class rubin_sim.maf.stackers.MoMagStacker(magtype='asteroid', v_mag_col='magV', color_col='dmag_color', loss_col='dmag_detect', m5_col='fiveSigmaDepth', seeing_col='seeingFwhmGeom', filter_col='filter', gamma=0.038, sigma=0.12, random_seed=None)

Bases: BaseMoStacker

Add columns relevant to SSobject apparent magnitudes and visibility to the slicer ssoObs dataframe, given a particular Href and current h_val.

Specifically, this stacker adds magLimit, appMag, SNR, and vis. magLimit indicates the appropriate limiting magnitude to consider for a particular object in a particular observation, when combined with the losses due to detection (dmag_detect) or trailing (dmagTrail). appMag adds the apparent magnitude in the filter of the current object, at the current h_val. SNR adds the SNR of this object, given the magLimit. vis adds a flag (0/1) indicating whether an object was visible (assuming a 5sigma threshhold including some probabilistic determination of visibility).

m5Colstr, optional

Name of the column describing the 5 sigma depth of each visit. Default fiveSigmaDepth.

lossColstr, optional

Name of the column describing the magnitude losses, due to trailing (dmagTrail) or detection (dmag_detect). Default dmag_detect.

gammafloat, optional

The ‘gamma’ value for calculating SNR. Default 0.038. LSST range under normal conditions is about 0.037 to 0.039.

sigmafloat, optional

The ‘sigma’ value for probabilistic prediction of whether or not an object is visible at 5sigma. Default 0.12. The probabilistic prediction of visibility is based on Fermi-Dirac completeness formula (see SDSS, eqn 24, Stripe82 analysis:

randomSeed: `int` or None, optional

If set, then used as the random seed for the numpy random number generation for the dither offsets. Default: None.

Attributes Summary


Attributes Documentation

cols_added = ['appMag', 'SNR', 'vis']