[Numpy-tickets] [NumPy] #928: histogramdd() overflow error on high-dimension arrays

[NumPy]

#928: histogramdd() overflow error on high-dimension arrays
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 Reporter:  jvansanten  |        Owner:  somebody
     Type:  defect      |       Status:  new     
 Priority:  normal      |    Milestone:          
Component:  numpy.lib   |      Version:  none    
 Severity:  normal      |   Resolution:          
 Keywords:              |  
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Old description:

> When histogramdd() is called on a large array (say, 5 dimensions with 100
> bins each), it tries to create a flat array of the bins. The size of the
> flat array is given by nbin.prod(). prod() uses the dtype of nbin by
> default (int32), which on arrays like the example above overflows into a
> negative integer, throwing an error.
>
> This is of course not a problem until one starts working with gigantic
> histograms, but it can be tricky nonetheless. Forcing nbin.prod() to use
> a long would clean this up nicely (I think).

New description:

 When histogramdd() is called on a large array (say, 5 dimensions with 100
 bins each), it tries to create a flat array of the bins. The size of the
 flat array is given by nbin.prod(). prod() uses the dtype of nbin by
 default (int32), which on arrays like the example above overflows into a
 negative integer, throwing an error.

 This is of course not a problem until one starts working with gigantic
 histograms, but it can be tricky nonetheless. Forcing nbin.prod() to use a
 long would clean this up nic

Comment (by charris):

 Yes they can -- on 64 bits. So it would be worth booting up a 64 bit
 system to see what the default sizes are. I suspect the default numpy type
 for array indices should be intp.

-- 
Ticket URL: <http://scipy.org/scipy/numpy/ticket/928#comment:2>
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