Efficiently get indices of histogram bins in Python

Question

Short Question

I have a large 10000x10000 elements image, which I bin into a few hundred different sectors/bins. I then need to perform some iterative calculation

Answer 1

You can halve the computation time by sorting the array first, then use np.searchsorted.

vals = np.random.random(1e8)
vals.sort()

nbins = 100
bins = np.linspace(0, 1, nbins+1)
ind = np.digitize(vals, bins)

results = [func(vals[np.searchsorted(ind,j,side='left'):
                     np.searchsorted(ind,j,side='right')])
           for j in range(1,nbins)]

Using 1e8 as my test case, I go from 34 seconds of computation to about 17.