as_strided in numpy.lib.stride_tricks

Used to produce an effect similar to a sliding serial port

1D sliding window

from numpy.lib import stride_tricks

def sliding_window_1d(a, window):
    shape = (len(a)-window+1, window)
    strides = (a.itemsize, a.itemsize)
    ret = stride_tricks.as_strided(Z, shape=shape, strides=strides)
    return ret

Z = np.arange(10)
R = sliding_window_1d(Z, 4)
print(R)

[[0 1 2 3]
 [1 2 3 4]
 [2 3 4 5]
 [3 4 5 6]
 [4 5 6 7]
 [5 6 7 8]
 [6 7 8 9]]

Note that the return value is a view, not an entity, you need to use copy()it to turn it into an entity

print(R.strides)
print(R.copy().strides)

(4, 4)
(16, 4)

2D sliding window

from numpy.lib import stride_tricks

def sliding_window_2d(a, window):
    h, w = a.shape
    hh, ww = window
    i = a.itemsize
    shape=(h-hh+1, w-ww+1, hh, ww)
    strides=(w*i, i, w*i, i)
    ret = stride_tricks.as_strided(a, shape=shape, strides=strides)
    return ret

a = np.arange(9).reshape(3, 3)
print(a)
print(sliding_window_2d(a, (2, 2)))

[[0 1 2]
 [3 4 5]
 [6 7 8]]
 
[[[[0 1]
   [3 4]]
  [[1 2]
   [4 5]]]

 [[[3 4]
   [6 7]]
  [[4 5]
   [7 8]]]]