I have a n x n array, and want to receive its outline values. For example,
[4,5,6,7]
[2,2,6,3]
It's probably slower than the alternatives mentioned in the other answers because it's creating a mask (which was my use-case then) it can be used in your case:
def mask_borders(arr, num=1):
mask = np.zeros(arr.shape, bool)
for dim in range(arr.ndim):
mask[tuple(slice(0, num) if idx == dim else slice(None) for idx in range(arr.ndim))] = True
mask[tuple(slice(-num, None) if idx == dim else slice(None) for idx in range(arr.ndim))] = True
return mask
As already said this creates and returns a mask
where the borders are masked (True
):
>>> mask_borders(np.ones((5,5)))
array([[ True, True, True, True, True],
[ True, False, False, False, True],
[ True, False, False, False, True],
[ True, False, False, False, True],
[ True, True, True, True, True]], dtype=bool)
>>> # Besides supporting arbitary dimensional input it can mask multiple border rows/cols
>>> mask_borders(np.ones((5,5)), 2)
array([[ True, True, True, True, True],
[ True, True, True, True, True],
[ True, True, False, True, True],
[ True, True, True, True, True],
[ True, True, True, True, True]], dtype=bool)
To get the "border" values this needs to be applied with boolean indexing to your array:
>>> arr = np.array([[4,5,6,7], [2,2,6,3], [4,4,9,4], [8,1,6,1]])
>>> arr[mask_borders(arr)]
array([4, 5, 6, 7, 2, 3, 4, 4, 8, 1, 6, 1])