def test_reshape(self):
from numpypy import arange, array, dtype, reshape
a = arange(12)
b = reshape(a, (3, 4))
assert b.shape == (3, 4)
a = range(12)
b = reshape(a, (3, 4))
assert b.shape == (3, 4)
a = array(range(105)).reshape(3, 5, 7)
assert reshape(a, (1, -1)).shape == (1, 105)
assert reshape(a, (1, 1, -1)).shape == (1, 1, 105)
assert reshape(a, (-1, 1, 1)).shape == (105, 1, 1)
def test_reshape(self):
from numpypy import arange, array, dtype, reshape
a = arange(12)
b = reshape(a, (3, 4))
assert b.shape == (3, 4)
a = range(12)
b = reshape(a, (3, 4))
assert b.shape == (3, 4)
a = array(range(105)).reshape(3, 5, 7)
assert reshape(a, (1, -1)).shape == (1, 105)
assert reshape(a, (1, 1, -1)).shape == (1, 1, 105)
assert reshape(a, (-1, 1, 1)).shape == (105, 1, 1)
def solve(par):
N, mat = par
# construct the sum of each column in side the array
# so kadane's algorithm can be used in each sub row sum
for j in range(N):
for i in range(1, N):
mat[i, j] += mat[i - 1, j]
maxSum = -1 * INF
for i in range(N):
for j in range(i, N):
array = [mat[j, k] - mat[i, k] for k in range(N)]
maxSum = max(maxSum, kadane(array))
return maxSum
if __name__ == '__main__':
sys.stdin = open('input.txt', 'r')
N = int(input())
mat = []
while True:
try:
mat += map(int, raw_input().split())
except:
break
mat = np.array(mat)
mat = np.reshape(mat, (N, N))
print(solve((N, mat)))
