MoCompletenessAtTimeMetric¶
- 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.
- Parameters:
- times
numpy.ndarray
like The bins to distribute the discovery times into. Same units as the discovery time (typically MJD).
- hval
float
, 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.
- cumulative
bool
, 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’.
- hindex
float
, optional Use hindex as the power law to integrate over H, if cumulative is True. Default 0.3.
- times
Methods Summary
run
(discovery_times, h_vals)Calculate the metric value.
Methods Documentation
- run(discovery_times, h_vals)¶
Calculate the metric value.
- Parameters:
- 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.
- hvalfloat
The H value for which the metric is being calculated.
- Returns:
- float or np.ndarray or dict