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
matchedMultiVisitDatasetlsst.valididate.drp.matchreduce.MatchedMultiVisitDataset

A dataset containing matched statistics for stars across multiple visits.

selectionnp.array of bool

The selection of sources to use to build the model.

medianReffloat or astropy.unit.Quantity, optional

Median reference astrometric scatter (millimagnitudes by default).

matchRefint or astropy.unit.Quantity, optional

Should match at least matchRef stars.

Returns
bloblsst.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.