Detail-preserving 2D binning, part 1: the appetizer

(Sorry about the hiatus, there’s been a period filled with that noblest of Japanese traditions: paperwork!)

If you want to do fitting of a 2D image, you want to preserve the information in the entire image. 2D fitting is quite computationally intensive, so you still want to reduce the number of pixels in your images. Methods I have seen published, are occasionally quite poor at preserving detail, but I’ve played with a type of binning (quite similar to the mathematical concept of k-d trees) that does preserve this: Behold the coolness in the following plots, which are different zoom levels of the same scattering pattern. On the vertical axis is the azimuthal angle, on the horizontal axis q (in reciprocal meters). An explanation will follow in the near future, but you’re welcome to write to me for the scoop.

Pretty cool, huh! And since the errors of the intensity of each bin are known, fitting is not affected by the differences in area!



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