SIMBAD Queries (astroquery.simbad)¶
Getting started¶
This module can be used to query the Simbad service. Presented below are
examples that illustrate the different types of queries that can be
formulated. If successful all the queries will return the results in a
Table.
A warning about big queries¶
The SIMBAD database is widely used and has to limit the rate of incoming queries.
If you spam the server with more that ~5-10 queries per second you will be
blacklisted for an hour. If it happens to you, you can use the section about
vectorized queries below. You can pass
query_region
a vector of coordinates or query_objects
a list of object names, and SIMBAD will treat this submission as a single
query.
Different ways to access Simbad¶
The Simbad tool described here provides a number of convenient methods that internally creates a script query to the Simbad server, which is also how the Simbad web interface operates.
A more versatile option is to query SIMBAD directly via Table Access Protocol
(TAP) with the query_tap method.
Query modes¶
Objects queries¶
Query by an Identifier¶
This is useful if you want to query a known identifier (name). For instance to query the messier object M1:
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_object("M1")
>>> print(result_table)
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
------- ----------- ----------- ------- -------- ------------ ------------ ------------- -------- -------------- -------------------
M 1 05 34 31.94 +22 00 52.2 6 6 nan nan 0 C R 2011A&A...533A..10L
Wildcards are supported. So for instance to query messier objects from 1 through 9:
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_object("m [1-9]", wildcard=True)
>>> print(result_table)
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
------- ----------- ----------- ------- -------- ------------ ------------ ------------- -------- -------------- -------------------
M 1 05 34 31.94 +22 00 52.2 6 6 nan nan 0 C R 2011A&A...533A..10L
M 2 21 33 27.02 -00 49 23.7 6 6 100.000 100.000 0 C O 2010AJ....140.1830G
M 3 13 42 11.62 +28 22 38.2 6 6 200.000 200.000 0 C O 2010AJ....140.1830G
M 4 16 23 35.22 -26 31 32.7 6 6 400.000 400.000 0 C O 2010AJ....140.1830G
M 5 15 18 33.22 +02 04 51.7 6 6 nan nan 0 C O 2010AJ....140.1830G
M 6 17 40 20 -32 15.2 4 4 nan nan 0 E O 2009MNRAS.399.2146W
M 7 17 53 51 -34 47.6 4 4 nan nan 0 E O 2009MNRAS.399.2146W
M 8 18 03 37 -24 23.2 4 4 18000.000 18000.000 179 E
M 9 17 19 11.78 -18 30 58.5 6 6 nan nan 0 D 2002MNRAS.332..441F
Wildcards are supported by other queries as well - where this is the case, examples are presented to this end. The wildcards that are supported and their usage across all these queries is the same. To see the available wildcards and their functions:
>>> from astroquery.simbad import Simbad
>>> Simbad.list_wildcards()
* : Any string of characters (including an empty one)
[^0-9] : Any (one) character not in the list.
? : Any character (exactly one character)
[abc] : Exactly one character taken in the list. Can also be defined by a range of characters: [A-Z]
Query to get all names (identifiers) for an object¶
These queries can be used to retrieve all of the names (identifiers) associated with an object.
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_objectids("Polaris")
>>> print(result_table)
ID
-----------------------
NAME Polaris
NAME North Star
NAME Lodestar
PLX 299
SBC9 76
* 1 UMi
* alf UMi
AAVSO 0122+88
ADS 1477 A
AG+89 4
BD+88 8
CCDM J02319+8915A
CSI+88 8 1
FK5 907
GC 2243
GCRV 1037
...
PPM 431
ROT 3491
SAO 308
SBC7 51
SKY# 3738
TD1 835
TYC 4628-237-1
UBV 21589
UBV M 8201
V* alf UMi
PLX 299.00
WDS J02318+8916Aa,Ab
ADS 1477 AP
** WRH 39
WDS J02318+8916A
** STF 93A
2MASS J02314822+8915503
Query a region¶
Queries that support a cone search with a specified radius - around an identifier or given coordinates are also supported. If an identifier is used then it will be resolved to coordinates using the Sesame name resolver.
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_region("m81")
>>> print(result_table)
MAIN_ID RA DEC RA_PREC DEC_PREC ... COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
-------------------------- ------------- ------------- ------- -------- ... ------------- -------- -------------- -------------------
[VV2006c] J095534.0+043546 09 55 33.9854 +04 35 46.438 8 8 ... 0 B O 2009A&A...505..385A
...
When no radius is specified, the radius defaults to 20 arcmin. A radius may
also be explicitly specified - it can be entered either as a string that is
acceptable by Angle or by using
the Quantity object:
>>> from astroquery.simbad import Simbad
>>> import astropy.units as u
>>> result_table = Simbad.query_region("m81", radius=0.1 * u.deg)
>>> # another way to specify the radius.
>>> result_table = Simbad.query_region("m81", radius='0d6m0s')
>>> print(result_table)
MAIN_ID RA ... COO_BIBCODE
----------------------- ------------- ... -------------------
M 81 09 55 33.1730 ... 2004AJ....127.3587F
[SPZ2011] ML2 09 55 32.97 ... 2011ApJ...735...26S
[F88] X-5 09 55 33.32 ... 2001ApJ...554..202I
[SPZ2011] 264 09 55 32.618 ... 2011ApJ...735...26S
[SPZ2011] ML1 09 55 33.10 ... 2011ApJ...735...26S
[SPZ2011] ML3 09 55 33.99 ... 2011ApJ...735...26S
[SPZ2011] ML5 09 55 33.39 ... 2011ApJ...735...26S
[SPZ2011] ML6 09 55 32.47 ... 2011ApJ...735...26S
... ... ... ...
[MPC2001] 8 09 54 45.50 ... 2001A&A...379...90M
2MASS J09561112+6859003 09 56 11.13 ... 2003yCat.2246....0C
[PR95] 50721 09 56 36.460 ...
PSK 72 09 54 54.1 ...
PSK 353 09 56 03.7 ...
[BBC91] S02S 09 56 07.1 ...
PSK 489 09 56 36.55 ... 2003AJ....126.1286L
PSK 7 09 54 37.0 ...
If coordinates are used, then they should be entered using an astropy.coordinates.SkyCoord
object.
>>> from astroquery.simbad import Simbad
>>> import astropy.coordinates as coord
>>> result_table = Simbad.query_region(coord.SkyCoord("05h35m17.3s -05h23m28s", frame='icrs'), radius='1d0m0s')
>>> print(result_table)
MAIN_ID RA ... COO_BIBCODE
----------------------- ------------- ... -------------------
HD 38875 05 34 59.7297 ... 2007A&A...474..653V
TYC 9390-799-1 05 33 58.2222 ... 1998A&A...335L..65H
TYC 9390-646-1 05 35 02.830 ... 2000A&A...355L..27H
TYC 9390-629-1 05 35 20.419 ... 2000A&A...355L..27H
TYC 9390-857-1 05 30 58.989 ... 2000A&A...355L..27H
TYC 9390-1171-1 05 37 35.9623 ... 1998A&A...335L..65H
TYC 9390-654-1 05 35 27.395 ... 2000A&A...355L..27H
TYC 9390-656-1 05 30 43.665 ... 2000A&A...355L..27H
... ... ... ...
TYC 9373-779-1 05 11 57.788 ... 2000A&A...355L..27H
TYC 9377-513-1 05 10 43.0669 ... 1998A&A...335L..65H
TYC 9386-135-1 05 28 24.988 ... 2000A&A...355L..27H
TYC 9390-1786-1 05 56 34.801 ... 2000A&A...355L..27H
2MASS J05493730-8141270 05 49 37.30 ... 2003yCat.2246....0C
TYC 9390-157-1 05 35 55.233 ... 2000A&A...355L..27H
PKS J0557-8122 05 57 26.80 ... 2003MNRAS.342.1117M
PKS 0602-813 05 57 30.7 ...
>>> from astroquery.simbad import Simbad
>>> import astropy.coordinates as coord
>>> import astropy.units as u
>>> result_table = Simbad.query_region(coord.SkyCoord(31.0087, 14.0627,
... unit=(u.deg, u.deg), frame='galactic'),
... radius='0d0m2s')
>>> print(result_table)
MAIN_ID RA ... COO_WAVELENGTH COO_BIBCODE
------------------- ------------- ... -------------- -------------------
NAME Barnard's star 17 57 48.4980 ... O 2007A&A...474..653V
Two other options can also be specified - the epoch and the equinox. If these are not explicitly mentioned, then the epoch defaults to J2000 and the equinox to 2000.0. So here is a query with all the options utilized:
>>> from astroquery.simbad import Simbad
>>> import astropy.coordinates as coord
>>> import astropy.units as u
>>> result_table = Simbad.query_region(coord.SkyCoord(ra=11.70, dec=10.90,
... unit=(u.deg, u.deg), frame='fk5'),
... radius=0.5 * u.deg,
... epoch='B1950',
... equinox=1950)
>>> print(result_table)
MAIN_ID RA ... COO_BIBCODE
----------------------- ------------- ... -------------------
PHL 6696 00 49.4 ...
BD+10 97 00 49 25.4553 ... 2007A&A...474..653V
TYC 607-238-1 00 48 53.302 ... 2000A&A...355L..27H
PHL 2998 00 49.3 ...
2MASS J00492121+1121094 00 49 21.219 ... 2003yCat.2246....0C
TYC 607-1135-1 00 48 46.5838 ... 1998A&A...335L..65H
2MASX J00495215+1118527 00 49 52.154 ... 2006AJ....131.1163S
BD+10 98 00 50 03.4124 ... 1998A&A...335L..65H
... ... ... ...
TYC 607-971-1 00 47 38.0430 ... 1998A&A...335L..65H
TYC 607-793-1 00 50 35.545 ... 2000A&A...355L..27H
USNO-A2.0 0975-00169117 00 47 55.351 ... 2007ApJ...664...53A
TYC 607-950-1 00 50 51.875 ... 2000A&A...355L..27H
BD+10 100 00 51 15.0789 ... 1998A&A...335L..65H
TYC 608-60-1 00 51 13.314 ... 2000A&A...355L..27H
TYC 608-432-1 00 51 05.289 ... 2000A&A...355L..27H
TYC 607-418-1 00 49 09.636 ... 2000A&A...355L..27H
Query a catalogue¶
Queries can also be formulated to return all the objects from a catalogue. For instance to query the ESO catalog:
>>> from astroquery.simbad import Simbad
>>> limitedSimbad = Simbad()
>>> limitedSimbad.ROW_LIMIT = 6
>>> result_table = limitedSimbad.query_catalog('eso')
>>> print(result_table)
MAIN_ID RA ... COO_WAVELENGTH COO_BIBCODE
----------------------- ------------ ... -------------- -------------------
2MASS J08300740-4325465 08 30 07.41 ... I 2003yCat.2246....0C
NGC 2573 01 41 35.091 ... I 2006AJ....131.1163S
ESO 1-2 05 04 36.8 ... 1982ESO...C......0L
ESO 1-3 05 22 36.509 ... I 2006AJ....131.1163S
ESO 1-4 07 49 28.813 ... I 2006AJ....131.1163S
ESO 1-5 08 53 05.006 ... I 2006AJ....131.1163S
Bibliographic queries¶
Query a bibcode¶
This retrieves the reference corresponding to a bibcode.
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_bibcode('2005A&A.430.165F')
>>> print(result_table)
References
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2005A&A...430..165F -- ?
Astron. Astrophys., 430, 165-186 (2005)
FAMAEY B., JORISSEN A., LURI X., MAYOR M., UDRY S., DEJONGHE H. and TURON C.
Local kinematics of K and M giants from CORAVEL/Hipparcos/Tycho-2 data. Revisiting the concept of superclusters.
Files: (abstract)
Notes: <Available at CDS: tablea1.dat notes.dat>
Wildcards can be used in these queries as well. So to retrieve all the bibcodes from a given journal in a given year:
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_bibcode('2013A&A*', wildcard=True)
>>> print(result_table)
References
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2013A&A...549A...1G -- ?
Astron. Astrophys., 549A, 1-1 (2013)
GENTILE M., COURBIN F. and MEYLAN G.
Interpolating point spread function anisotropy.
Files: (abstract) (no object)
2013A&A...549A...2L -- ?
Astron. Astrophys., 549A, 2-2 (2013)
LEE B.-C., HAN I. and PARK M.-G.
Planetary companions orbiting M giants HD 208527 and HD 220074.
Files: (abstract)
2013A&A...549A...3C -- ?
Astron. Astrophys., 549A, 3-3 (2013)
COCCATO L., MORELLI L., PIZZELLA A., CORSINI E.M., BUSON L.M. and DALLA BONTA E.
Spectroscopic evidence of distinct stellar populations in the counter-rotating stellar disks of NGC 3593 and NGC 4550.
Files: (abstract)
2013A&A...549A...4S -- ?
Astron. Astrophys., 549A, 4-4 (2013)
SCHAERER D., DE BARROS S. and SKLIAS P.
Properties of z ~ 3-6 Lyman break galaxies. I. Testing star formation histories and the SFR-mass relation with ALMA and near-IR spectroscopy.
Files: (abstract)
2013A&A...549A...5R -- ?
Astron. Astrophys., 549A, 5-5 (2013)
RYGL K.L.J., WYROWSKI F., SCHULLER F. and MENTEN K.M.
Initial phases of massive star formation in high infrared extinction clouds. II. Infall and onset of star formation.
Files: (abstract)
2013A&A...549A...6K -- ?
Astron. Astrophys., 549A, 6-6 (2013)
KAMINSKI T., SCHMIDT M.R. and MENTEN K.M.
Aluminium oxide in the optical spectrum of VY Canis Majoris.
Files: (abstract)
Query a bibobj¶
These queries can be used to retrieve all the objects that are contained in the article specified by the bibcode:
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_bibobj('2006AJ....131.1163S')
>>> print(result_table)
MAIN_ID RA DEC RA_PREC DEC_PREC ... COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
"h:m:s" "d:m:s" ... mas deg
----------------------- ------------ ------------ ------- -------- ... ------------ ------------- -------- -------------- -------------------
M 32 00 42 41.825 +40 51 54.61 7 7 ... -- 0 B I 2006AJ....131.1163S
M 31 00 42 44.330 +41 16 07.50 7 7 ... -- 0 B I 2006AJ....131.1163S
NAME SMC 00 52 38.0 -72 48 01 5 5 ... -- 0 D O 2003A&A...412...45P
Cl Melotte 22 03 47 00 +24 07.0 4 4 ... -- 0 E O 2009MNRAS.399.2146W
2MASX J04504846-7531580 04 50 48.462 -75 31 58.08 7 7 ... -- 0 B I 2006AJ....131.1163S
NAME LMC 05 23 34.6 -69 45 22 5 5 ... -- 0 D O 2003A&A...412...45P
NAME Lockman Hole 10 45 00.0 +58 00 00 5 5 ... -- 0 E 2011ApJ...734...99H
NAME Gal Center 17 45 40.04 -29 00 28.1 6 6 ... -- 0 E
Query TAP¶
query_tap (for Table Access Protocol) is the one
query to rule them all. It allows one to access all the information in SIMBAD with the
Astronomical Data Query Language (ADQL). ADQL is a flavor of the Structured
Query Language (SQL) adapted to astronomy. To learn more about this language,
see the ADQL documentation
or the Simbad ADQL cheat sheet.
Structure of an ADQL query¶
The method query_tap is called with a string containing the
ADQL query.
/*ADQL queries start with selecting the columns that will be in the output. Usually,
the column name is sufficient. If there is a need to lift ambiguity, add the table
name first (table_name.column_name). This is also where the number of rows is fixed
(here 5).*/
SELECT TOP 5 basic.ra, basic.dec, main_id, nbref
/*Then comes the declaration of the tables to be included in the query. Here *basic* and
*ident*. Their common column is named *oid* in *basic* and *oidref* in *ident*.*/
FROM basic JOIN ident ON basic.oid = ident.oidref
/*The conditions come after. This query filters otypes that are not in any
cluster of star (Cl*) sub-category (..), specific redshifts, and the results should
have an NGC name in their list of names.*/
WHERE (otype != 'Cl*..') AND (rvz_redshift < 1) AND (id LIKE 'NGC%')
/*The result is then sorted so that the top 5 selected corresponds to
the objects cited by the largest number of papers.*/
ORDER BY nbref DESC
This ADQL query can be called with query_tap:
>>> from astroquery.simbad import Simbad
>>> Simbad.query_tap("""SELECT TOP 5 basic.ra, basic.dec, main_id, nbref
... FROM basic JOIN ident ON basic.oid = ident.oidref
... WHERE (otype != 'Cl*..') AND (rvz_redshift < 1)
... AND (id LIKE 'NGC%')
... ORDER BY nbref DESC""")
<Table length=5>
ra dec main_id nbref
deg deg
float64 float64 object int32
------------------ ------------------ -------- -----
10.684708333333333 41.268750000000004 M 31 12412
13.158333333333333 -72.80027777777778 NAME SMC 10875
187.70593076725 12.391123246083334 M 87 7040
148.96845833333333 69.67970277777778 M 82 5769
23.46206906218 30.660175111980003 M 33 5737
And voilà, we get the 5 NGC objects that are the most cited in literature, are not clusters of stars, and have a redshift < 1. The following sections cover methods that help build ADQL queries. A showcase of more complex queries comes after.
Available tables¶
SIMBAD is a relational database. This means that it is a collection of tables with
links between them. You can access a graphic representation of Simbad’s tables and
their relations or print
the names and descriptions of each table with the
list_tables method:
>>> from astroquery.simbad import Simbad
>>> Simbad.list_tables()
<Table length=30>
table_name description
object object
------------- ----------------------------------------------------------------------------
basic General data about an astronomical object
ids all names concatenated with pipe
alltypes all object types concatenated with pipe
ident Identifiers of an astronomical object
cat Catalogues name
flux Magnitude/Flux information about an astronomical object
allfluxes all flux/magnitudes U,B,V,I,J,H,K,u_,g_,r_,i_,z_
filter Description of a flux filter
has_ref Associations between astronomical objects and their bibliographic references
ref Bibliographic reference
author Author of a bibliographic reference
h_link hierarchy of membership measure
mesHerschel The Herschel observing Log
biblio Bibliography
keywords List of keywords in a paper
mesXmm XMM observing log.
mesVelocities Collection of HRV, Vlsr, cz and redshifts.
mesVar Collection of stellar variability types and periods.
mesRot Stellar Rotational Velocities.
mesPM Collection of proper motions.
mesPLX Collection of trigonometric parallaxes.
otypedef all names and definitions for the object types
mesIUE International Ultraviolet Explorer observing log.
mesISO Infrared Space Observatory (ISO) observing log.
mesFe_h Collection of metallicity, as well as Teff, logg for stars.
mesDiameter Collection of stellar diameters.
mesDistance Collection of distances (pc, kpc or Mpc) by several means.
otypes List of all object types associated with an object
mesSpT Collection of spectral types.
journals Description of all used journals in the database
To join tables, any columns sharing the same name are possible links between tables.
To find the other possible joins, the list_linked_tables method
can be useful. Here we look for possible links with the mesDiameter table
>>> from astroquery.simbad import Simbad
>>> Simbad.list_linked_tables("mesDiameter")
<Table length=1>
from_table from_column target_table target_column
object object object object
----------- ----------- ------------ -------------
mesDiameter oidref basic oid
The output indicates that the mesDiameter table can be linked to basic with the following
join statement: [...] mesDiameter JOIN basic ON mesDiameter.oidref = basic.oid [...].
A quick view of SIMBAD’s tables. Hover the links to see the linked columns.¶
Available columns¶
list_columns lists the columns in all or a subset of SIMBAD tables.
Calling it with no argument returns the 289 columns of SIMBAD. To restrict the output to
some tables, add their name. To get the columns of the tables ref and biblio:
>>> from astroquery.simbad import Simbad
>>> Simbad.list_columns("ref", "biblio")
<Table length=13>
table_name column_name datatype ... unit ucd
object object object ... object object
---------- ----------- ----------- ... ------ --------------------
biblio biblio TEXT ... meta.record;meta.bib
biblio oidref BIGINT ... meta.record;meta.id
ref abstract UNICODECHAR ... meta.record
ref bibcode CHAR ... meta.bib.bibcode
ref doi VARCHAR ... meta.code;meta.bib
ref journal VARCHAR ... meta.bib.journal
ref last_page INTEGER ... meta.bib.page
ref nbobject INTEGER ... meta.number
ref oidbib BIGINT ... meta.record;meta.bib
ref page INTEGER ... meta.bib.page
ref title UNICODECHAR ... meta.title
ref volume INTEGER ... meta.bib.volume
ref year SMALLINT ... meta.note;meta.bib
list_columns can also be called with a keyword argument.
This returns columns from any table for witch the given keyword is either in the table name,
in the column name or in its description. This is not case-sensitive.
>>> from astroquery.simbad import Simbad
>>> Simbad.list_columns(keyword="Radial velocity")
<Table length=9>
table_name column_name ... unit ucd
object object ... object object
------------- --------------- ... ------ -------------------------------------
basic rvz_bibcode ... meta.bib.bibcode;spect.dopplerVeloc
basic rvz_err ... km.s-1 stat.error;spect.dopplerVeloc
basic rvz_err_prec ...
basic rvz_qual ... meta.code.qual;spect.dopplerVeloc
basic rvz_radvel ... km.s-1 spect.dopplerVeloc.opt
basic rvz_radvel_prec ...
basic rvz_type ...
basic rvz_wavelength ... instr.bandpass;spect.dopplerVeloc.opt
mesVelocities origin ... meta.note
Example TAP queries¶
This section lists more complex queries by looking at use cases from former astroquery issues.
Getting all bibcodes containing a certain type of measurement for a given object¶
The measurement tables – the ones with names starting with mes– have a bibcode column
that corresponds to the paper in which the information was found.
This query joins the tables ident to get all possible names of the object and mesrot
that is the measurement table for rotations. Their common column is oidref.
>>> from astroquery.simbad import Simbad
>>> query = """SELECT bibcode AS "Rotation Measurements Bibcodes"
... FROM ident JOIN mesrot USING(oidref)
... WHERE id = 'Sirius';
... """
>>> Simbad.query_tap(query)
<Table length=6>
Rotation Measurements Bibcodes
object
------------------------------
2016A&A...589A..83G
2002A&A...393..897R
1995ApJS...99..135A
1970CoKwa.189....0U
1970CoAsi.239....1B
2011A&A...531A.143D
This returns six papers in which the SIMBAD team found rotation data for Sirius.
Criteria on region, measurements and object types¶
Here we search for objects that are not stars and have a redshift<0.4 in a cone search. All this information
is in the basic column. The star.. syntax refers to any type of star.
>>> from astroquery.simbad import Simbad
>>> query = """SELECT ra, dec, main_id, rvz_redshift, otype
... FROM basic
... WHERE otype != 'star..'
... AND CONTAINS(POINT('ICRS', basic.ra, basic.dec), CIRCLE('ICRS', 331.92, +12.44 , 0.25)) = 1
... AND rvz_redshift <= 0.4"""
>>> Simbad.query_tap(query)
<Table length=11>
ra dec main_id rvz_redshift otype
deg deg
float64 float64 object float64 object
--------------- ------------------ ------------------------ ------------ ------
331.86493815752 12.61105991847 SDSS J220727.58+123639.8 0.11816 EmG
331.80665742545 12.5032406228 SDSS J220713.60+123011.7 0.1477 EmG
332.022027 12.29211 SDSS J220805.28+121731.5 0.12186 G
331.984091 12.573282 SDSS J220756.18+123423.8 0.13824 G
331.87489584192 12.5830568196 SDSS J220729.97+123458.8 0.03129 G
331.77233978222 12.314639195540002 2MASX J22070538+1218523 0.079 G
331.796426 12.426641 SDSS J220711.14+122535.9 0.07886 G
331.68420630414 12.3609942055 2MASX J22064423+1221397 0.1219 G
331.951995 12.431051 SDSS J220748.47+122551.7 0.16484 G
332.171805 12.430204 SDSS J220841.23+122548.7 0.14762 G
332.084711 12.486509 SDSS J220820.33+122911.4 0.12246 G
This returns a few galaxies ‘G’ and emission-line galaxies ‘EmG’.
Get the members of a galaxy cluster¶
All membership information is in the h_link table. We first need to retrieve the oidref
corresponding to the parent cluster SDSSCGB 350. This is done is the sub-query between parenthesis.
Then, the basic table is joined with h_link and the sub-query result.
>>> from astroquery.simbad import Simbad
>>> query = """SELECT main_id AS "child id",
... otype, ra, dec, membership,
... cluster_table.id AS "parent cluster"
... FROM (SELECT oidref, id FROM ident WHERE id = 'SDSSCGB 350') AS cluster_table,
... basic JOIN h_link ON basic.oid = h_link.child
... WHERE h_link.parent = cluster_table.oidref;
... """
>>> Simbad.query_tap(query)
<Table length=7>
child id otype ra ... membership parent cluster
deg ... percent
object object float64 ... int16 object
------------------------ ------ ------------------ ... ---------- --------------
SDSSCGB 350.4 G 243.18303333333336 ... 75 SDSSCGB 350
SDSS J161245.36+281652.4 G 243.18900464937997 ... 75 SDSSCGB 350
SDSSCGB 350.1 G 243.18618110644002 ... 75 SDSSCGB 350
LEDA 1831614 G 243.189153 ... 75 SDSSCGB 350
LEDA 1832284 G 243.187819 ... 100 SDSSCGB 350
SDSSCGB 350.1 G 243.18618110644002 ... 100 SDSSCGB 350
LEDA 1831614 G 243.189153 ... 100 SDSSCGB 350
Query a long list of object¶
To query a list of objects (or coordinates, of bibliographic references), we can use the
ADQL criteria IN like so:
>>> from astroquery.simbad import Simbad
>>> Simbad.query_tap("SELECT main_id, otype FROM basic WHERE main_id IN ('M1', 'M2', 'M3')")
<Table length=3>
main_id otype
object object
------- ------
M 1 SNR
M 2 GlC
M 3 GlC
And that would work perfectly… until we reach the character limit for the ADQL query. This
is one of the example use case where the upload table capability is very useful. You can create/use
an Table containing the desired list and use it in a JOIN to replace an IN:
>>> from astroquery.simbad import Simbad
>>> from astropy.table import Table
>>> list_of_objects = Table([["M1", "M2", "M3"]], names=["Messier_objects"])
>>> query = """SELECT main_id, otype FROM basic
... JOIN TAP_UPLOAD.messiers
... ON basic.main_id = TAP_UPLOAD.messiers.Messier_objects
... """
>>> Simbad.query_tap(query, messiers=list_of_objects)
<Table length=3>
main_id otype
object object
------- ------
M 1 SNR
M 2 GlC
M 3 GlC
Note
The uploaded tables are limited to 200000 lines. You might need to break your query into smaller chunks if you have longer tables.
Query based on any criteria¶
Anything done in SIMBAD’s criteria interface can be done via astroquery. See that link for details of how these queries are formed.
>>> from astroquery.simbad import Simbad
>>> result = Simbad.query_criteria('region(box, GAL, 0 +0, 3d 1d)', otype='SNR')
>>> print(result)
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
--------------------- ----------- ----------- ------- -------- ------------ ------------ ------------- -------- -------------- -------------------
EQ J174702.6-282733 17 47 02.6 -28 27 33 5 5 nan nan 0 D 2002ApJ...565.1017S
[L92] 174535.0-280410 17 48 44.4 -28 05 06 5 5 3000.000 3000.000 0 D
[GWC93] 19 17 42 04.9 -30 04 04 5 5 3000.000 3000.000 1 D
SNR G359.1-00.2 17 43 29 -29 45.9 4 4 nan nan 0 E 2000AJ....119..207L
SNR G000.1-00.2 17 48 42.5 -28 09 11 5 5 nan nan 0 D 2008ApJS..177..255L
SNR G359.9-00.9 17 45.8 -29 03 3 3 nan nan 0
SNR G359.4-00.1 17 44 37 -29 27.2 4 4 18000.000 18000.000 1 E
NAME SGR D 17 48 42 -28 01.4 4 4 18000.000 18000.000 0 E
SNR G359.1-00.5 17 45 25 -29 57.9 4 4 18000.000 18000.000 1 E
NAME SGR D SNR 17 48.7 -28 07 3 3 nan nan 0 E
Suzaku J1747-2824 17 47 00 -28 24.5 4 4 nan nan 0 E 2007ApJ...666..934C
SNR G000.4+00.2 17 46 27.65 -28 36 05.6 6 6 300.000 300.000 1 D
SNR G001.4-00.1 17 49 28.1 -27 47 45 5 5 nan nan 0 D 1999ApJ...527..172Y
GAL 000.61+00.01 17 47.0 -28 25 3 3 nan nan 0 D
SNR G000.9+00.1 17 47.3 -28 09 3 3 nan nan 0 E R 2009BASI...37...45G
SNR G000.3+00.0 17 46 14.9 -28 37 15 5 5 3000.000 3000.000 1 D
SNR G001.0-00.1 17 48.5 -28 09 3 3 nan nan 0 E R 2009BASI...37...45G
NAME SGR A EAST 17 45 47 -29 00.2 4 4 18000.000 18000.000 1 E
Object type criteria¶
SIMBAD sets a maintype for each astronomical object that is related to the real type classification. Other object types (otypes) are given, which are related to some types coming from some surveys/observations. Depending on your needs, maintype or otype fields can be used.
To use all subcategories of an object type, maintypes or otypes fields can also be used.
See the dedicated SIMBAD documentation on object types.
>>> from astroquery.simbad import Simbad
>>> result = Simbad.query_criteria('region(CIRCLE, Trapezium Nebula, 3m)', maintypes='YSO')
>>> print(result)
MAIN_ID RA DEC RA_PREC DEC_PREC ... COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE SCRIPT_NUMBER_ID
----------------------- ------------- ------------- ------- -------- ... ------------- -------- -------------- ------------------- ----------------
* tet01 Ori D 05 35 17.2574 -05 23 16.570 14 14 ... 90 A O 2020yCat.1350....0G 0
* tet01 Ori A 05 35 15.8254 -05 23 14.334 14 14 ... 90 A O 2020yCat.1350....0G 0
V* MR Ori 05 35 16.9783 -05 21 45.337 14 14 ... 90 A O 2020yCat.1350....0G 0
V* V377 Ori 05 35 21.2917 -05 24 57.399 14 14 ... 90 A O 2020yCat.1350....0G 0
V* AF Ori 05 35 18.6664 -05 23 13.946 14 14 ... 90 A O 2020yCat.1350....0G 0
V* V1228 Ori 05 35 12.2788 -05 23 48.027 14 14 ... 90 A O 2020yCat.1350....0G 0
V* V2228 Ori 05 35 12.8166 -05 20 43.608 14 14 ... 90 A O 2020yCat.1350....0G 0
Parenago 1820 05 35 13.5189 -05 22 19.552 14 14 ... 90 A O 2020yCat.1350....0G 0
... ... ... ... ... ... ... ... ... ... ...
HH 998 05 35 16.0 -05 23 54 5 5 ... 0 E 2015AJ....150..108O 0
Parenago 1823 05 35 14.0513 -05 23 38.466 14 14 ... 90 A O 2020yCat.1350....0G 0
2MASS J05351884-0522229 05 35 18.8454 -05 22 22.996 14 14 ... 90 C O 2020yCat.1350....0G 0
[SRB2015] p132 05 35 25.9362 -05 22 24.404 9 9 ... 0 E s 2015MNRAS.449.1769S 0
[SRB2015] p136 05 35 14.3406 -05 22 26.643 9 9 ... 0 E s 2015MNRAS.449.1769S 0
[SRB2015] p142 05 35 25.9653 -05 21 24.460 9 9 ... 0 E s 2015MNRAS.449.1769S 0
[OW94] 183-405 05 35 18.3314 -05 24 04.844 14 14 ... 90 A O 2020yCat.1350....0G 0
[H97b] 511b 05 35 16.2800 -05 22 10.420 8 8 ... 0 C R 2016ApJ...831..155S 0
Vectorized Queries¶
You can query multiple regions at once using vectorized queries. Each region must have the same radius.
>>> from astroquery.simbad import Simbad
>>> import astropy.coordinates as coord
>>> import astropy.units as u
>>> result_table = Simbad.query_region(coord.SkyCoord(ra=[10, 11], dec=[10, 11],
... unit=(u.deg, u.deg), frame='fk5'),
... radius=0.1 * u.deg)
>>> print(result_table)
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
"h:m:s" "d:m:s" mas mas deg
------------------------- ------------- ------------- ------- -------- ------------ ------------ ------------- -------- -------------- -------------------
PLCKECC G118.25-52.70 00 39 55.5 +10 03 42 5 5 -- -- 0 E m 2011A&A...536A...7P
IRAS 00373+0947 00 39 55.6 +10 04 15 5 5 39000.000 29000.000 67 E F 1988NASAR1190....1B
IRAS 00371+0946 00 39 43.1 +10 03 21 5 5 88000.000 32000.000 67 E F 1988NASAR1190....1B
LEDA 1387229 00 43 57.2 +10 58 54 5 5 -- -- 0 D O 2003A&A...412...45P
LEDA 1387610 00 43 50.3 +11 00 32 5 5 -- -- 0 D O 2003A&A...412...45P
LEDA 1386801 00 43 53.1 +10 56 59 5 5 -- -- 0 D O 2003A&A...412...45P
LEDA 1387466 00 43 41.3 +10 59 57 5 5 -- -- 0 D O 2003A&A...412...45P
NVSS J004420+110010 00 44 20.74 +11 00 10.8 6 6 2800.000 1200.000 90 D 1996AJ....111.1945D
SDSS J004340.18+105815.6 00 43 40.1841 +10 58 15.602 14 14 0.207 0.124 90 A O 2018yCat.1345....0G
GALEX 2675641789401008459 00 43 57.698 +10 54 46.15 7 7 -- -- 0 D 2007ApJ...664...53A
SDSS J004422.75+110104.3 00 44 22.753 +11 01 04.34 7 7 -- -- 0 C O 2017A&A...597A..79P
TYC 607-628-1 00 44 05.6169 +11 05 41.195 14 14 0.047 0.033 90 A O 2018yCat.1345....0G
You can do the same based on IDs. If you add the votable field typed_id, a
column showing your input identifier will be added:
>>> from astroquery.simbad import Simbad
>>> Simbad.add_votable_fields('typed_id')
>>> result_table = Simbad.query_objects(["M1", "M2", "M3", "M4"])
>>> print(result_table)
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE TYPED_ID
"h:m:s" "d:m:s" mas mas deg
------- ----------- ----------- ------- -------- ------------ ------------ ------------- -------- -------------- ------------------- --------
M 1 05 34 31.94 +22 00 52.2 6 6 -- -- 0 C R 2011A&A...533A..10L M1
M 2 21 33 27.02 -00 49 23.7 6 6 100.000 100.000 90 C O 2010AJ....140.1830G M2
M 3 13 42 11.62 +28 22 38.2 6 6 200.000 200.000 90 C O 2010AJ....140.1830G M3
M 4 16 23 35.22 -26 31 32.7 6 6 400.000 400.000 90 C O 2010AJ....140.1830G M4
However, note that missing data will result in missing lines:
>>> from astroquery.simbad import Simbad
>>> result_table = Simbad.query_objects(["M1", "notanobject", "m2", "m1000"])
>>> print(result_table)
UserWarning: Warning: The script line number 4 raised an error (recorded in the `errors` attribute of the result table): 'notanobject': No known catalog could be found
(error.line, error.msg))
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
"h:m:s" "d:m:s" mas mas deg
------- ----------- ----------- ------- -------- ------------ ------------ ------------- -------- -------------- -------------------
M 1 05 34 31.94 +22 00 52.2 6 6 -- -- 0 C R 2011A&A...533A..10L
M 2 21 33 27.02 -00 49 23.7 6 6 100.000 100.000 90 C O 2010AJ....140.1830G
Only the results for M1 and M2 are included. As of May 2019, there is a feature request in place with SIMBAD to return blank rows with the queried identifier indicated.
You can also stitch together region queries by writing a sophisticated script:
>>> from astroquery.simbad import Simbad
>>> script = '(region(box, GAL, 0 +0, 0.5d 0.5d) | region(box, GAL, 43.3 -0.2, 0.25d 0.25d))'
>>> result = Simbad.query_criteria(script, otype='SNR')
>>> print(result)
<Table masked=True length=4>
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE
"h:m:s" "d:m:s" mas mas deg
object str13 str13 int16 int16 float32 float32 int16 str1 str1 object
----------------- ------------ ------------ ------- -------- ------------ ------------ ------------- -------- -------------- -------------------
SNR G359.9-00.9 17 45.8 -29 03 3 3 -- -- 0
NAME Sgr A East 17 45 41 -29 00.8 4 4 -- -- 0 D 2010ApJS..188..405A
W 49b 19 11 09.000 +09 06 24.00 7 7 -- -- 0 D 2015ApJS..217....2M
SNR G000.13-00.12 17 46.4 -28 53 3 3 -- -- 0 E 2013MNRAS.434.1339H
Customizing the default settings¶
There may be times when you wish to change the defaults that have been set for the Simbad queries.
Changing the row limit¶
To fetch all the rows in the result, the row limit must be set to 0. However for some queries, results are likely to be very large, in such cases it may be best to limit the rows to a smaller number. If you want to do this only for the current python session then:
>>> from astroquery.simbad import Simbad
>>> Simbad.ROW_LIMIT = 15 # now any query fetches at most 15 rows
If you would like to make your choice persistent, then you can do this by modifying the setting in the Astroquery configuration file.
Changing the timeout¶
The timeout is the time limit in seconds for establishing connection with the Simbad server and by default it is set to 100 seconds. You may want to modify this - again you can do this at run-time if you want to adjust it only for the current session. To make it persistent, you must modify the setting in the Astroquery configuration file.
>>> from astroquery.simbad import Simbad
>>> Simbad.TIMEOUT = 60 # sets the timeout to 60s
Specifying which VOTable fields to include in the result¶
The VOTable fields that are currently returned in the result are set to
main_id and coordinates. However you can specify other fields that you
also want to be fetched in the result. To see the list of the fields:
>>> from astroquery.simbad import Simbad
>>> Simbad.list_votable_fields()
col0 col1 col2
------------------------ -------------------- --------------
bibcodelist(y1-y2) fluxdata(filtername) plx_qual
cel gcrv pm
cl.g gen pm_bibcode
coo(opt) gj pm_err_angle
coo_bibcode hbet pm_err_maja
coo_err_angle hbet1 pm_err_mina
coo_err_maja hgam pm_qual
The above shows just a small snippet of the table that is returned and has all the fields sorted lexicographically column-wise. For more information on a particular field:
>>> from astroquery.simbad import Simbad
>>> Simbad.get_field_description('ra_prec')
right ascension precision code (0:1/10deg, ..., 8: 1/1000 arcsec)
To set additional fields to be returned in the VOTable:
>>> from astroquery.simbad import Simbad
>>> customSimbad = Simbad()
# see which fields are currently set
>>> customSimbad.get_votable_fields()
['main_id', 'coordinates']
# To set other fields
>>> customSimbad.add_votable_fields('mk', 'rot', 'bibcodelist(1800-2014)')
>>> customSimbad.get_votable_fields()
['main_id', 'coordinates', 'mk', 'rot', 'bibcodelist(1800-2014')]
You can also remove a field you have set or
astroquery.simbad.SimbadClass.reset_votable_fields(). Continuing from
the above example:
>>> customSimbad.remove_votable_fields('mk', 'coordinates')
>>> customSimbad.get_votable_fields()
['main_id', 'rot', 'bibcodelist(1800-2014)']
# reset back to defaults
>>> customSimbad.reset_votable_fields()
>>> customSimbad.get_votable_fields()
['main_id', 'coordinates']
Returning the queried name in the return table¶
You can include the name(s) queried in the output table by adding typed_id to
the votable fields. This was also mentioned in vectorized queries above, but we emphasize here that it works for all queries.
>>> Simbad.add_votable_fields('typed_id')
>>> Simbad.query_objects(['M31', 'Eta Carinae', 'Alpha Centauri'])
<Table masked=True length=3>
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE TYPED_ID
"h:m:s" "d:m:s" mas mas deg
object str13 str13 int16 int16 float32 float32 int16 str1 str1 object object
--------- ------------- ------------- ------- -------- ------------ ------------ ------------- -------- -------------- ------------------- --------------
M 31 00 42 44.330 +41 16 07.50 7 7 -- -- 0 C I 2006AJ....131.1163S M31
+ eta Car 10 45 03.5455 -59 41 03.951 11 11 11.000 10.000 90 B O 2000A&A...355L..27H Eta Carinae
+ alf Cen 14 39 29.7199 -60 49 55.999 9 9 -- -- 0 C O 2016A&A...589A.115S Alpha Centauri
>>> Simbad.query_object('M31')
<Table masked=True length=1>
MAIN_ID RA DEC RA_PREC DEC_PREC COO_ERR_MAJA COO_ERR_MINA COO_ERR_ANGLE COO_QUAL COO_WAVELENGTH COO_BIBCODE TYPED_ID
"h:m:s" "d:m:s" mas mas deg
object str13 str13 int16 int16 float32 float32 int16 str1 str1 object object
------- ------------ ------------ ------- -------- ------------ ------------ ------------- -------- -------------- ------------------- --------
M 31 00 42 44.330 +41 16 07.50 7 7 -- -- 0 C I 2006AJ....131.1163S M31
Specifying the format of the included VOTable fields¶
The output for several of the VOTable fields can be formatted in many different ways described in the help page of the SIMBAD query interface (see Sect. 4.3 of this page). As an example, the epoch and equinox for the Right Ascension and Declination can be specified as follows (e.g. epoch of J2017.5 and equinox of 2000):
>>> customSimbad.add_votable_fields('ra(2;A;ICRS;J2017.5;2000)', 'dec(2;D;ICRS;J2017.5;2000)')
>>> customSimbad.remove_votable_fields('coordinates')
>>> customSimbad.query_object("HD189733")
<Table masked=True length=1>
MAIN_ID RA_2_A_ICRS_J2017_5_2000 DEC_2_D_ICRS_2017_5_2000
"h:m:s" "d:m:s"
object str13 str13
--------- ------------------------ ------------------------
HD 189733 20 00 43.7107 +22 42 39.064
Troubleshooting¶
If you are repeatedly getting failed queries, or bad/out-of-date results, try clearing your cache:
>>> from astroquery.simbad import Simbad
>>> Simbad.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¶
astroquery.simbad Package¶
SIMBAD Query Tool¶
The SIMBAD query tool creates a script query that returns VOtable XML
data that is then parsed into a SimbadResult object. This object then
parses the data and returns a table parsed with astropy.io.votable.parse.
Classes¶
The class for querying the Simbad web service. |
|
SimbadBaseQuery overloads the base query because we know that SIMBAD will sometimes blacklist users for exceeding rate limits. |
|
|
Configuration parameters for |