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_statistic_2d.html 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
