Python numpy array sum over certain indices

The accepted a[indices].sum() approach copies data and creates a new array, which might cause problem if the array is large. np.sum actually has an argument to mask out colums, you can just do

np.sum(a, where=[True, False, True, False])

Which doesn't copy any data.

The mask array can be obtained by:

mask = np.full(4, False)
mask[np.array([0,2])] = True

You can use sum directly after indexing with indices:

a = np.array([1,2,3,4])
indices = [0, 2] 
a[indices].sum()