Numpy 2d array - select multiple elements without a for loop

Question

I maintain some code and I run across something like:

    travel_time_vec = np.zeros(...)
    for v in some_indexes: # some_indexes is a list of row indexes
        traveltimes = traveltime_2d_array[v, list_of_column_indexes]
        best_index = np.argmin(traveltimes)
        travel_time_vec[v] = traveltimes[best_index]

I would like to drop the for loop and do all the operations below at once - but naively asking for traveltime_2d_array[some_indexes, list_of_column_indexes] results in:

{IndexError}shape mismatch: indexing arrays could not be broadcast together with shapes (4,) (8,)

Answer 1

Got it - I need to pass the some_indexes as a list of lists so numpy broadcasts each one to the columns in list_of_column_indexes. So this:

travel_time_vec = np.zeros(...)
# newaxis below tranforms [1, 2, 3] to [[1], [2], [3]]
traveltimes = traveltime_2d_array[np.array(some_indexes)[:, np.newaxis], 
                                  list_of_column_indexes]
# get the index of the min time on each row
best_index = np.argmin(traveltimes, axis=1)
travel_time_vec[some_indexes] = traveltimes[:, best_index]

works as expected, and no more looping