numpy: get ndarray's value from an index array

Question

I have high dimension numpy array, the dimension of the array is not fixed. I need to retrieve the value with a index list, the length of the index list is the same as the dimension of the numpy array.

In other words, I need a function:

def get_value_by_list_index(target_array, index_list):
  # len(index_list) = target_array.ndim
  # target array can be in any dimension
  # return the element at index specified on index list

For example, for a 3-dimension array, data and a list [i1, i2, i3], I the function should return data[i1][i2][i3].

Is there a good way to achieve this task?

target_array[tuple(index_list)] which is the same as target_array[i1,i2,i3] — hpaulj
– hpaulj, Commented Mar 21, 2022 at 21:24
@hpaulj uff, I didn't even know that; what an API nightmare: let idx=[1,2] be our index list, then arr[idx] gives the second and third row of a matrix, but if idx=(1,2), the same statement yields the second row, third column element — Marcus Müller
– Marcus Müller, Commented Mar 21, 2022 at 21:28
Often in python, list and tuple can be used interchangably, but in array indexing the difference is significant. It's the comma that makes a tuple, more so than the (), which are just used to reduce ambiguities. @MarcusMüller — hpaulj
– hpaulj, Commented Mar 21, 2022 at 21:45
@hpaulj fully aware of that, it's just that the type sensitivity to the index container being a tuple or any other iterable is a bit of a footgun if you're passing these around through an API. This is more of a realization than a hm, numpy critique, I guess. — Marcus Müller
– Marcus Müller, Commented Mar 21, 2022 at 21:50

Marcus Müller · Accepted Answer · 2022-03-21 21:25:02Z

1

If you know the ndarray is actually containing a type that is just a number well-representable by python types:

source_array.item(*index_iterable)

will do the same.

If you need to work with ndarrays of more complex types that might not have a python built-in type representation, things are harder.

You could implement exactly what you sketch in your comment:

data[i1][i2][i3]

# note that I didn't like the name of your function
def get_value_by_index_iterable(source_array, index_iterable):
  subarray = source_array
  for index in index_iterable:
    subarray = subarray[index]
  return subarray

edited Mar 21, 2022 at 21:25

answered Mar 21, 2022 at 21:10

Marcus Müller

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