Сгенерировать квадратную матрицу

from random import randint
 
lst = ([[randint(-100,100) for j in range(100)] for i in range(100)])
 
def diagonal(l,c=0):
    s = 0
    i = 0
    n = len(l)
    while i < n:
        if c == 1:
            if l[i][i] > 0:
                s += l[i][i]  ** 2
        else:
            if l[i][n-i-1] < 0:
                s += l[i][n-i-1] ** 2
        i += 1
    return s
 
sum_gl_diag = diagonal(lst, 1)
sum_pob_diag = diagonal(lst)
print("{} - {} = {}".format(sum_gl_diag, sum_pob_diag, sum_gl_diag - sum_pob_diag))

lst = ([[randint(-100,100) for j in range(100)] for i in range(100)])

from random import randint
n = 100
lst = [[randint(-100, 100) for _ in range(n)] for _ in range(n)]
ss1 = sum(lst[x][x]**2 for x in range(n) if lst[x][x] >= 0)
ss2 = sum(lst[n-1-x][x]**2 for x in range(n) if lst[n-1-x][x] < 0)
print(ss1 - ss2)

from random import randint
n = 100
lst = [[randint(-100, 100) for _ in range(n)] for _ in range(n)]
ss3 = sum((lst[x][x]**2 if lst[x][x] >= 0 else 0) - (lst[n-1-x][x]**2 if lst[n-1-x][x] < 0 else 0) for x in range(n))
print(ss3)

from random import randint
 
def totals(x, flag):
    sum_square = 0
    for row,column in zip(*x):
        elem = matrix[row][column]
        if int(elem > 0) == flag :
            sum_square += elem ** 2
    return sum_square
 
size = 100
matrix = [[randint(-100,100) for _ in range(size)] for _ in range(size)]
sum_main = totals((range(size),range(size)) ,flag = 1)
sum_secondary = totals((range(size),range(size)[::-1]) ,flag = 0)
print(sum_main - sum_secondary)

import numpy as np
 
matrix_100_100 = np.random.uniform(low=-100, high=101, size=(100,100))
m_diag = matrix_100_100.diagonal()
opp_diag = np.diag(np.fliplr(matrix_100_100))
print(sum(i**2 for i in m_diag if i > 0) - sum(i**2 for i in opp_diag if i < 0))

import numpy as np
 
matrix_100_100 = np.random.uniform(low=-100, high=101, size=(100,100))
print(sum(i**2 for i in matrix_100_100.diagonal() if i > 0) - sum(i**2 for i in np.diag(np.fliplr(matrix_100_100)) if i < 0))