CoaddStacker

class rubin_sim.maf.stackers.CoaddStacker(mjd_col='observationStartMJD', ra_col='fieldRA', dec_col='fieldDec', m5_col='fiveSigmaDepth', nightcol='night', filter_col='filter', night_col='night', num_exposures_col='numExposures', visit_time_col='visitTime', visit_exposure_time_col='visitExposureTime')

Bases: BaseStacker

Stacker to estimate m5 “coadded” per band and par night

Parameters:

liststr, optional

Name of the columns used. Default : ‘observationStartMJD’, ‘fieldRA’, ‘fieldDec’,’filter’,’fiveSigmaDepth’,’visitExposureTime’,’night’,’observationId’, ‘numExposures’,’visitTime’

Attributes Summary

cols_added

Methods Summary

fill(tab)	Estimation of new fields (m5 "coadded" values, ...)
m5_coadd(m5)	Estimation of "coadded" m5 values based on: flux_5sigma = 10**(-0.4*m5) sigmas = flux_5sigma/5.

Attributes Documentation

cols_added = ['coadd']

Methods Documentation

fill(tab)

Estimation of new fields (m5 “coadded” values, …)

Parameters:

tabarray of (initial) data

Returns:

tuple with modified field values:

• m5Col: “coadded” m5

• numExposuresCol: sum of numExposuresCol

• visitTimeCol: sum of visitTimeCol

• visitExposureTimeCol: sum of visitExposureTimeCol

- all other input fields except band (Ra, Dec, night)median(field)

m5_coadd(m5)

Estimation of “coadded” m5 values based on: flux_5sigma = 10**(-0.4*m5) sigmas = flux_5sigma/5. sigma_tot = 1./sqrt(np.sum(1/sigmas**2)) flux_tot = 5.*sigma_tot

Parameters:

m5set of m5 (five-sigma depths) values

Returns:

“coadded” m5 value