UniformityMetric¶
- class rubin_sim.maf.metrics.UniformityMetric(mjd_col='observationStartMJD', units='', survey_length=10.0, **kwargs)¶
Bases:
BaseMetric
Calculate how uniformly the observations are spaced in time.
This is based on how a KS-test works: look at the cumulative distribution of observation dates, and compare to a perfectly uniform cumulative distribution. Perfectly uniform observations = 0, perfectly non-uniform = 1.
- Parameters:
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: