Observations - Cone Search

In the simplest case, archive queries can be performed using a positional (cone) search, which returns all data products within a given angular radius around a specified sky position. This approach is particularly useful when searching for reduced (Phase 3) data products around well-known targets or regions on the sky.

Note

This is typically done within the astroquery using the query_region or query_object methods. However, these methods are not yet implemented for astroquery.eso. Instead, cone searches can be performed by passing the appropriate parameters to the existing query methods, such as query_surveys(), query_instrument(), and query_main().

Query for Reduced Data

This example demonstrates how to perform a basic cone search for publicly available HAWK-I reduced data products around the Galactic Center (Sgr A*) using query_surveys(). Sgr A* is located at right ascension 266.41683° and declination –29.00781°. We perform a search within a 0.05-degree radius (~3 arcminutes).

>>> import astropy.units as u
>>> ra = 266.41683 *u.deg # degrees
>>> dec = -29.00781 *u.deg # degrees
>>> radius = 0.05 *u.deg # degrees

If coordinates are not known, you can use the SkyCoord class to create them. Here, we create a SkyCoord object for Sgr A*.

>>> from astropy.coordinates import SkyCoord
>>> coords = SkyCoord.from_name("Sgr A*")
>>> ra = coords.ra
>>> dec = coords.dec
>>> radius = 0.05 *u.deg

With the defined coordinates and radius, we can now perform the cone search using query_surveys(). This method allows us to filter results based on specific columns, such as instrument_name.

>>> from astroquery.eso import Eso
>>> eso = Eso()

>>> table = eso.query_surveys(
...             cone_ra=ra.value,
...             cone_dec=dec.value,
...             cone_radius=radius.to(u.deg).value,
...             column_filters={"instrument_name": "HAWKI"}
...                           )

Note that cone_ra, cone_dec, and cone_radius parameters are specified in degrees, but as float values (so we use .value to extract the float from the astropy.units.Quantity).

Query for Raw Data

Similar cone search functionality is also available through query_instrument() and query_main() by passing the same cone_ra, cone_dec, and cone_radius arguments.

Instrument-Specific Cone Search

Cone search for raw data products can be performed using the instrument-specific method, such as query_instrument(). This example searches for HAWK-I raw data products around the same coordinates as above.

>>> table = eso.query_instrument(
...             "HAWKI",
...             cone_ra=ra.value,
...             cone_dec=dec.value,
...             cone_radius=radius.to(u.deg).value
...                           )

Generic Cone Search

Cone search for raw data products can also be performed using the more generic method, query_main(). This allows you to search across all instruments without specifying one, with the following example searching for HAWK-I raw data products around the same coordinates as above.

>>> table = eso.query_main(
...             "HAWKI",
...             cone_ra=ra.value,
...             cone_dec=dec.value,
...             cone_radius=radius.to(u.deg).value
...                           )

Download Data

To download the data returned by the query, you can use the retrieve_data() method. This method takes a list of data product IDs (dp_id) and downloads the corresponding files from the ESO archive.

>>> eso.retrieve_data(table["dp_id"])

The data_files list points to the decompressed dataset filenames that have been locally downloaded. The default location of the decompressed datasets can be adjusted by providing a destination keyword in the call to retrieve_data().

>>> data_files = eso.retrieve_data(table["dp_id"], destination="./eso_data/")