Mission Searches¶
Mission-Specific Search Queries¶
These queries allow for searches based on mission-specific metadata for a given data collection. Currently, it provides access to a broad set of Hubble Space Telescope (HST) and James Webb Space Telescope (JWST) metadata, including header keywords, proposal information, and observational parameters.
Note: This API interface does not yet support data product downloads, only metadata search access.
An object of the MastMissions class is instantiated with a default mission of 'hst' and
default service set to 'search'. The searchable metadata for Hubble encompasses all information that
was previously accessible through the original HST web search form and is now available in
the current MAST HST Search Form.
>>> from astroquery.mast import MastMissions
>>> missions = MastMissions()
>>> missions.mission
'hst'
>>> missions.service
'search'
To search for JWST metadata, a MastMissions object is instantiated with a value of 'jwst' for mission.
The searchable metadata for Webb encompasses all information that is available in
the current MAST JWST Search Form.
>>> from astroquery.mast import MastMissions
>>> missions = MastMissions(mission='jwst')
>>> missions.mission
'jwst'
The missions object can be used to search metadata by object name, sky position, or other criteria.
When writing queries, keyword arguments can be used to specify output characteristics and filter on
values like instrument, exposure type, and principal investigator. The available column names for a
mission are returned by the get_column_list function.
>>> from astroquery.mast import MastMissions
>>> missions = MastMissions(mission='hst')
>>> columns = missions.get_column_list()
Metadata queries can be performed on a particular region in the sky. Passing in a set of coordinates to the
query_region function returns datasets that fall within a
certain radius value of that point. This type of search is also known as a cone search.
The select_cols keyword argument specifies a list of columns to be included in the response.
The sort_by keyword argument specifies a column (or columns) to sort the results by.
>>> from astroquery.mast import MastMissions
>>> from astropy.coordinates import SkyCoord
>>> missions = MastMissions(mission='hst')
>>> regionCoords = SkyCoord(210.80227, 54.34895, unit=('deg', 'deg'))
>>> results = missions.query_region(regionCoords,
... radius=3,
... sci_pep_id=12556,
... select_cols=["sci_stop_time", "sci_targname", "sci_start_time", "sci_status"],
... sort_by=['sci_targname'])
>>> results[:5]
<Table masked=True length=5>
search_pos sci_data_set_name sci_targname sci_start_time sci_stop_time ang_sep sci_status
------------------ ----------------- ---------------- -------------------------- -------------------------- -------------------- ----------
210.80227 54.34895 OBQU01050 NUCLEUS+HODGE602 2012-05-24T07:51:40.553000 2012-05-24T07:54:46.553000 0.017460048037303017 PUBLIC
210.80227 54.34895 OBQU010H0 NUCLEUS+HODGE602 2012-05-24T09:17:38.570000 2012-05-24T09:20:44.570000 0.017460048037303017 PUBLIC
210.80227 54.34895 OBQU01030 NUCLEUS+HODGE602 2012-05-24T07:43:20.553000 2012-05-24T07:46:26.553000 0.022143836477276503 PUBLIC
210.80227 54.34895 OBQU010F0 NUCLEUS+HODGE602 2012-05-24T09:09:18.570000 2012-05-24T09:12:24.570000 0.022143836477276503 PUBLIC
210.80227 54.34895 OBQU01070 NUCLEUS+HODGE602 2012-05-24T08:00:00.553000 2012-05-24T08:03:06.553000 0.04381046755938432 PUBLIC
You may notice that the above query returned more columns than were specified in the select_cols
argument. For each mission, certain columns are automatically returned.
HST: For positional searches, the columns
ang_sep,sci_data_set_name, andsearch_posare always included in the query results. For non-positional searches,sci_data_set_nameis always present.JWST: For every query, the
ArchiveFileIDcolumn is always returned.
Searches can also be run on target names with the query_object
function.
>>> results = missions.query_object('M101',
... radius=3,
... select_cols=["sci_stop_time", "sci_targname", "sci_start_time", "sci_status"],
... sort_by=['sci_targname'])
>>> results[:5]
<Table masked=True length=5>
search_pos sci_data_set_name sci_targname sci_start_time sci_stop_time ang_sep sci_status
------------------ ----------------- ------------ -------------------------- -------------------------- ------------------ ----------
210.80243 54.34875 LDJI01010 +164.6+9.9 2019-02-19T00:49:58.010000 2019-02-19T05:52:40.020000 2.7469653000840397 PUBLIC
210.80243 54.34875 J8OB02011 ANY 2003-08-27T07:44:47.417000 2003-08-27T08:27:34.513000 0.8111299061221189 PUBLIC
210.80243 54.34875 J8D711J1Q ANY 2003-01-17T00:42:06.993000 2003-01-17T00:50:22.250000 1.1297984178946574 PUBLIC
210.80243 54.34875 JD6V01012 ANY 2017-06-15T18:10:12.037000 2017-06-15T18:33:25.983000 1.1541053362381077 PUBLIC
210.80243 54.34875 JD6V01013 ANY 2017-06-15T19:45:30.023000 2017-06-15T20:08:44.063000 1.15442580192948 PUBLIC
For non-positional metadata queries, use the query_criteria
function. For paging through results, the offset and limit keyword arguments can be used
to specify the starting record and the number of returned records. The default values for offset
and limit are 0 and 5000, respectively.
>>> results = missions.query_criteria(sci_start_time=">=2021-01-01 00:00:00",
... select_cols=["sci_stop_time", "sci_targname", "sci_start_time", "sci_status", "sci_pep_id"],
... sort_by=['sci_pep_id'],
... limit=1000,
... offset=1000)
... # MaxResultsWarning('Maximum results returned, may not include all sources within radius.')
>>> len(results)
1000