u = np.array([[100., 100., 100., 100., 100.],
             [100.,  0.,    0.,   0.,  100.],
             [100.,  0.,    0.,   0., 100.],
             [100.,  0.,    0.,   0., 100.],
             [100., 100., 100., 100., 100.]])

[[100. 100. 100. 100. 100.]
[100.  50.  25.  50. 100.]
[100.  25.   0.  25. 100.]
[100.  50.  25.  50. 100.]
[100. 100. 100. 100. 100.]]

import numpy as np

#example array
x = np.array([[100.,   2.,   3.,   7., 100.],
              [100.,   5.,   3.,   7., 100.],
              [100.,   3.,   6.,   3., 100.],
              [50.,   4.,   5.,   2., 100.],
              [100., 100., 100., 100., 100.]])

lbarrier = (np.size(x, 1))+1
rbarrier = (np.size(x, 1))-1
bbarrier = (np.size(x, 0))-1




#inner vals
itops = x[0:bbarrier][1:rbarrier][0][1:rbarrier]
ibot = x[0:bbarrier][1:rbarrier][-1][1:rbarrier]
ileft = x[1:bbarrier,1]
iright = x[1:bbarrier,-2]



#edge vals
etops = np.array(x[0:][0:][0][1:-1])
ebot = np.array(x[0:][0:][-1][1:-1])
eleft = np.array(x[1:bbarrier, 0])
eright = np.array(x[1:bbarrier, -1])

In [49]: from scipy import ndimage

In [50]: import numpy as np

In [51]: k
Out[51]:
array([[0.  , 0.25, 0.  ],
       [0.25, 0.  , 0.25],
       [0.  , 0.25, 0.  ]])

In [52]: u = np.zeros((3,3))

In [53]: ndimage.convolve(u, k, mode='constant', cval=100.0)
Out[53]:
array([[50., 25., 50.],
       [25.,  0., 25.],
       [50., 25., 50.]])

In [54]: