def __init__(self):
BlobBase.__init__(self)
self.register_datum('mag', quantity=5 * u.mag, description='Magnitude')
self.register_datum('updateable_mag',
quantity=5 * u.mag,
description='Magnitude')
def __init__(self,
repo,
dataIds,
matchRadius=None,
safeSnr=50.,
useJointCal=False,
verbose=False):
BlobBase.__init__(self)
self.verbose = verbose
if not matchRadius:
matchRadius = afwGeom.Angle(1, afwGeom.arcseconds)
# Extract single filter
self.register_datum('filterName',
quantity=set([dId['filter']
for dId in dataIds]).pop(),
description='Filter name')
# Record important configuration
self.register_datum(
'useJointCal',
quantity=useJointCal,
description='Whether jointcal/meas_mosaic calibrations were used')
# Register datums stored by this blob; will be set later
self.register_datum(
'mag',
label='{band}'.format(band=self.filterName),
description='Mean PSF magnitudes of stars over multiple visits')
self.register_datum(
'magrms',
label='RMS({band})'.format(band=self.filterName),
description='RMS of PSF magnitudes over multiple visits')
self.register_datum(
'magerr',
label='sigma({band})'.format(band=self.filterName),
description='Median 1-sigma uncertainty of PSF magnitudes over '
'multiple visits')
self.register_datum(
'snr',
label='SNR({band})'.format(band=self.filterName),
description='Median signal-to-noise ratio of PSF magnitudes over '
'multiple visits')
self.register_datum(
'dist',
label='d',
description='RMS of sky coordinates of stars over multiple visits')
# Match catalogs across visits
self._matchedCatalog = self._loadAndMatchCatalogs(
repo, dataIds, matchRadius, useJointCal=useJointCal)
self.magKey = self._matchedCatalog.schema.find("base_PsfFlux_mag").key
# Reduce catalogs into summary statistics.
# These are the serialiable attributes of this class.
self._reduceStars(self._matchedCatalog, safeSnr)
def __init__(self,
matchedMultiVisitDataset,
brightSnr=100,
medianRef=100,
matchRef=500):
BlobBase.__init__(self)
self.register_datum(
'brightSnr',
label='Bright SNR',
description='Threshold in SNR for bright sources used in this '
'model')
self.register_datum('sigmaSys',
label='sigma(sys)',
description='Systematic error floor')
self.register_datum(
'gamma',
label='gamma',
description='Proxy for sky brightness and read noise')
self.register_datum('m5', label='m5', description='5-sigma depth')
self.register_datum(
'photScatter',
label='RMS',
description='RMS photometric scatter for good stars')
# FIXME add a description field to blobs?
# self._doc['doc'] \
# = "Photometric uncertainty model from " \
# "http://arxiv.org/abs/0805.2366v4 (Eq 4, 5): " \
# "sigma_1^2 = sigma_sys^2 + sigma_rand^2, " \
# "sigma_rand^2 = (0.04 - gamma) * x + gamma * x^2 [mag^2] " \
# "where x = 10**(0.4*(m-m_5))"
if not isinstance(medianRef, u.Quantity):
medianRef = medianRef * u.mmag
if not isinstance(brightSnr, u.Quantity):
brightSnr = brightSnr * u.Unit('')
self._compute(matchedMultiVisitDataset.snr,
matchedMultiVisitDataset.mag,
matchedMultiVisitDataset.magerr,
matchedMultiVisitDataset.magrms,
matchedMultiVisitDataset.dist,
len(matchedMultiVisitDataset.goodMatches), brightSnr,
medianRef, matchRef)
def __init__(self,
matchedMultiVisitDataset,
brightSnr=100,
medianRef=100,
matchRef=500):
BlobBase.__init__(self)
# FIXME add description field to blobs
# self._doc['doc'] \
# = "Astrometric astrometry model: mas = C*theta/SNR + sigmaSys"
if not isinstance(brightSnr, u.Quantity):
brightSnr = brightSnr * u.Unit('')
if not isinstance(medianRef, u.Quantity):
medianRef = medianRef * u.marcsec
self._compute(matchedMultiVisitDataset.snr,
matchedMultiVisitDataset.dist,
len(matchedMultiVisitDataset.goodMatches), brightSnr,
medianRef, matchRef)