def phi_X(self, X):
def f(i, j):
if i != j:
return imm(0)
return X[i]
return Matrix(self.nbits, self.nbits, f)
def __identify(app, in_name):
# TODO: identify number of independant inputs
NL = app.nl().vector()
M = app.matrix()
nbits_in = M.ncols()
nbits_out = M.nlines()
if nbits_in != nbits_out:
raise ValueError("do not yet support application with a different\
number of input and output bits!")
mba = MBA(nbits_in)
var_in = mba.var(in_name)
if NL != Vector(len(NL)):
return _identify_nonaffine(app, var_in)
C = EX.ExprCst(mba.from_vec(app.cst()).to_cst(), nbits_out)
if M == Matrix(nbits_out, nbits_in):
# This is just a constant
return C
ret = EX.ExprBV(var_in)
matrix_empty = 0
# Find empty columns in the matrix.
for j in range(nbits_in):
is_zero = reduce(operator.and_, (M.at(i, j) == imm(0)
for i in range(nbits_out)), True)
if is_zero:
matrix_empty |= 1 << j
matrix_and_mask = (~matrix_empty) % (2**nbits_out)
if matrix_empty != 0:
ret = EX.ExprAnd(ret, EX.ExprCst(matrix_and_mask, nbits_out))
if mba.from_vec(M * var_in.vec) ^ (var_in & matrix_empty) == var_in:
# This is a XOR
return EX.ExprXor(ret, C)
raise ValueError("unable to identify an expression")
def add_n_matrix(self, n):
def matrix_v(i, j):
if i == j:
return imm(1)
if i < j:
return imm(0)
if i > j:
mask = (~((1 << (j)) - 1)) & self.max_uint
mask2 = ((1 << (i)) - 1) & self.max_uint
mask &= mask2
return imm((n & mask) == mask)
return Matrix(self.nbits, self.nbits, matrix_v)
def null_matrix(self):
return Matrix(self.nbits, self.nbits)
def cst_matrix(self, cst):
return Matrix(self.nbits, self.nbits, lambda i, j: cst)
def identity(self):
return Matrix.identity(self.nbits)