"""DELVE survey"""
import numpy as np
from frb.surveys import dlsurvey, defs
from frb.surveys import catalog_utils
# Dependencies
try:
from pyvo.dal import sia
except ImportError:
print("Warning: You need to install pyvo to retrieve DELVE images")
_svc = None
else:
_svc = sia.SIAService(defs.NOIR_DEF_ACCESS_URL+'delve_dr1')
# Define the data model for DELVE data
# See https://datalab.noirlab.edu/query.php?name=delve_dr2.objects for
# table schema
photom = {}
photom['DELVE'] = {}
photom['DELVE']['DELVE_ID'] = 'quick_object_id'
photom['DELVE']['ra'] = 'ra'
photom['DELVE']['dec'] = 'dec'
photom['DELVE']['ebv'] = 'ebv' # Schegel, Finkbeiner, Davis (1998)
DELVE_bands = ['g', 'r', 'i', 'z']
for band in DELVE_bands:
photom['DELVE'][f'DELVE_{band}'] = f'mag_auto_{band}' #mag
photom['DELVE'][f'DELVE_{band}_err'] = f'magerr_auto_{band}' #magerr
photom['DELVE'][f'class_star_{band}'] = f'class_star_{band}' #morphology class
[docs]
class DELVE_Survey(dlsurvey.DL_Survey):
"""
Class to handle queries on the DELVE survey
Child of DL_Survey which uses datalab to access NOAO
Args:
coord (SkyCoord): Coordiante for surveying around
radius (Angle): Search radius around the coordinate
"""
[docs]
def __init__(self, coord, radius, **kwargs):
dlsurvey.DL_Survey.__init__(self, coord, radius, **kwargs)
self.survey = 'DELVE'
self.bands = DELVE_bands
self.svc = sia.SIAService("https://datalab.noao.edu/sia/delve_dr2")
self.qc_profile = "default"
self.database = "delve_dr2.objects"
self.default_query_fields = list(photom['DELVE'].values())
[docs]
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(DELVE_Survey, self).get_catalog(query=query,
query_fields=query_fields,
print_query=print_query,**kwargs)
if len(main_cat) == 0:
main_cat = catalog_utils.clean_cat(main_cat,photom['DELVE'])
return main_cat
main_cat = catalog_utils.clean_cat(main_cat, photom['DELVE'])
#import pdb; pdb.set_trace()
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