The rapid growth of imaging surveys, from space and ground-based facilities has created the need to develop alternative and reliable methods to morphologically segregate galaxies over large datasets. Unfortunately, for samples of galaxies >103, the traditional approach of visual classification becomes unfeasible. Moreover, there is a clear need to have a classification method that it is objective and repeatable over time, not possible under human selection methods. Recognizing this, We have developed PyCA (Menanteau et al. 2006), a Python public and open source module that computes Concentration (C) and Asymmetry (A) of galaxies from, preferentially, the by-products of SExtractor runs. Many studies have been devoted to study the morphological properties of HST (WFPC2 and ACS) galaxies using structural parameters and their link to visual morphologies establishing a firm relation between Concentration and Asymmetry, and traditional visual morphologies based on Hubble types. However, until now, there were no public recipes or code available to the astronomical community to compute and compare them. In the tradition of open source and science software, such as IRAF, SExtractor and BPZ, PyCA is publicly available and open source to the whole community. It has been tested to run in Linux, Solaris and in Mac OS X. PyCA has been rapidly adopted by the extra-galactic astronomy community and several ACS related papers have already used it for the morphological classification of galaxies. PyCA can be downloaded from http://acs.pha.jhu.edu/~felipe/PyCA
This research is supported by NASA grant NAG5-7697.
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