Removing Loops In Numpy For A Simple Matrix Assignment

How can I remove loops in this simple matrix assignment in order to increase performance? nk,ncol,nrow=index.shape for kk in range(0,nk): for ii in range(0,nrow): for jj

Solution 1:

If I understand it correctly, you are looking for this:

uniq, counter = np.unique(index, return_counts=True, axis=0)

The uniq should give you unique set of x,ys (x,y will be flattened into a single array) and counter corresponding number of repetitions in the array index

EDIT:

Per OP's comment below:

xx,yy = np.meshgrid(np.arange(ncol),np.arange(nrow))
idx, counts = np.unique(np.vstack((index.flatten(),np.repeat(yy.flatten(),nk),np.repeat(xx.flatten(),nk))), return_counts=True,axis=1)
counter[tuple(idx)] = counts