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
grab_wise (bool): Attempt to grab WISE data too.
This is not recommended.
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'])
## Finish
self.catalog = main_cat
self.validate_catalog()
return self.catalog
def get_catalog(self,
query=None,
query_fields=_DEFAULT_query_fields,
print_query=False,
system='AB'):
"""
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
system (str): Magnitude system ['AB', 'Vega']
Returns:
astropy.table.Table: Catalog of sources returned. Includes WISE
photometry for matched sources.
Magnitudes are in AB by default
"""
# Main WISE query
if query is None:
self._gen_cat_query(query_fields)
if print_query:
print(self.query)
main_cat = self.service.run_async(self.query).to_table()
main_cat.meta['radius'] = self.radius
main_cat.meta['survey'] = self.survey
if len(main_cat) == 0:
main_cat = catalog_utils.clean_cat(main_cat,
photom['WISE'],
fill_mask=-999.)
return main_cat
main_cat = catalog_utils.clean_cat(main_cat,
photom['WISE'],
fill_mask=-999.)
# Convert to AB mag
if system == 'AB':
fnu0 = {
'WISE_W1': 309.54,
'WISE_W2': 171.787,
'WISE_W3': 31.674,
'WISE_W4': 8.363
}
for item in ['1', '2', '3', '4']:
filt = 'WISE_W' + item
main_cat[filt] -= 2.5 * np.log10(fnu0[filt] / 3631.)
elif system == 'Vega':
pass
# Finish
self.catalog = main_cat
self.validate_catalog()
return self.catalog.copy()
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, query=None, query_fields=None, print_query=False):
"""
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(WISE_Survey,
self).get_catalog(query_fields=query_fields,
print_query=print_query)
if len(main_cat) == 0:
return main_cat
main_cat = catalog_utils.clean_cat(main_cat,
photom['WISE'],
fill_mask=-999.)
# Finish
self.catalog = main_cat
self.validate_catalog()
return self.catalog
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
if query == None:
self.query = self._gen_cat_query(query_fields=query_fields)
else:
self.query = query
main_cat = super(VISTA_Survey,
self).get_catalog(query=self.query,
print_query=print_query,
photomdict=photom['VISTA'],
**kwargs)
if len(main_cat) == 0:
main_cat = catalog_utils.clean_cat(main_cat, photom['VISTA'])
return main_cat
main_cat = catalog_utils.clean_cat(main_cat, photom['VISTA'])
for col in main_cat.colnames:
if main_cat[col].dtype == float:
mask = np.isnan(main_cat[col]) + (main_cat[col] == 99.99)
main_cat[col] = np.where(~mask, main_cat[col], -999.0)
# Finish
self.catalog = main_cat
self.validate_catalog()
return self.catalog
def get_catalog(self,
query=None,
query_fields=None,
print_query=False,
exclude_gaia=False,
**kwargs):
"""
Grab a catalog of sources around the input coordinate to the search radius
Args:
query: SQL query
query_fields (list, optional): Over-ride list of items to query
exclude_gaia (bool,optional): If the field 'gaia_pointsource' is present and is 1,
remove those objects from the output catalog.
print_query (bool): Print the SQL query generated
Returns:
astropy.table.Table: Catalog of sources returned
"""
# Query
main_cat = super(DECaL_Survey,
self).get_catalog(query_fields=query_fields,
print_query=print_query,
**kwargs)
main_cat = Table(main_cat, masked=True)
#
for col in main_cat.colnames:
main_cat[col].mask = np.isnan(main_cat[col])
#Convert SNR to mag error values.
snr_cols = [
colname for colname in main_cat.colnames if "snr" in colname
]
for col in snr_cols:
main_cat[col].mask = main_cat[col] < 0
main_cat[col] = 2.5 * np.log10(1 + 1 / main_cat[col])
main_cat = main_cat.filled(-99.0)
#Remove gaia objects if necessary
if exclude_gaia:
self.catalog = main_cat[main_cat['gaia_pointsource'] == 0]
else:
self.catalog = main_cat
# Clean
main_cat = catalog_utils.clean_cat(main_cat, photom['DECaL'])
self.validate_catalog()
# Return
return self.catalog
def get_catalog(self,
query=None,
query_fields=None,
print_query=False,
timeout=120,
photomdict=None):
"""
Get catalog sources around the given coordinates
within self.radius.
Args:
query (str, optional): SQL query to generate the catalog
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 obtained from the SQL query.
"""
qc.set_profile(self.qc_profile)
# Generate the query
if query is None:
self._gen_cat_query(query_fields)
query = self.query
if print_query:
print(query)
# Do it while silencing print statements
result = qc.query(self.token, sql=query, timeout=timeout)
self.catalog = convert(result, outfmt="table")
if photomdict:
self.catalog = catalog_utils.clean_cat(self.catalog, photomdict)
self.catalog.meta['radius'] = self.radius
self.catalog.meta['survey'] = self.survey
# Validate
self.validate_catalog()
# Return
return self.catalog.copy()
def get_catalog(self, query_fields=None, release="dr2", table="stack"):
"""
Query a catalog in the VizieR database for
photometry.
Args:
query_fields: list, optional
A list of query fields to
get.
release: str, optional
"dr1" or "dr2" (default: "dr2").
Data release version.
table: str, optional
"mean","stack" or "detection"
(default: "stack"). The data table to
search within.
Returns:
catalog: astropy.table.Table
Contains all query results
"""
assert self.radius <= 0.5 * u.deg, "Cone serches have a maximum radius"
#Validate table and release input
_check_legal(table, release)
url = "https://catalogs.mast.stsci.edu/api/v0.1/panstarrs/{:s}/{:s}.csv".format(
release, table)
if query_fields is None:
query_fields = [
'objID', 'raStack', 'decStack', 'objInfoFlag', 'qualityFlag'
]
query_fields += [
'{:s}PSFmag'.format(band) for band in PanSTARRS_bands
]
query_fields += [
'{:s}PSFmagErr'.format(band) for band in PanSTARRS_bands
]
#Validate columns
_check_columns(query_fields, table, release)
data = {}
data['ra'] = self.coord.ra.value
data['dec'] = self.coord.dec.value
data['radius'] = self.radius.to(u.deg).value
data['columns'] = query_fields
ret = requests.get(url, params=data)
ret.raise_for_status()
if len(ret.text) == 0:
self.catalog = Table()
self.catalog.meta['radius'] = self.radius
self.catalog.meta['survey'] = self.survey
# Validate
self.validate_catalog()
return self.catalog.copy()
photom_catalog = Table.read(ret.text, format="ascii.csv")
pdict = photom['Pan-STARRS']
photom_catalog = catalog_utils.clean_cat(photom_catalog, pdict)
#
self.catalog = catalog_utils.sort_by_separation(photom_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()
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()
def get_catalog(self,
query_fields=None,
release="dr2",
table="stack",
print_query=False,
use_psf=False):
"""
Query a catalog in the MAST Pan-STARRS database for
photometry.
Args:
query_fields: list, optional
A list of query fields to
get in addition to the
default fields.
release: str, optional
"dr1" or "dr2" (default: "dr2").
Data release version.
table: str, optional
"mean","stack" or "detection"
(default: "stack"). The data table to
search within.
use_psf: bool, optional
If True, use PSFmag instead of KronMag
Returns:
catalog: astropy.table.Table
Contains all query results
"""
#assert self.radius <= 0.5*u.deg, "Cone serches have a maximum radius"
#Validate table and release input
_check_legal(table, release)
url = "https://catalogs.mast.stsci.edu/api/v0.1/panstarrs/{:s}/{:s}.csv".format(
release, table)
if query_fields is None:
query_fields = _DEFAULT_query_fields
else:
query_fields = _DEFAULT_query_fields + query_fields
#Validate columns
_check_columns(query_fields, table, release)
data = {}
data['ra'] = self.coord.ra.value
data['dec'] = self.coord.dec.value
data['radius'] = self.radius.to(u.deg).value
data['columns'] = query_fields
if print_query:
print(url)
ret = requests.get(url, params=data)
ret.raise_for_status()
if len(ret.text) == 0:
self.catalog = Table()
self.catalog.meta['radius'] = self.radius
self.catalog.meta['survey'] = self.survey
# Validate
self.validate_catalog()
return self.catalog.copy()
photom_catalog = Table.read(ret.text, format="ascii.csv")
pdict = photom['Pan-STARRS'].copy()
# Allow for PSF
if use_psf:
for band in PanSTARRS_bands:
pdict["Pan-STARRS" +
'_{:s}'.format(band)] = '{:s}PSFmag'.format(band.lower())
pdict["Pan-STARRS" +
'_{:s}_err'.format(band)] = '{:s}PSFmagErr'.format(
band.lower())
photom_catalog = catalog_utils.clean_cat(photom_catalog, pdict)
#Remove bad positions because Pan-STARRS apparently decided
#to flag some positions with large negative numbers. Why even keep
#them?
bad_ra = (photom_catalog['ra'] < 0) + (photom_catalog['ra'] > 360)
bad_dec = (photom_catalog['dec'] < -90) + (photom_catalog['dec'] > 90)
bad_pos = bad_ra + bad_dec # bad_ra OR bad_dec
photom_catalog = photom_catalog[~bad_pos]
# Remove duplicate entries.
photom_catalog = catalog_utils.remove_duplicates(
photom_catalog, "Pan-STARRS_ID")
self.catalog = catalog_utils.sort_by_separation(photom_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()