class rubin_sim.maf.metrics.ColorAsteroidMetric(weight_det=10, snr_max=20, snr_limit=None, **kwargs)

Bases: BaseMoMetric

This metric is appropriate for MBAs and NEOs, and other inner solar system objects.

The metric evaluates if the SNR-weighted number of observations are enough to determine an approximate lightcurve and phase function – and from this, then a color for the asteroid can be determined. The assumption is that you must fit the lightcurve/phase function in each bandpass, and could do this well-enough if you have at least weight_det SNR-weighted observations in the bandpass. e.g. to find a g-r color, you must have 10 (SNR-weighted) obs in g and 10 in r.

For more details, see Contributed by Wes Fraser, Steven Chesley & the inner solar system working group.

weight_det: float, optional

The SNR-weighted number of detections required (per bandpass in any ONE of the filters in filterlist). Default 10.

snr_limit: float or None, optional

If snr_limit is set as a float, then requires object to be above snr_limit SNR in the image. If snr_limit is None, this uses the probabilistic ‘visibility’ calculated by the vis stacker, which means SNR ~ 5. Default is None.

snr_max: float, optional

Maximum value toward the SNR-weighting to consider. Default 20.


An integer ‘flag’ that indicates whether the mean magnitude (and thus a color) was determined in: 0 = no bands 1 = g and (r or i) and (z or y). i.e. obtain colors g-r or g-i PLUS g-z or g-y 2 = Any 4 different filters (from grizy). i.e. colors = g-r, r-i, i-z, OR r-i, i-z, z-y.. 3 = All 5 from grizy. i.e. colors g-r, r-i, i-z, z-y. 4 = All 6 filters (ugrizy) – best possible! add u-g.

Methods Summary

run(sso_obs, orb, hval)

Calculate the metric value.

Methods Documentation

run(sso_obs, orb, hval)

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