PeriodicStarMetric

class rubin_sim.maf.maf_contrib.PeriodicStarMetric(metric_name='PeriodicStarMetric', mjd_col='observationStartMJD', m5_col='fiveSigmaDepth', filter_col='filter', period=10.0, amplitude=0.5, phase=2.0, n_monte=1000, period_tol=0.05, amp_tol=0.1, means=[20.0, 20.0, 20.0, 20.0, 20.0, 20.0], mag_tol=0.1, n_bands=3, seed=42, **kwargs)

Bases: BaseMetric

At each slice_point, run a Monte Carlo simulation to see how well a periodic source can be fit. Assumes a simple sin-wave light-curve, and generates Gaussain noise based in the 5-sigma limiting depth of each observation.

Methods Summary

run(data_slice[, slice_point])

Calculate metric values.

Methods Documentation

run(data_slice, slice_point=None)

Calculate metric values.

Parameters:

data_slicenumpy.recarray

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.

Returns:

metricValue: int float or object

The metric value at each slice_point.