[Numpy-discussion] Automatic number of bins for numpy histograms

[Neil Girdhar]

If you're going to C, is there a reason not to go to C++ and include the
already-written Boost code?  Otherwise, why not use Python?

On Tue, Apr 14, 2015 at 7:24 PM, Jaime Fernández del Río <
jaime.frio at gmail.com> wrote:

> On Tue, Apr 14, 2015 at 4:12 PM, Nathaniel Smith <njs at pobox.com> wrote:
>
>> On Mon, Apr 13, 2015 at 8:02 AM, Neil Girdhar <mistersheik at gmail.com>
>> wrote:
>> > Can I suggest that we instead add the P-square algorithm for the dynamic
>> > calculation of histograms?
>> > (
>> http://pierrechainais.ec-lille.fr/Centrale/Option_DAD/IMPACT_files/Dynamic%20quantiles%20calcultation%20-%20P2%20Algorythm.pdf
>> )
>> >
>> > This is already implemented in C++'s boost library
>> > (
>> http://www.boost.org/doc/libs/1_44_0/boost/accumulators/statistics/extended_p_square.hpp
>> )
>> >
>> > I implemented it in Boost Python as a module, which I'm happy to share.
>> > This is much better than fixed-width histograms in practice.  Rather
>> than
>> > adjusting the number of bins, it adjusts what you really want, which is
>> the
>> > resolution of the bins throughout the domain.
>>
>> This definitely sounds like a useful thing to have in numpy or scipy
>> (though if it's possible to do without using Boost/C++ that would be
>> nice). But yeah, we should leave the existing histogram alone (in this
>> regard) and add a new name for this like "adaptive_histogram" or
>> something. Then you can set about convincing matplotlib and friends to
>> use it by default :-)
>>
>
> Would having a negative number of bins mean "this many, but with optimized
> boundaries" be too clever an interface?
>
> I have taken a look at the paper linked, and the P-2 algorithm would not
> be too complicated to implement from scratch, although it would require
> writing some C code I'm afraid.
>
> Jaime
>
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