Chris - 11 months ago 39

Python Question

**I have a function that I would like to apply to an array of tuples** and I am wondering if there is a clean way to do it.

Normally, I could use

`np.vectorize`

So I can assume that the incoming array is one of:

- tuple
- 1 dimensional array of tuples
- 2 dimensional array of tuples

I can probably write some looping logic but it seems like

`numpy`

This is an example. I am trying to apply the

`tuple_converter`

`array_of_tuples1 = np.array([`

[(1,2,3),(2,3,4),(5,6,7)],

[(7,2,3),(2,6,4),(5,6,6)],

[(8,2,3),(2,5,4),(7,6,7)],

])

array_of_tuples2 = np.array([

(1,2,3),(2,3,4),(5,6,7),

])

plain_tuple = (1,2,3)

# Convert each set of tuples

def tuple_converter(tup):

return tup[0]**2 + tup[1] + tup[2]

# Vectorizing applies the formula to each integer rather than each tuple

tuple_converter_vectorized = np.vectorize(tuple_converter)

print(tuple_converter_vectorized(array_of_tuples1))

print(tuple_converter_vectorized(array_of_tuples2))

print(tuple_converter_vectorized(plain_tuple))

Desired Output for

`array_of_tuples1`

`[[ 6 11 38]`

[54 14 37]

[69 13 62]]

Desired Output for

`array_of_tuples2`

`[ 6 11 38]`

Desired Output for

`plain_tuple`

`6`

But the code above produces this error

`<ipython-input-209-fdf78c6f4b13> in tuple_converter(tup)`

10

11 def tuple_converter(tup):

---> 12 return tup[0]**2 + tup[1] + tup[2]

13

14

IndexError: invalid index to scalar variable.

Answer

*array_of_tuples1* and *array_of_tuples2* are not actually arrays of tuples, but just 3- and 2-dimensional arrays of integers:

```
In [1]: array_of_tuples1 = np.array([
...: [(1,2,3),(2,3,4),(5,6,7)],
...: [(7,2,3),(2,6,4),(5,6,6)],
...: [(8,2,3),(2,5,4),(7,6,7)],
...: ])
In [2]: array_of_tuples1
Out[2]:
array([[[1, 2, 3],
[2, 3, 4],
[5, 6, 7]],
[[7, 2, 3],
[2, 6, 4],
[5, 6, 6]],
[[8, 2, 3],
[2, 5, 4],
[7, 6, 7]]])
```

So, instead of vectorizing your function, because it then will basically for-loop through the elements of the array (integers), you should apply it on the suitable axis (the axis of the "tuples") and not care about the type of the sequence:

```
In [6]: np.apply_along_axis(tuple_converter, 2, array_of_tuples1)
Out[6]:
array([[ 6, 11, 38],
[54, 14, 37],
[69, 13, 62]])
In [9]: np.apply_along_axis(tuple_converter, 1, array_of_tuples2)
Out[9]: array([ 6, 11, 38])
```