class rubin_sim.maf.metrics.MoCompletenessAtTimeMetric(times, hval=None, cumulative=None, hindex=0.33, **kwargs)

Bases: BaseMoMetric

Calculate the completeness (relative to the entire population) <= a given H as a function of time, given the times of each discovery.

Input values of the discovery times can come from the Discovery_Time (child) metric or the KnownObjects metric.

timesnumpy.ndarray like

The bins to distribute the discovery times into. Same units as the discovery time (typically MJD).

hvalfloat, optional

The value of H to count completeness at (or cumulative completeness to). Default None, in which case a value halfway through h_vals (the slicer H range) will be chosen.

cumulativebool, optional

If True, calculate the cumulative completeness (completeness <= H). If False, calculate the differential completeness (completeness @ H). Default None which becomes ‘True’ unless metric_name starts with ‘differential’.

hindexfloat, optional

Use hindex as the power law to integrate over H, if cumulative is True. Default 0.3.

Methods Summary

run(discovery_times, h_vals)

Calculate the metric value.

Methods Documentation

run(discovery_times, h_vals)

Calculate the metric value.

sso_obs: np.ndarray

The input data to the metric (same as the parent metric).

orb: np.ndarray

The information about the orbit for which the metric is being calculated.


The H value for which the metric is being calculated.

float or np.ndarray or dict