Working with SEDs

Performing an SED Query

To perform an SED query and plot the result:

from ATK import query

sed_query = query("sed", targets=587316166180416640, path="example_sed.fits.gz")
sed_query.show(show_types=True)
sed_query.open()

<SED DataSet>

.kind (str):        SED
.targets (list):    587316166180416640 | 141.185° 8.031° (icrs, 2016-01-01T00:00:00.000, 3.0″)
.exception (bool):  False
.data (list):
          <Spectral Energy Distribution>
                    survey (numpy.ndarray):        [gaia, gaia, ..., galex, galex]
                    correction (numpy.ndarray):    [full, full, ..., full, full]
                    band (numpy.ndarray):          [Gmag, BPmag, ..., FUVmag, NUVmag]
                    id (numpy.ndarray):            [587316166180416640, 587316166180416640, ..., 6377741628902215075, 6377741628902215075]
                    separation (astropy.Quantity): [nan, nan, ..., 1.087, 1.087] ″
                    wavelength (astropy.Quantity): [5822.39, 5035.75, ..., 1535.08, 2300.78] Å
                    flux (astropy.Quantity):       [0.101, 0.078, ..., 0.048, 0.055] mJy
                    flux_err (astropy.Quantity):   [0.003, 0.008, ..., 0.005, 0.004] mJy


Available Methods: .add(), .apply(), .from_target(), .merge(), .open(), .plot(), .save(), .show(), .split(), .store()

The returned DataSet’s data attribute is a list of SED objects (one per target, subject to data availability). Each SED contains all retrieved photometry within the search radius.

Note

SEDs are generated using photometry from the following surveys:

• GAIA

• 2MASS

• WISE

• Pan-STARRS

• SDSS

• SkyMapper

• GALEX

For a refresher on query() fundamentals, see here. For a refresher on plotting fundamentals, see here.

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