[Numpy-discussion] efficient 3d histogram creation

josef.pktd@gmai... josef.pktd@gmai...
Wed May 6 18:30:00 CDT 2009


On Wed, May 6, 2009 at 6:06 PM, Chris Colbert <sccolbert@gmail.com> wrote:
> I decided to hold myself over until being able to take a hard look at the
> numpy histogramdd code:
>
> Here is a quick thing a put together in cython. It's a 40x speedup over
> histogramdd on Vista 32 using the minGW32 compiler. For a (480, 630, 3)
> array, this executed in 0.005 seconds on my machine.
>
> This only works for arrays with uint8 data types having dimensions (x, y, 3)
> (common image format). The return array is a (16, 16, 16) equal width bin
> histogram of the input.
>
> If anyone wants the cython C-output, let me know and I will email it to you.
>
> If there is interest, I will extend this for different size bins and aliases
> for different data types.
>
> Chris
>
> import numpy as np
>
> cimport numpy as np
>
> DTYPE = np.uint8
> DTYPE32 = np.int
>
> ctypedef np.uint8_t DTYPE_t
> ctypedef np.int_t DTYPE_t32
>
> def hist3d(np.ndarray[DTYPE_t, ndim=3] img):
>     cdef int x = img.shape[0]
>     cdef int y = img.shape[1]
>     cdef int z = img.shape[2]
>     cdef int addx
>     cdef int addy
>     cdef int addz
>     cdef np.ndarray[DTYPE_t32, ndim=3] out = np.zeros([16, 16, 16],
> dtype=DTYPE32)
>     cdef int i, j, v0, v1, v2
>
>
>     for i in range(x):
>         for j in range(y):
>             v0 = img[i, j, 0]
>             v1 = img[i, j, 1]
>             v2 = img[i, j, 2]
>             addx = (v0 - (v0 % 16)) / 16
>             addy = (v1 - (v1 % 16)) / 16
>             addz = (v2 - (v2 % 16)) / 16
>             out[addx, addy, addz] += 1
>
>     return out
>

Thanks for the example for using cython. Once I figure out what the
types are, cython will look very convenient for loops, and pyximport
takes care of the compiler.

Josef

import pyximport; pyximport.install()
import hist_rgb    #name of .pyx files

import numpy as np
factors = np.random.randint(256,size=(480, 630, 3))
h = hist_rgb.hist3d(factors.astype(np.uint8))
print h[:,:,0]


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