def incidence_matrix_from_multiplicities(n, mu):
m = sum(mu.values())
A = Matrix(n, m)
j = 0
for support, multiplicity in mu.items():
if multiplicity < 0:
raise ValueError('invalid multiplicity')
if any(x not in range(n) for x in support):
raise ValueError('invalid support')
col = [1 if i in support else 0 for i in range(n)]
for _ in range(multiplicity):
A.set_column(j, col)
j += 1
return A
def are_CCZ_equivalent(s1, s2):
s1, s2 = convert_sboxes(s1, s2)
assert_equal_sizes(s1, s2)
lin1 = s1.is_linear()
lin2 = s2.is_linear()
if lin1 ^ lin2:
return False
if lin1 and lin2:
return True
inp, out = s1.m, s1.n
M1 = Matrix(GF(2), 1 + inp + out, 2**inp)
M2 = Matrix(GF(2), 1 + inp + out, 2**inp)
for x in range(2**inp):
M1.set_column(x, tobin(1, 1) + tobin(x, inp) + tobin(s1[x], out))
M2.set_column(x, tobin(1, 1) + tobin(x, inp) + tobin(s2[x], out))
L1 = LinearCode(M1)
L2 = LinearCode(M2)
# Annoying: this is not checked in "is_permutation_equivalent" code!
# raises a TypeError instead
if L1.generator_matrix().nrows() != L2.generator_matrix().nrows():
return False
return L1.is_permutation_equivalent(L2)
