class rubin_sim.maf.metrics.GalPlaneFootprintMetric(science_map, tau_obs=None, mag_cuts=None, filter_col='filter', m5_col='fiveSigmaDepth', filterlist=None, **kwargs)

Bases: BaseMetric

Evaluate the survey overlap with desired regions in the Galactic Plane and Magellanic Clouds, by referencing the pre-computed priority maps provided. These priority maps are keyed by science area (science_map) and per filter. The returned metric values are summed over all filters.


Name of the priority footprint map key to use from the column headers contained in the priority_GalPlane_footprint_map_data tables.

tau_obsnp.ndarray or list of float, opt

Timescales of minimum-required observations intervals for various classes of time variability. Default (None), uses TAU_OBS. In general, this should be left as the default and consistent across all galactic-plane oriented metrics.

mag_cutsdict of float, opt

Magnitudes to use as cutoffs for individual image depths. Default None uses a default set of values which correspond roughly to the 50th percentile.

filter_colstr, opt

Name of the filter column. Default ‘filter’.

m5_colstr, opt

Name of the five-sigma depth column. Default ‘fiveSigmaDepth’.

filterlistlist of str, opt

The filters to consider from the priority map and observations. Default None uses u, g, r, i, z, and y.

metricNamestr, opt

Name for the metric. Default ‘GalPlaneFootprintMetric_{scienceMap}

Methods Summary



run(data_slice, slice_point)

Calculate the number of observations that meet the mag_cut values at each slice_point.

Methods Documentation

run(data_slice, slice_point)

Calculate the number of observations that meet the mag_cut values at each slice_point. Also calculate the number of observations * the priority map summed over all filter. Return both of these values as a dictionary.