On 11/15/2009 01:16 AM, David Warde-Farley wrote: > On 14-Nov-09, at 10:57 AM, Bruce Southey wrote: > > >> Is it just that bincount does not count negative numbers? >> If so, then I would strongly argue that is insufficient for creating >> new function. Rather you need to provide a suitable patch to fix >> bincount or replace bincount with a better version. >> > The whole point of bincount is that in the result array, the indices > correspond to _values_ in the original array, i.e. bc = bincount(arr) > then bc[3] gives me the number of 3's that appear in arr. This is lost > if bincount starts reporting negatives. I suppose you could return a > tuple of two arrays, optionally, but I don't know how much use it > would get. > Isn't this indexing invalid if you have a negative value in the original array in the first place? While I have not tried Priit's code (as it is in C), the provided output with negative values does not appear to maintain this property. Really without changing the output type, I do not see how you can keep this indexing property with negative values. So really the comparison has to be with histogram(). > If you really need to do bincount on an array with negative ints, you > can just add -arr.min() to the array first and subtract the same value > when done. Assuming you don't have a huge array this will be very > fast, and can even be done in place. > > David > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > Josef provided the histogram solution using np.arange for the bins that appears to be handle negative values except that the indexing is refers to position not the value. That is the index is value minus the minimum of (zero, min(array)) - which is the indexing as required by Priit's code.
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