On Wed, May 2, 2012 at 5:45 PM, Moroney, Catherine M (388D) < catherine.m.moro...@jpl.nasa.gov> wrote:
> Thanks to Perry for some very useful off-list conversation. I realize > that > I wasn't being clear at all in my earlier description of the problem so > here it is > in a nutshell: > > Find the best match in an array t(5000, 7) for a single vector e(7). Now > scale > it up so e is (128, 512, 7) and I want to return a (128, 512) array of the > t-identifiers > that are the best match for e. "Best match" is defined as the minimum > Euclidean distance. > > It sounds like you want to find the nearest neighbor to a point in a high-dimensional space. This sounds like a job for a spacial data structure like a KD-tree. See: http://docs.scipy.org/doc/scipy/reference/spatial.html http://mloss.org/software/view/143/ http://www.mrzv.org/software/pyANN/ etc. -Kevin
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
