So. I am trying to access and modify the penultimate individual element of a series of Numpy arrays.
array_1D = np.array([10,11,12,13, 14])
array_2D = np.array([[20,30,40,50,60], [43,54,65,76,87], [11,22,33,44,55]])
array_3D = np.array([[[1,2,3,4,5], [11,21,31,41,51]], [[11,12,13,14,15], [51,52,53,54,5]]])
arrays = [array_1D, array_2D, array_3D]
I wanted to do this programmatically as opposed to manually, to learn a bit deeper.
What I have is:
for array in arrays:
print(array) # Before
print('CHANGE TEN')
array[..., -2] = 10
print(array, end='\n--------\n\n') # After
Which returns:
[10 11 12 13 14]
CHANGE TEN
[10 11 12 10 14]
--------
[[20 30 40 50 60]
[43 54 65 76 87]
[11 22 33 44 55]]
CHANGE TEN
[[20 30 40 10 60]
[43 54 65 10 87]
[11 22 33 10 55]]
--------
[[[ 1 2 3 4 5]
[11 21 31 41 51]]
[[11 12 13 14 15]
[51 52 53 54 5]]]
CHANGE TEN
[[[ 1 2 3 10 5]
[11 21 31 10 51]]
[[11 12 13 10 15]
[51 52 53 10 5]]]
--------
As you can see this syntax currently accesses the penultimate individual element of all elements along the major axis.
Is there a neat way to access the penultimate individual element of an array of arbitrary dimension? (In this case that would mean a single integer.)
Strange application I know. I'm interested in understanding the limitations germane to working with arrays of arbitrary dimension.
(I googled a bit and searched SO to no avail. Google Fu not strong apparently.)
Here you go:
array_1D = np.array([10,11,12,13, 14])
array_2D = np.array([[20,30,40,50,60], [43,54,65,76,87], [11,22,33,44,55]])
array_3D = np.array([[[1,2,3,4,5], [11,21,31,41,51]], [[11,12,13,14,15], [51,52,53,54,5]]])
arrays = [array_1D, array_2D, array_3D]
for array in arrays:
print(array) # Before
print('CHANGE TEN')
array[tuple([-2] * array.ndim)] = 10
print(array, end='\n--------\n\n') # After
print(array_1D[-2], array_2D[-2,-2], array_3D[-2,-2,-2])
Output:
10 10 10