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.

mjd_colstr, optional

The column containing time for each observation. Default “observationStartMJD”.

survey_lengthfloat, optional

The overall duration of the survey. Default 10.

Methods Summary

run(data_slice[, slice_point])

Calculate metric values.

Methods Documentation

run(data_slice, slice_point=None)

Calculate metric values.

data_slicenumpy.ndarray, (N,)

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.

metricValue: int float or object

The metric value at each slice_point.