201692800 15.687 299.570216500 35.225663400 14.878 299.601080600 35.233337800 13.170 299.617995000 35.205863700 13.946 When specifying the columns of the query, sorting of the returned table can be requested by adding ``+`` (or ``-`` for reverse sorting order) in front of the column name. In the following example, the standard (``"*"``) columns and the calculated distance column (``"_r"``) of the 2MASS catalog (II/246) are queried, 20 arcsec around HD 226868. The result is sorted in increasing distance, as requested with the ``"+"`` in front of ``"_r"``. .. doctest-remote-data:: >>> vizier = Vizier(columns=["*", "+_r"], catalog="II/246") >>> result = vizier.query_region("HD 226868", radius="20s") >>> print(result[0]) _r RAJ2000 DEJ2000 2MASS Jmag ... Bflg Cflg Xflg Aflg deg deg mag ... ------ ---------- ---------- ---------------- ------ ... ---- ---- ---- ---- 0.134 299.590280 35.201599 19582166+3512057 6.872 ... 111 000 0 0 10.135 299.587491 35.203217 19582099+3512115 10.285 ... 111 c00 0 0 11.167 299.588599 35.198849 19582126+3511558 13.111 ... 2 00c 0 0 12.288 299.586356 35.200542 19582072+3512019 14.553 ... 111 ccc 0 0 17.691 299.586254 35.197994 19582070+3511527 16.413 ... 100 c00 0 0 Note: The special column ``"*"`` requests just the default columns of a catalog; ``"**"`` would request all the columns. Query with table ---------------- A `~astropy.table.Table` can also be used to specify the coordinates in a region query *if* it contains the columns ``_RAJ2000`` and ``_DEJ2000``. The following example starts by looking for AGNs in the Veron & Cety catalog with a ``Vmag`` between 10.0 and 11.0. Based on the result of this first query, guide stars with a ``Kmag`` brighter than 9.0 are looked for, with a separation between 2 and 30 arcsec. The column ``_q`` in the ``guide`` table is a 1-based index to the ``agn`` table (not the 0-based python convention). .. doctest-remote-data:: >>> agn = Vizier(catalog="VII/258/vv10", ... columns=['*', '_RAJ2000', '_DEJ2000']).query_constraints(Vmag="10.0..11.0")[0] >>> print(agn) _RAJ2000 _DEJ2000 Cl nR Name ... Sp n_Vmag Vmag B-V r_z deg deg ... mag mag ---------- ---------- --- --- ------------- ... ---- ------ ----- ----- ---- 10.684583 41.269444 Q M 31 ... S2 10.57 1.08 1936 60.277917 -16.110833 Q NPM1G-16.0168 ... R 10.16 -- 988 27.238750 5.906667 A * NGC 676 ... S2 10.50 -- 1034 40.669583 -0.013056 A NGC 1068 ... S1h 10.83 0.87 58 139.759583 26.269722 A NGC 2824 ... S? 10.88 -- 2528 147.592083 72.279167 A NGC 2985 ... S1.9 10.61 0.76 1033 173.144167 53.067778 A NGC 3718 ... S3b 10.61 0.74 1033 184.960833 29.613889 A UGC 7377 ... S3 10.47 0.99 2500 185.028750 29.280833 A NGC 4278 ... S3b 10.87 0.98 1033 186.453750 33.546667 A NGC 4395 ... S1.8 10.27 0.53 1033 192.719583 41.119444 A NGC 4736 ... S 10.85 0.85 1032 208.361250 40.283056 A NGC 5353 ... S? R 10.91 -- 368 .. doctest-remote-data:: >>> guide = Vizier(catalog="II/246", column_filters={"Kmag":"<9.0"}).query_region(agn, radius="30s", inner_radius="2s")[0] >>> guide.pprint() _q RAJ2000 DEJ2000 2MASS Jmag ... Rflg Bflg Cflg Xflg Aflg deg deg mag ... --- ---------- ---------- ---------------- ------ ... ---- ---- ---- ---- ---- 1 10.686015 41.269630 00424464+4116106 9.399 ... 20 20 0c0 2 0 1 10.685657 41.269550 00424455+4116103 10.773 ... 200 200 c00 2 0 1 10.685837 41.270599 00424460+4116141 9.880 ... 20 20 0c0 2 0 1 10.683263 41.267456 00424398+4116028 12.136 ... 200 100 c00 2 0 1 10.683465 41.269676 00424403+4116108 11.507 ... 200 100 c00 2 0 3 27.238636 5.906066 01485727+0554218 8.961 ... 112 111 000 0 0 4 40.669277 -0.014225 02424062-0000512 11.795 ... 200 100 c00 2 0 4 40.668802 -0.013064 02424051-0000470 11.849 ... 200 100 c00 2 0 4 40.669219 -0.012236 02424061-0000440 12.276 ... 200 100 c00 2 0 4 40.670761 -0.012208 02424098-0000439 12.119 ... 200 100 c00 2 0 4 40.670177 -0.012830 02424084-0000461 11.381 ... 200 100 c00 2 0 11 192.721982 41.121040 12505327+4107157 10.822 ... 200 100 c00 2 0 11 192.721179 41.120201 12505308+4107127 9.306 ... 222 111 000 2 0 Troubleshooting =============== If you are repeatedly getting failed queries, or bad/out-of-date results, try clearing your cache: .. code-block:: python >>> from astroquery.vizier import Vizier >>> Vizier.clear_cache() If this function is unavailable, upgrade your version of astroquery. The ``clear_cache`` function was introduced in version 0.4.7.dev8479. Reference/API ============= .. automodapi:: astroquery.vizier :no-inheritance-diagram: .. _for details see here: https://vizier.cds.unistra.fr/vizier/vizHelp/1.htx