build_photometric_error_model¶
-
lsst.validate.drp.photerrmodel.
build_photometric_error_model
(matchedMultiVisitDataset, selection, medianRef=100, matchRef=500)¶ Returns a serializable analytic photometry error model for a single visit.
This model is originally presented in http://arxiv.org/abs/0805.2366v4 (Eq 4, 5):
\[\begin{split}\sigma_1^2 &= \sigma_\mathrm{sys}^2 + \sigma_\mathrm{rand}^2 \\ x &= 10^{0.4(m-m_5)} \\ \sigma_\mathrm{rand}^2 &= (0.04 - \gamma) x + \gamma x^2~[\mathrm{mag}^2]\end{split}\]Parameters: - matchedMultiVisitDataset :
lsst.valididate.drp.matchreduce.MatchedMultiVisitDataset
A dataset containing matched statistics for stars across multiple visits.
- selection :
np.array
ofbool
The selection of sources to use to build the model.
- medianRef :
float
orastropy.unit.Quantity
, optional Median reference astrometric scatter (millimagnitudes by default).
- matchRef :
int
orastropy.unit.Quantity
, optional Should match at least matchRef stars.
Returns: - blob :
lsst.verify.Blob
Blob with datums:
sigmaSys
: Systematic error floor.gamma
: Proxy for sky brightness and read noise.m5
: 5-sigma photometric depth (magnitudes).photRms
: RMS photometric scatter for ‘good’ stars (millimagnitudes).
Notes
The scatter and match defaults are appropriate to SDSS are stored here. For SDSS, stars with mag < 19.5 should be completely well measured. This limit is a band-dependent statement most appropriate to r.
- matchedMultiVisitDataset :