ESASky Queries (`astroquery.esasky`)¶

Getting started¶

This is a python interface for querying the ESASky web service. This module supports cone searches and download of data products from all missions available in ESASky. You can also use the ESASky Solar System Object crossmatch methods to get all observations (both targeted and serendipitous) of a solar system object.

There are 4 categories of methods, based on the type of data: catalogs, observations, spectra, and SSO. Documentation on the ESASky web service can be found here.

Get the available catalog names¶

If you know the names of all the available catalogs you can use list_catalogs():

>>> from astroquery.esasky import ESASky
>>> catalog_list = ESASky.list_catalogs()
>>> print(catalog_list)
['LAMOST', 'AllWise', 'AKARI-IRC-SC', 'TwoMASS', 'INTEGRAL', 'CHANDRA-SC2', 'XMM-EPIC-STACK', 'XMM-EPIC', 'XMM-OM',
'XMM-SLEW', 'Tycho-2', 'Gaia-eDR3', 'Hipparcos-2', 'HSC', 'Herschel-HPPSC-070', 'Herschel-HPPSC-100',
'Herschel-HPPSC-160', 'Herschel-SPSC-250', 'Herschel-SPSC-350', 'Herschel-SPSC-500', 'Planck-PGCC',
'Planck-PCCS2E-HFI', 'Planck-PCCS2-HFI', 'Planck-PCCS2-LFI', 'Planck-PSZ2']

Get the available maps mission names¶

If you know the names of all the available maps missions you can use list_maps():

>>> maps_list = ESASky.list_maps()
>>> print(maps_list)
['INTEGRAL', 'XMM', 'Chandra', 'SUZAKU', 'XMM-OM-OPTICAL', 'XMM-OM-UV', 'HST-UV', 'HST-OPTICAL', 'HST-IR', 'ISO-IR',
'Herschel', 'AKARI', 'Spitzer', 'ALMA']

Get the available spectra mission names¶

If you know the names of all the available spectra you can use list_spectra():

>>> spectra_list = ESASky.list_spectra()
>>> print(spectra_list)
['XMM-NEWTON', 'Chandra', 'IUE', 'HST-UV', 'HST-OPTICAL', 'HST-IR', 'ISO-IR', 'Herschel', 'LAMOST']

Get the available SSO mission names¶

If you know the names of all the available missions with SSO cross match data, you can use list_sso():

>>> sso_list = ESASky.list_sso()
>>> print(sso_list)
['Herschel', 'HST', 'XMM']

Query an object¶

There are three very similar query objects methods in this module query_object_catalogs(), query_object_maps(), and query_object_spectra(). There is also a method for querying SSO object query_sso() which is covered in its own section further down.

For catalogs, the query returns a maximum of 10000 sources per mission by default. However, this can be modified by the row_limit parameter. You can set the parameter to -1, which will result in the maximum number of sources (currently 100 000). To account for observation errors, this method will search for any sources within 5 arcsec from the object.

For instance to query an object around M51 in the Hubble catalog:

>>> from astroquery.esasky import ESASky
>>> result = ESASky.query_object_catalogs(position="M51", missions="HSC")

Note that the catalog may also be specified as a list. So the above query may also be written as:

>>> result = ESASky.query_object_catalogs(position="M51", missions=["HSC", "XMM-OM"])

To search in all available catalogs you can write "all" instead of a catalog name. The same thing will happen if you don’t write any catalog name.

>>> result = ESASky.query_object_catalogs(position="M51", missions="all")
>>> result = ESASky.query_object_catalogs(position="M51")

To see the result:

>>> print(result)
TableList with 9 tables:
    '0:ALLWISE' with 13 column(s) and 1 row(s)
    '1:TWOMASS' with 9 column(s) and 3 row(s)
    '2:CHANDRA-SC2' with 41 column(s) and 9 row(s)
    '3:XMM-EPIC-STACK' with 13 column(s) and 1 row(s)
    '4:XMM-EPIC' with 14 column(s) and 11 row(s)
    '5:XMM-OM' with 11 column(s) and 5 row(s)
    '6:HSC' with 9 column(s) and 230 row(s)
    '7:HERSCHEL-HPPSC-070' with 15 column(s) and 1 row(s)
    '8:HERSCHEL-HPPSC-100' with 15 column(s) and 1 row(s)

All the results are returned as a TableList object. This is a container for Table objects. It is basically an extension to OrderedDict for storing a Table against its name.

To access an individual table from the TableList object

>>> interesting_table = result['ALLWISE']
>>> print(interesting_table)
        name             ra        dec     ... w3mpro_error w4mpro w4mpro_error
                        deg        deg     ...     mag       mag       mag
------------------- ----------- ---------- ... ------------ ------ ------------
J132952.72+471142.6 202.4696996 47.1951717 ...        0.023  3.386        0.036

To do some common processing to all the tables in the returned TableList object, you can just use a for loop:

>>> for table in result:
...     colnames = table.colnames
...     # table is now an `astropy.table.Table` object
...     # some code to apply on table

As mentioned earlier, astroquery.esasky.ESASkyClass.query_object_maps() and astroquery.esasky.ESASkyClass.query_object_spectra() works extremely similar. It will return all maps or spectra that contain the chosen object or coordinate. To execute the same command as above you write this:

>>> result = ESASky.query_object_maps(position="M51", missions="all")
>>> result = ESASky.query_object_spectra(position="M51", missions="all")

The parameters are interchangeable in the same way as in query_object_catalogs().

Query a region¶

The region queries work in a similar way as query_object, except that you must choose a radius as well. There are three query region methods in this module astroquery.esasky.ESASkyClass.query_region_catalogs(), astroquery.esasky.ESASkyClass.query_region_maps(), and astroquery.esasky.ESASkyClass.query_region_spectra(). The row_limit parameter can be set to choose the maximum number of row to be selected. If this parameter is not set, the method will return the first 10000 sources. You can set the parameter to -1, which will result in the maximum number of sources (currently 100 000).

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 of the region. For instance to query region around M51 in the HSC catalog:

>>> from astroquery.esasky import ESASky
>>> import astropy.units as u
>>> result = ESASky.query_region_catalogs(position="M51", radius=10 * u.arcmin, catalogs="HSC")

Note that the catalog may also be specified as a list. So the above query may also be written as:

>>> result = ESASky.query_region_catalogs(position="M51", radius=10 * u.arcmin, catalogs=["HSC", "XMM-OM"])

To search in all available catalogs you can write "all" instead of a catalog name. The same thing will happen if you don’t write any catalog name.

>>> result = ESASky.query_region_catalogs(position="M51", radius=10 * u.arcmin, catalogs="all")
>>> result = ESASky.query_region_catalogs(position="M51", radius=10 * u.arcmin)

In the same manner, the radius can be specified with either a string or any Quantity

>>> result = ESASky.query_region_catalogs(position="M51", radius="10 arcmin")

To see the result:

>>> print(result)
TableList with 18 tables:
    '0:LAMOST' with 21 column(s) and 41 row(s)
    '1:ALLWISE' with 13 column(s) and 1762 row(s)
    '2:AKARI-IRC-SC' with 13 column(s) and 1 row(s)
    '3:TWOMASS' with 9 column(s) and 188 row(s)
    '4:CHANDRA-SC2' with 41 column(s) and 430 row(s)
    '5:XMM-EPIC-STACK' with 13 column(s) and 214 row(s)
    '6:XMM-EPIC' with 14 column(s) and 823 row(s)
    '7:XMM-OM' with 11 column(s) and 4849 row(s)
    '8:XMM-SLEW' with 9 column(s) and 2 row(s)
    '9:GAIA-EDR3' with 20 column(s) and 932 row(s)
    '10:HSC' with 9 column(s) and 10000 row(s)
    '11:HERSCHEL-HPPSC-070' with 15 column(s) and 93 row(s)
    '12:HERSCHEL-HPPSC-100' with 15 column(s) and 122 row(s)
    '13:HERSCHEL-HPPSC-160' with 15 column(s) and 93 row(s)
    '14:HERSCHEL-SPSC-250' with 16 column(s) and 59 row(s)
    '15:HERSCHEL-SPSC-350' with 16 column(s) and 24 row(s)
    '16:HERSCHEL-SPSC-500' with 16 column(s) and 7 row(s)
    '17:PLANCK-PCCS2-HFI' with 8 column(s) and 8 row(s)

You can use, query_region_maps() and query_region_maps() with the same parameters. To execute the same command as above you write this:

>>> result = ESASky.query_region_maps(position="M51", radius=10 * u.arcmin, missions="all")
>>> result = ESASky.query_region_spectra(position="M51", radius=10 * u.arcmin, missions="all")

The parameters are interchangeable in the same way as in query_region_catalogs().

Get the metadata of specific observations or sources¶

If you already know the observation ID’s or source names of interest, you can get their related metadata directly with query_ids_maps(), or query_ids_catalogs(), or query_ids_spectra()

>>> maps = ESASky.query_ids_maps(observation_ids=["lbsk03vbq", "ieag90010"], missions="HST-UV")
>>> catalogs = ESASky.query_ids_catalogs(source_ids=["2CXO J090341.1-322609", "2CXO J090353.8-322642",
                                                     "44899", "45057"], catalogs=["CHANDRA-SC2", "Hipparcos-2"])
>>> spectra = ESASky.query_ids_spectra(observation_ids="0001730501")

If you already know which missions you are interested in, it is recommended to explicitly mention them in the mission parameter. Otherwise, ESASky will search through all missions for the ID’s, which also works, but is a little bit slower.

Get images¶

You can either fetch images around the specified target or coordinates, or fetch images from a list of observation ID’s. When a target name is used rather than the coordinates, this will be resolved to coordinates using astropy name resolving methods that utilize online services like SESAME. Coordinates may be entered using the suitable object from astropy.coordinates.

The method returns a dict to separate the different missions. All mission except Herschel returns a list of HDUList. For Herschel each item in the list is a dictionary where the used filter is the key and the HDUList is the value.

>>> from astroquery.esasky import ESASky
>>> images = ESASky.get_images(position="m51", radius="20 arcmin", missions=['Herschel', 'ISO-IR'])
Starting download of HERSCHEL data. (25 files)
Downloading Observation ID: 1342188589 from http://archives.esac.esa.int/hsa/whsa-tap-server/data?RETRIEVAL_TYPE=STANDALONE&observation_oid=8618001&DATA_RETRIEVAL_ORIGIN=UI [Done]
Downloading Observation ID: 1342188328 from http://archives.esac.esa.int/hsa/whsa-tap-server/data?RETRIEVAL_TYPE=STANDALONE&observation_oid=8637833&DATA_RETRIEVAL_ORIGIN=UI
...

>>> print(images)
{
'HERSCHEL': [{'70': [HDUList], '160': HDUList}, {'70': HDUList, '160': HDUList}, ...],
'ISO' : [HDUList, HDUList, HDUList, HDUList, ...]
...
}

As mentioned above, you can also download a images from a list of observation ID’s. To do that you just have to use the parameter observation_id instead of target and position.

>>> from astroquery.esasky import ESASky
>>> images = ESASky.get_images(position="m51", radius="20 arcmin", missions=['Herschel', 'ISO-IR'])

Note that the fits files also are stored to disk. By default they are saved to the working directory but the location can be chosen by the download_dir parameter:

>>> images = ESASky.get_images(observation_ids="100001010", missions="SUZAKU")
>>> images = ESASky.get_images(observation_ids=["100001010", "01500403"], missions=["SUZAKU", "ISO-IR"])

Get maps¶

You can also fetch images using astroquery.esasky.ESASkyClass.get_maps(). It works exactly as astroquery.esasky.ESASkyClass.get_images() except that it takes a TableList instead of position, radius and missions.

>>> table_list = ESASky.query_region_maps(position="m51", radius="20 arcmin", missions=['Herschel', 'ISO-IR'])
>>> images = ESASky.get_maps(query_table_list=table_list, download_dir="/home/user/esasky")

This example is equivalent to:

>>> images = ESASky.get_images(position="m51", radius="20 arcmin", missions=['Herschel', 'ISO-IR'],
...                            download_dir="/home/user/esasky")

Get spectra¶

There are also two methods to download spectra: astroquery.esasky.ESASkyClass.get_spectra() and astroquery.esasky.ESASkyClass.get_spectra_from_table(). These two methods use the same parameters as astroquery.esasky.ESASkyClass.get_maps() and astroquery.esasky.ESASkyClass.get_images() respectively.

The methods returns a dict to separate the different missions. All mission except Herschel returns a list of HDUList. Herschel returns a three-level dictionary.

>>> from astroquery.esasky import ESASky
>>> spectra = ESASky.get_spectra(position="m51", radius="20 arcmin", missions=['Herschel', 'XMM-NEWTON'])
>>> spectra = ESASky.get_spectra(observation_ids=["02101201", "z1ax0102t"], missions=["ISO-IR", "HST-UV"])

or

>>> table_list = ESASky.query_region_spectra(position="m51", radius="20 arcmin",
...                                          missions=['Herschel', 'XMM-NEWTON'])
>>> spectra = ESASky.get_spectra_from_table(query_table_list=table_list, download_dir="/home/user/esasky")

The return value is structured in a dictionary like this:

dict: {
'HERSCHEL': {'1342211195': {'red' : {'HPSTBRRS' : HDUList}, 'blue' : {'HPSTBRBS': HDUList},
    '1342180796': {'WBS' : {'WBS-H_LSB_5a' : HDUList}, 'HRS' : {'HRS-H_LSB_5a': HDUList},
    ...},
'HST-IR':[HDUList, HDUList, HDUList, HDUList, HDUList, ...],
'XMM-NEWTON' : [HDUList, HDUList, HDUList, HDUList, ...]
...
}

Here is another example for Herschel, since it is a bit special:

>>> from astroquery.esasky import ESASky
>>> result = ESASky.query_region_spectra(position='M51', radius='1arcmin', missions=['HERSCHEL'])
>>> herschel_result = result['HERSCHEL']
>>> herschel_result['observation_id', 'target_name', 'instrument', 'observing_mode_name', 'band', 'duration'].pprint()
>>> spectra = ESASky.get_spectra_from_table(query_table_list=[('HERSCHEL', herschel_result)], download_dir='Spectra_new')
>>> spectra['HERSCHEL']['1342211195']['red'].keys()
>>> spectra['HERSCHEL']['1342211195']['red']['HPSTBRRS'].info()

Solar System Object Crossmatch¶

ESASky has a solar system object crossmatch feature which performs a crossmatch on the SSO orbits against the entire mission archives to find observations in which the SSO fell within the imaging instrument’s field of view during the time the images were being taken. Read more about the ESASky SSO feature You can access the results of this crossmatch by using astroquery.esasky.ESASkyClass.query_sso() which works like the other query methods, but it takes an SSO name as input instead of a position.

>>> from astroquery.esasky import ESASky
>>> result = ESASky.query_sso(sso_name="Pallas", missions=["XMM", "HST"])

In some cases an SSO name is ambiguous, in which case you may need to use a more precise SSO name or specify the SSO type of the desired object. For example:

>>> from astroquery.esasky import ESASky
>>> ESASky.query_sso(sso_name="503")
INFO: Found 4 SSO's with name: 503.
Try narrowing your search by typing a more specific sso_name.
You can also narrow your search by specifying the sso_type.
Allowed values are ALL, ASTEROID, COMET, SATELLITE, PLANET, DWARF_PLANET, SPACECRAFT, SPACEJUNK, EXOPLANET, STAR.
The following SSO's were found:
{'aliases': ['503', 'J-3', 'J-III'], 'sso_name': 'Ganymede', 'sso_type': 'SATELLITE'}
{'aliases': [], 'sso_name': 'TOI-503 b', 'sso_type': 'EXOPLANET'}
{'aliases': [], 'sso_name': 'Wolf 503 b', 'sso_type': 'EXOPLANET'}
{'aliases': ['00503', '1899 GA', '1903 BL', '1948 BA', '1948 DA', '2000503', '503', 'I99G00A', 'J03B00L', 'J48B00A', 'J48D00A'], 'sso_name': 'Evelyn', 'sso_type': 'ASTEROID'}

In this case, you can specify the sso_type

>>> from astroquery.esasky import ESASky
>>> ESASky.query_sso(sso_name="503", sso_type="SATELLITE")

You can see the available missions with:

>>> from astroquery.esasky import ESASky
>>> ESASky.list_sso()

Other parameters and the return value are structured in the same manner as the other query methods.

You can also download the observation for a given SSO with astroquery.esasky.ESASkyClass.get_images_sso(). This function works very similar to astroquery.esasky.ESASkyClass.get_images() and astroquery.esasky.ESASkyClass.get_maps(), as it structures the return values in the same way, and most parameters are the same. You can for example, download a table list just like in get_maps by doing something like this:

>>> from astroquery.esasky import ESASky
>>> table_list_from_query_maps=ESASky.query_sso(sso_name="ganymede", missions="XMM")
>>> table_list_from_query_maps['XMM'].remove_rows(list(range(0, 32)))
>>> images=ESASky.get_images_sso(table_list=table_list_from_query_maps)

Or download everything on an SSO by something like this:

>>> from astroquery.esasky import ESASky
>>> images=ESASky.get_images_sso(sso_name="ganymede")

This module also offers access to IMCCE’s SsODNet resolver, which allows you to find solar and extra solar system objects with a given name. Here you can see all matches and there aliases and types. You can use this method to help you specify which SSO you are after. Use astroquery.esasky.ESASkyClass.find_sso() like this:

>>> from astroquery.esasky import ESASky
>>> list_of_matches=ESASky.find_sso(sso_name="Io")

Reference/API¶

astroquery.esasky Package¶

Classes¶

`ESASkyClass`([tap_handler])
`Conf`()	Configuration parameters for `astroquery.esasky`.

Navigation

ESASky Queries (astroquery.esasky)¶