TgapsPercentMetric¶
- class rubin_sim.maf.metrics.TgapsPercentMetric(times_col='observationStartMJD', all_gaps=False, min_time=0.08333333333333333, max_time=0.5833333333333334, units='percent', **kwargs)¶
Bases:
BaseMetric
Compute the fraction of the time gaps between observations that occur in a given time range.
Measure the gaps between observations. By default, only gaps between neighboring visits are computed. If all_gaps is set to true, all gaps are computed (i.e., if there are observations at 10, 20, 30 and 40 the default will Compute the percent of gaps between specified endpoints.
This is different from the TgapsMetric in that this only looks at what percent of intervals fall into the specified range, rather than histogramming the entire set of tgaps.
- Parameters:
- times_col
str
, opt The column name for the exposure times. Values assumed to be in days. Default observationStartMJD.
- all_gaps
bool
, opt Histogram the gaps between all observations (True) or just successive observations (False)? Default is False. If all gaps are used, this metric can become significantly slower.
- min_time
float
, opt Minimum time of gaps to include (days). Default 2/24 (2 hours).
- max_time
float
, opt Max time of gaps to include (days). Default 14/24 (14 hours).
- times_col
- Returns:
- percent
float
Returns a float percent of the CDF between cdfMinTime and cdfMaxTime - (# of tgaps within min_time/max_time / # of all tgaps).
- percent
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: