On Tue, Sep 10, 2013 at 9:59 AM, Andreas Hilboll <lists@hilboll.de> wrote:

On 10.09.2013 15:52, David Reed wrote:

...

Hi there,

Is there a faster way to perform a 2D Histogram from a 2D matrix than what I have below:

def spatial_histogram(frame, n_bins): shape = frame.shape

h_len = shape[0]/n_bins w_len = shape[1]/n_bins

h_ind = range(0, shape[0], h_len) w_ind = range(0, shape[1], w_len)

max_val = 255*h_len*w_len

out = np.empty((n_bins, n_bins), np.uint8)

for ii in range(n_bins): for jj in range(n_bins): out[ii, jj] = np.sum(frame[h_ind[ii]:h_ind[ii]+h_len, w_ind[jj]:w_ind[jj]+w_len])/max_val*255

return out

Should I try implementing this in Cython, or is there something I can do in Numpy?

Thanks!

David,

are you aware of Scipy's binne_statistic_2d method?

http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.binned_stati...

That's modeled after numpy.histogram2d, and just calculates other statistics besides histogram Josef

At first glance it can do what you're trying to do.

Andreas.

_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion