I have a bunch of data points in R^2 (Euclidean plane). But I want to project these onto a 2d integer grid -- that is, there's at most one data point for each integer (x, y) coordinate, and points near each other in the integer grid should also be near each other in the original R^2 space. Is there some method to do this? I'm not necessarily looking for an R function (though that would be nice).
For example, I tried a kind of simulated annealing approach (basically, I threw all the data points onto a rectangular integer grid, and tried to minimize the distances between points), but is there any other method? I'm not too familiar with self-organizing maps, but would using an SOM with # of clusters = # of original data points give me what I want? Any pointers are appreciated! -- View this message in context: http://www.nabble.com/projecting-onto-2d-*integer*-grid--tp23579946p23579946.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
