M5OptimalStacker

class rubin_sim.maf.stackers.M5OptimalStacker(airmass_col='airmass', dec_col='fieldDec', sky_bright_col='skyBrightness', seeing_col='seeingFwhmEff', filter_col='filter', moon_alt_col='moonAlt', sun_alt_col='sunAlt', site='LSST')

Bases: BaseStacker

Make a new m5 column as if observations were taken on the meridian. If the moon is up, assume sky brightness stays the same.

Assumes seeing scales as airmass^0.6. Uses linear fits for sky and airmass relation.

Parameters:

airmass_colstr (‘airmass’)

Column name for the airmass per pointing.

dec_colstr (‘dec_rad’)

Column name for the pointing declination.

sky_bright_col: str (‘filtSkyBrightness’)

Column name for the sky brighntess per pointing.

filter_colstr (‘filter’)

Column name for the filter name.

m5_colstr (‘fiveSigmaDepth’)

Colum name for the five sigma limiting depth per pointing.

moon_alt_colstr (‘moonAlt’)

Column name for the moon altitude per pointing.

sun_alt_colstr (‘sun_alt_col’)

Column name for the sun altitude column.

sitestr (‘LSST’)

Name of the site.

Returns:

numpy.array

Adds a column to that is approximately what the five-sigma depth would have been if the observation had been taken on the meridian.

Attributes Summary

cols_added

Attributes Documentation

cols_added = ['m5Optimal']