def get_catalog(self,
query=None,
query_fields=None,
print_query=False,
**kwargs):
"""
Grab a catalog of sources around the input coordinate to the search radius
Args:
query: Not used
query_fields (list, optional): Over-ride list of items to query
print_query (bool): Print the SQL query generated
Returns:
astropy.table.Table: Catalog of sources returned. Includes WISE
photometry for matched sources.
"""
# Main DES query
main_cat = super(DES_Survey,
self).get_catalog(query_fields=query_fields,
print_query=print_query,
**kwargs)
if len(main_cat) == 0:
main_cat = catalog_utils.clean_cat(main_cat, photom['DES'])
return main_cat
main_cat = catalog_utils.clean_cat(main_cat, photom['DES'])
# WISE
wise_query = self._gen_cat_query(qtype='wise')
wise_cat = super(DES_Survey, self).get_catalog(query=wise_query,
print_query=print_query,
**kwargs)
wise_cat = catalog_utils.clean_cat(wise_cat,
photom['DES-WISE'],
fill_mask=-999.)
# Match em up
if len(wise_cat) > 0:
idx = catalog_utils.match_ids(wise_cat['DES_ID'],
main_cat['DES_ID'],
require_in_match=False)
# Fill me
for band in DES_WISE_bands:
main_cat['WISE_{:s}'.format(band)] = -999.
main_cat['WISE_{:s}'.format(band)][idx] = wise_cat[
band.replace("W", "WISE")]
main_cat['WISE_{:s}_err'.format(band)] = -999.
main_cat['WISE_{:s}_err'.format(band)][idx] = wise_cat[
'{:s}_err'.format(band.replace("W", "WISE"))]
# Finish
self.catalog = main_cat
self.validate_catalog()
return self.catalog
def get_catalog(self, photoobj_fields=None, timeout=120, print_query=False):
"""
Query SDSS for all objects within a given
radius of the input coordinates.
Merges photometry with photo-z
TODO -- Expand to include spectroscopy
TODO -- Consider grabbing all of the photometry fields
Args:
coord: astropy.coordiantes.SkyCoord
radius: Angle, optional
Search radius
photoobj_fields: list
Fields for querying
timeout: float, optional
Default value - 120 s.
print_query: bool, optional
Print the SQL query for the photo-z values
Returns:
catalog: astropy.table.Table
Contains all measurements retieved
*WARNING* :: The SDSS photometry table frequently has multiple entries for a given
source, with unique objid values
"""
if photoobj_fields is None:
photoobj_fs = ['ra', 'dec', 'objid', 'run', 'rerun', 'camcol', 'field','type']
mags = ['modelMag_'+band for band in SDSS_bands]
magsErr = ['modelMagErr_'+band for band in SDSS_bands]
extinct = ["extinction_"+band for band in SDSS_bands]
photoobj_fields = photoobj_fs+mags+magsErr+extinct
# Call
photom_catalog = SDSS.query_region(self.coord, radius=self.radius, timeout=timeout,
photoobj_fields=photoobj_fields)
if photom_catalog is None:
self.catalog = Table()
self.catalog.meta['radius'] = self.radius
self.catalog.meta['survey'] = self.survey
# Validate
self.validate_catalog()
return
# Now query for photo-z
query = "SELECT GN.distance, "
query += "p.objid, "
query += "pz.z as redshift, pz.zErr as redshift_error\n"
query += "FROM PhotoObj as p\n"
query += "JOIN dbo.fGetNearbyObjEq({:f},{:f},{:f}) AS GN\nON GN.objID=p.objID\n".format(
self.coord.ra.value,self.coord.dec.value,self.radius.to('arcmin').value)
query += "JOIN Photoz AS pz ON pz.objID=p.objID\n"
query += "ORDER BY distance"
if print_query:
print(query)
# SQL command
photz_cat = SDSS.query_sql(query,timeout=timeout)
# Match em up
if photz_cat is not None:
matches = catalog_utils.match_ids(photz_cat['objid'], photom_catalog['objid'], require_in_match=False)
else:
matches = -1 * np.ones(len(photom_catalog), dtype=int)
gdz = matches > 0
# Init
photom_catalog['photo_z'] = -9999.
photom_catalog['photo_zerr'] = -9999.
# Fill
if np.any(gdz):
photom_catalog['photo_z'][matches[gdz]] = photz_cat['redshift'][np.where(gdz)]
photom_catalog['photo_zerr'][matches[gdz]] = photz_cat['redshift_error'][np.where(gdz)]
# Trim down catalog
trim_catalog = trim_down_catalog(photom_catalog, keep_photoz=True)
# Clean up
trim_catalog = catalog_utils.clean_cat(trim_catalog, photom['SDSS'])
# Spectral info
spec_fields = ['ra', 'dec', 'z', 'run2d', 'plate', 'fiberID', 'mjd', 'instrument']
spec_catalog = SDSS.query_region(self.coord,spectro=True, radius=self.radius,
timeout=timeout, specobj_fields=spec_fields) # Duplicates may exist
if spec_catalog is not None:
trim_spec_catalog = trim_down_catalog(spec_catalog)
# Match
spec_coords = SkyCoord(ra=trim_spec_catalog['ra'], dec=trim_spec_catalog['dec'], unit='deg')
phot_coords = SkyCoord(ra=trim_catalog['ra'], dec=trim_catalog['dec'], unit='deg')
idx, d2d, d3d = match_coordinates_sky(spec_coords, phot_coords, nthneighbor=1)
# Check
if np.max(d2d).to('arcsec').value > 1.5:
raise ValueError("Bad match in SDSS")
# Fill me
zs = -1 * np.ones_like(trim_catalog['ra'].data)
zs[idx] = trim_spec_catalog['z']
trim_catalog['z_spec'] = zs
else:
trim_catalog['z_spec'] = -1.
# Sort by offset
catalog = trim_catalog.copy()
self.catalog = catalog_utils.sort_by_separation(catalog, self.coord, radec=('ra','dec'), add_sep=True)
# Meta
self.catalog.meta['radius'] = self.radius
self.catalog.meta['survey'] = self.survey
# Validate
self.validate_catalog()
# Return
return self.catalog.copy()