# [Numpy-discussion] efficient 3d histogram creation

josef.pktd@gmai... josef.pktd@gmai...
Sun May 3 19:36:09 CDT 2009

```On Sun, May 3, 2009 at 8:15 PM, Chris Colbert <sccolbert@gmail.com> wrote:
> in my endless pursuit of perfomance, i'm searching for a quick way to create
> a 3d histogram from a 3d rgb image.
>
> Here is what I have so far for a (16,16,16) 3d histogram:
>
> def hist3d(imgarray):
>     histarray = N.zeros((16, 16, 16))
>     temp = imgarray.copy()
>     (i, j) = imgarray.shape[0:2]
>     temp = (temp - temp % 16) / 16
>     for a in range(i):
>         for b in range(j):
>             (b1, b2, b3) = temp[a, b, :]
>             histarray[b1, b2, b3] += 1
>     return histarray
>
> this works, but takes about 4 seconds for a 640x480 image.
>
> I tried doing the inverse of my previous post, namely replacing the nested
> for loop with:
> histarray[temp[:,:,0], temp[:,:,1], temp[:,:,2]] += 1
>
>
> but that doesn't work for whatever reason. It gives me number, but they're
> incorrect.
>
> Any ideas?

I'm not sure what exactly you need, but did you look at np.histogramdd ?

reading the help file, this might work

numpy.histogramdd(temp[:,:,0].ravel(), temp[:,:,1].ravel(),
temp[:,:,2].ravel(), bins=16)

but I never used histogramdd.

also looking at the source of numpy is often very instructive, lots of
good tricks to find in there: np.source(np.histogramdd).

Josef
```