def _xmatch(session, edge):
"""Join photometric measurements of two overlapping catalogs in the
given bandpass.
"""
from_cstar = aliased(CatalogStar)
to_cstar = aliased(CatalogStar)
from_cat = aliased(Catalog)
to_cat = aliased(Catalog)
from_obs = aliased(Observation)
to_obs = aliased(Observation)
from_bp = aliased(Bandpass)
to_bp = aliased(Bandpass)
overlap_polygon = _make_q3c_polygon(_get_overlap_polygon(session, edge))
q = (
session.query(from_obs.mag, from_obs.mag_err, to_obs.mag, to_obs.mag_err)
.join(to_cstar, to_cat.catalog_stars)
.join(from_cstar, from_cat.catalog_stars)
.filter(to_cat.id == edge.to_id)
.filter(from_cat.id == edge.from_id)
.filter(func.q3c_poly_query(to_cstar.ra, to_cstar.dec, overlap_polygon))
.filter(func.q3c_join(to_cstar.ra, to_cstar.dec, from_cstar.ra, from_cstar.dec, 1.0 / 3600.0))
.join(from_obs, from_cstar.observations)
.join(to_obs, to_cstar.observations)
.join(from_bp, from_obs.bandpass)
.filter(from_bp.id == edge.bandpass_id)
.join(to_bp, to_obs.bandpass)
.filter(to_bp.id == edge.bandpass_id)
)
dt = np.dtype([("from_mag", float), ("from_mag_err", float), ("to_mag", float), ("to_mag_err", float)])
data = np.array(q.all(), np.dtype(dt))
return data
def sources_contained(self):
"""Query the database and return all `Sources` contained by the
polygon of this object"""
from .source import Source
return DBSession().query(Source) \
.filter(func.q3c_poly_query(Source.ra,
Source.dec,
self.poly))
def images(self, type=CalibratableImage):
candidates = DBSession().query(type).filter(
func.q3c_radial_query(
type.ra, type.dec, self.ra, self.dec,
0.64)).filter(func.q3c_poly_query(self.ra, self.dec,
type.poly))
return candidates.all()
def load_photometry(fieldname, tile, radec_poly,
use_vega, disable_intercal,
server='marvin'):
"""Load WIRCam photometry from Starplex, converted to AB mag."""
instrument = "wircam"
connect_to_server(server)
session = Session()
mag1obs = aliased(Observation)
mag2obs = aliased(Observation)
bp1 = aliased(Bandpass)
bp2 = aliased(Bandpass)
catalog = session.query(Catalog).\
filter(Catalog.name == fieldname).\
filter(Catalog.instrument == instrument).\
one()
q = session.query(CatalogStar.cfrac, mag1obs.mag, mag2obs.mag_err,
mag2obs.mag, mag2obs.mag_err).\
join(mag1obs, CatalogStar.observations).\
join(mag2obs, CatalogStar.observations).\
join(Catalog).\
filter(Catalog.name == fieldname).\
filter(Catalog.instrument == instrument).\
join(bp1, mag1obs.bandpass).\
filter(bp1.name == "J").\
join(bp2, mag2obs.bandpass).\
filter(bp2.name == "Ks").\
filter(func.q3c_poly_query(CatalogStar.ra,
CatalogStar.dec,
np.array(radec_poly).flatten().tolist()))
dt = [('cfrac', np.float), ('J', np.float), ('J_err', np.float),
('Ks', np.float), ('Ks_err', np.float)]
data = np.array(q.all(), dtype=np.dtype(dt))
# Apply the intercal ZP correction
if not disable_intercal:
if 'intercal' in catalog.meta:
for band in ['J', 'Ks']:
if band in catalog.meta['intercal']:
data[band] += catalog.meta['intercal'][band]['zp']
# Convert to AB
if not use_vega:
data['J'] = wircam_vega_to_ab(data['J'], "J")
data['Ks'] = wircam_vega_to_ab(data['Ks'], "Ks")
log.info("Field {0} {2} {3:d} has {1:d} stars".
format(fieldname, data.shape[0], instrument, tile))
session.close()
if len(data) == 0:
raise NoDataError
return data
def unphotometered_images(self):
subq = DBSession().query(
ForcedPhotometry.id, ForcedPhotometry.image_id).filter(
ForcedPhotometry.source_id == self.id).subquery()
q = DBSession().query(SingleEpochSubtraction).filter(
func.q3c_radial_query(
SingleEpochSubtraction.ra, SingleEpochSubtraction.dec, self.ra,
self.dec, 0.64)).filter(
func.q3c_poly_query(
self.ra, self.dec,
SingleEpochSubtraction.poly)).outerjoin(
subq, subq.c.image_id == SingleEpochSubtraction.id
).filter(subq.c.id == None)
return q.all()
def _xmatch(session, edge):
"""Join photometric measurements of two overlapping catalogs in the
given bandpass.
"""
from_cstar = aliased(CatalogStar)
to_cstar = aliased(CatalogStar)
from_cat = aliased(Catalog)
to_cat = aliased(Catalog)
from_obs = aliased(Observation)
to_obs = aliased(Observation)
from_bp = aliased(Bandpass)
to_bp = aliased(Bandpass)
overlap_polygon = _make_q3c_polygon(_get_overlap_polygon(session, edge))
q = session.query(from_obs.mag,
from_obs.mag_err,
to_obs.mag,
to_obs.mag_err).\
join(to_cstar, to_cat.catalog_stars).\
join(from_cstar, from_cat.catalog_stars).\
filter(to_cat.id == edge.to_id).\
filter(from_cat.id == edge.from_id).\
filter(func.q3c_poly_query(to_cstar.ra,
to_cstar.dec,
overlap_polygon)).\
filter(func.q3c_join(to_cstar.ra,
to_cstar.dec,
from_cstar.ra,
from_cstar.dec,
1. / 3600.)).\
join(from_obs, from_cstar.observations).\
join(to_obs, to_cstar.observations).\
join(from_bp, from_obs.bandpass).\
filter(from_bp.id == edge.bandpass_id).\
join(to_bp, to_obs.bandpass).\
filter(to_bp.id == edge.bandpass_id)
dt = np.dtype([('from_mag', float), ('from_mag_err', float),
('to_mag', float), ('to_mag_err', float)])
data = np.array(q.all(), np.dtype(dt))
return data
