[Numpy-discussion] efficient 3d histogram creation
Chris Colbert
sccolbert@gmail....
Mon May 4 15:00:31 CDT 2009
i'll take a look at them over the next few days and see what i can hack out.
Chris
On Mon, May 4, 2009 at 3:18 PM, David Huard <david.huard@gmail.com> wrote:
>
>
> On Mon, May 4, 2009 at 7:00 AM, <josef.pktd@gmail.com> wrote:
>
>> On Mon, May 4, 2009 at 12:31 AM, Chris Colbert <sccolbert@gmail.com>
>> wrote:
>> > this actually sort of worked. Thanks for putting me on the right track.
>> >
>> > Here is what I ended up with.
>> >
>> > this is what I ended up with:
>> >
>> > def hist3d(imgarray):
>> > histarray = N.zeros((16, 16, 16))
>> > temp = imgarray.copy()
>> > bins = N.arange(0, 257, 16)
>> > histarray = N.histogramdd((temp[:,:,0].ravel(), temp[:,:,1].ravel(),
>> > temp[:,:,2].ravel()), bins=(bins, bins, bins))[0]
>> > return histarray
>> >
>> > this creates a 3d histogram of rgb image values in the range 0,255 using
>> 16
>> > bins per component color.
>> >
>> > on a 640x480 image, it executes in 0.3 seconds vs 4.5 seconds for a for
>> > loop.
>> >
>> > not quite framerate, but good enough for prototyping.
>> >
>>
>> I don't think your copy to temp is necessary, and use reshape(-1,3) as
>> in the example of Stefan, which will avoid copying the array 3 times.
>>
>> If you need to gain some more speed, then rewriting histogramdd and
>> removing some of the unnecessary checks and calculations looks
>> possible.
>
>
> Indeed, the strategy used in the histogram function is faster than the one
> used in the histogramdd case, so porting one to the other should speed
> things up.
>
> David
>
>
>>
>> Josef
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>
>
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