# DAOGroup¶

class photutils.DAOGroup(crit_separation)[source]

This class implements the DAOGROUP algorithm presented by Stetson (1987).

The method group_stars divides an entire starlist into sets of distinct, self-contained groups of mutually overlapping stars. It accepts as input a list of stars and determines which stars are close enough to be capable of adversely influencing each others’ profile fits.

Parameters: crit_separation : float or int Distance, in units of pixels, such that any two stars separated by less than this distance will be placed in the same group.

Notes

Assuming the psf fwhm to be known, crit_separation may be set to k*fwhm, for some positive real k.

References

[1] Stetson, Astronomical Society of the Pacific, Publications,
(ISSN 0004-6280), vol. 99, March 1987, p. 191-222. Available at: http://adsabs.harvard.edu/abs/1987PASP…99..191S

Attributes Summary

Methods Summary

 find_group(star, starlist) Find the ids of those stars in starlist which are at a distance less than crit_separation from star. group_stars(starlist) Classify stars into groups.

Attributes Documentation

crit_separation

Methods Documentation

find_group(star, starlist)[source]

Find the ids of those stars in starlist which are at a distance less than crit_separation from star.

Parameters: star : Row Star which will be either the head of a cluster or an isolated one. starlist : Table List of star positions. Columns named as x_0 and y_0, which corresponds to the centroid coordinates of the sources, must be provided. Array containing the ids of those stars which are at a distance less than crit_separation from star.
group_stars(starlist)[source]

Classify stars into groups.

Parameters: starlist : Table List of star positions. Columns named as x_0 and y_0, which corresponds to the centroid coordinates of the sources, must be provided. group_starlist : Table starlist with an additional column named group_id whose unique values represent groups of mutually overlapping stars.