ParallaxDcrDegenMetric¶
- class rubin_sim.maf.metrics.ParallaxDcrDegenMetric(metric_name='ParallaxDcrDegenMetric', seeing_col='seeingFwhmGeom', m5_col='fiveSigmaDepth', atm_err=0.01, rmag=20.0, sed_template='flat', filter_col='filter', tol=0.05, **kwargs)¶
Bases:
BaseMetricUse the full parallax and DCR displacement vectors to find if they are degenerate.
- Parameters:
- metricNamestr, optional
Default ‘ParallaxDcrDegenMetric’.
- seeing_colstr, optional
Default ‘FWHMgeom’
- m5_colstr, optional
Default ‘fiveSigmaDepth’
- filter_colstr
Default ‘filter’
- atm_errfloat
Minimum error in photometry centroids introduced by the atmosphere (arcseconds). Default 0.01.
- rmagfloat
r-band magnitude of the fiducual star that is being used (mag).
- SedTemplatestr
The SED template to use for fiducia star colors, passed to rubin_sim.utils.stellarMags. Default ‘flat’
- tolfloat
Tolerance for how well curve_fit needs to work before believing the covariance result. Default 0.05.
- Returns:
- metricValuefloat
Returns the correlation coefficient between the best-fit parallax amplitude and DCR amplitude. The RA and Dec offsets are fit simultaneously. Values close to zero are good, values close to +/- 1 are bad. Experience with fitting Monte Carlo simulations suggests the astrometric fits start becoming poor around a correlation of 0.7.
Methods Summary
run(data_slice[, slice_point])Calculate metric values.
Methods Documentation
- run(data_slice, slice_point=None)¶
Calculate metric values.
- Parameters:
- data_slice
numpy.recarray Values passed to metric by the slicer, which the metric will use to calculate metric values at each slice_point.
- slice_point
dictor None Dictionary of slice_point metadata passed to each metric. E.g. the ra/dec of the healpix pixel or opsim fieldId.
- data_slice
- Returns: