BDParallaxMetric

class rubin_sim.maf.metrics.BDParallaxMetric(metric_name='bdParallax', m5_col='fiveSigmaDepth', filter_col='filter', seeing_col='seeingFwhmGeom', badval=0, mags=None, parallax_snr=10.0, distances=array([10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190]), atm_err=0.01, normalize=False, **kwargs)

Bases: BaseMetric

Calculate the distance to which one could reach a parallax SNR for a given object Modification of ParallaxMetric, illustrated in https://github.com/jgizis/LSST-BD-Cadence/blob/main/bd_allLT_baseline_17.ipynb

Uses columns ra_pi_amp and dec_pi_amp, calculated by the ParallaxFactorStacker.

Parameters:

metricNamestr, opt

Default ‘parallax’.

m5_colstr, opt

The default column name for m5 information in the input data. Default fiveSigmaDepth.

filter_colstr, opt

The column name for the filter information. Default filter.

seeing_colstr, opt

The column name for the seeing information. Since the astrometry errors are based on the physical size of the PSF, this should be the FWHM of the physical psf. Default seeingFwhmGeom.

magsdict (None)

The absolute magnitude of the obeject in question. Keys of filter name, values in mags. Defaults to an L7 spectral type if None.

distancesnp.array

Distances to try putting the object at (pc).

atm_errfloat, opt

The expected centroiding error due to the atmosphere, in arcseconds. Default 0.01.

badvalfloat, opt

The value to return when the metric value cannot be calculated. Default 0.

Methods Summary

run(data_slice[, slice_point])

Calculate metric values.

Methods Documentation

run(data_slice, slice_point=None)

Calculate metric values.

Parameters:

data_slicenumpy.recarray

Values passed to metric by the slicer, which the metric will use to calculate metric values at each slice_point.

slice_pointdict or None

Dictionary of slice_point metadata passed to each metric. E.g. the ra/dec of the healpix pixel or opsim fieldId.

Returns:

metricValue: int float or object

The metric value at each slice_point.