[
  [ [.3 .1 .2]
    [.2 .1 .5]
    ... (224 lists)
    [.6 .9 .4] ]

    ... (224 lists)

  [ [.1 .7 .5]
    [.3 .8 .4]
    ... (224 lists)
    [.2 .6 .9] ]
]

a = 1st list items
b = 2nd list items

[
  [ [a0-b0 a1-b1 a2-b2]
    [.. .. ..]
    ... (224 lists)
    [.. .. ..] ]

    ... (224 lists)

  [ [.. .. ..]
    [.. .. ..]
    ... (224 lists)
    [.. .. ..] ]
]

[  [sqrt(A0**2+B0**2+C0**2) .. ..]
   ... (224 lists)
   [.. .. ..]
]

# Let sqrt(A0**2+B0**2+C0**2) = z. So we get :
[  [z0 z1 z2]
   ... (224 lists)
   [.. .. ..]
]

# two nested lists are tupfl and t2
difflay1 = [ [ [0 for i in range(3)] for i in range(224)] for i in range(224)]
rtsqlay2 = [ [0 for i in range(3)] for i in range(224)]

for i in range(224):
    for j in range(224):
        for k in range(3):
            difflay1[i][j][k] = tupfl[i][j][k] - t2[i][j][k]
for i in range(224):
    for j in range(224):
        for k in range(3):
            alpha = difflay1[i][j][0]
            beta = difflay1[i][j][1]
            theta = difflay1[i][j][2]
            rtsqlay2[i][k] = math.sqrt(alpha**2 + beta**2 + theta**2)

def nested_sum(L):
    total = 0
    for i in L:
        if isinstance(i, list):
            total += nested_sum(i)
        else:
            total += i
    return total
print(nested_sum(rtsqlay2))