ProperMotionMetric¶
- class rubin_sim.maf.metrics.ProperMotionMetric(metric_name='properMotion', m5_col='fiveSigmaDepth', mjd_col='observationStartMJD', filter_col='filter', seeing_col='seeingFwhmGeom', rmag=20.0, sed_template='flat', badval=-666, atm_err=0.01, normalize=False, baseline=10.0, **kwargs)¶
Bases:
BaseMetric
Calculate the uncertainty in the returned proper motion.
This metric assumes gaussian errors in the astrometry measurements.
- Parameters:
- metricNamestr, optional
Default ‘properMotion’.
- m5_colstr, optional
The default column name for m5 information in the input data. Default fiveSigmaDepth.
- mjd_colstr, optional
The column name for the exposure time. Default observationStartMJD.
- filterColstr, optional
The column name for the filter information. Default filter.
- seeing_colstr, optional
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.
- rmagfloat, optional
The r magnitude of the fiducial star in r band. Other filters are sclaed using sedTemplate keyword. Default 20.0
- SedTemplatestr, optional
The template to use. This can be ‘flat’ or ‘O’,’B’,’A’,’F’,’G’,’K’,’M’. Default flat.
- atm_errfloat, optional
The expected centroiding error due to the atmosphere, in arcseconds. Default 0.01.
- normalize
bool
, optional Compare the astrometric uncertainty to the uncertainty that would result if half the observations were taken at the start and half at the end. A perfect survey will have a value close to 1, while a poorly scheduled survey will be close to 0. Default False.
- baselinefloat, optional
The length of the survey used for the normalization, in years. Default 10.
- badvalfloat, optional
The value to return when the metric value cannot be calculated. Default -666.
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.ndarray
, (N,) Values passed to metric by the slicer, which the metric will use to calculate metric values at each slice_point.
- slice_point
dict
or 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: