On Wed, Apr 17, 2013 at 10:46 AM, Todd <[email protected]> wrote: > x,i=numpy.unique(y, return_inverse=True) > f=[numpy.where(i==ind) for ind in range(len(x))] > > >
A better version would be (np.where returns tuples, but we don't want tuples): x,i=numpy.unique(y, return_inverse=True) f=[numpy.where(i==ind)[0] for ind in range(len(x))] You can also do it this way, but it is much harder to read IMO: x=numpy.unique(y) f=numpy.split(numpy.argsort(y), numpy.nonzero(numpy.diff(numpy.sort(y)))[0]+1) This version figures out the indexes needed to put the values of y in sorted order (the same order x uses), then splits it into sub-arrays based on value. The principle is simpler but the implementation looks like clear to me. Note that these are only guaranteed to work on 1D arrays, I have not tested them on multidimensional arrays
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