Hi Devs, attached is a diff that adds 3 new modes to the graduated symbol renderer, including Jenks' Natural Breaks Optimisation algorithm, a standard deviation classification algorithm, and the 'pretty' algorithm from the R statistical programming language. An explanation of the algorithms is provided as comments in-code, and you can also have a look here: http://www.carsonfarmer.com/?p=761 for the initial Python version, along with a brief overview of the algorithms etc. I'd really appreciate any comments, suggestions, or fixes, as I'm not really a C++ programmer. I'm sure there are a few spots where things could be sped up, especially in the Jenks algorithm. Right now I'm using a random sample to speed things up, but I'm sure others more familiar with C++ could find other speed improvements. I don't really want to commit this directly, again mainly because I'm not really confident in my C++ abilities, but if it would make it easier, I can also add the patch as an enhancement ticket?
Thanks, Carson -- Carson J. Q. Farmer ISSP Doctoral Fellow National Centre for Geocomputation National University of Ireland, Maynooth, http://www.carsonfarmer.com/
jenks_class.diff
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