def reduction(self, exp):
xls = Xslxsaver()
xls.create_worksheet(exp)
self.otimizator = Ot()
exp_sorted = sorted(exp, reverse=True)
self.mdegree = exp_sorted[0]
self.max_collum = (2 * exp_sorted[0]) - 1
nr = self._calc_NR(exp_sorted)
self.matrix = self._generate_matrix()
exp_sorted.remove(self.mdegree)
j = 0
for i in range(0, len(exp_sorted)):
self._reduce_first(self.matrix, exp_sorted[i])
xls.save(self.matrix, "step_reduction_" + str(j))
j = j + 1
for i in range(0, nr):
self._reduce_others(self.matrix, exp_sorted)
j = j + 1
xls.save(self.matrix, "step_reduction_" + str(j))
# print "Sem remocoes"
# print_matrix(self.matrix)
# print "Size of Columns ", len(self.matrix)
print "Finish Reducing..."
# self.matrix_copy = copy.deepcopy(self.matrix)
# xls.save(self.matrix, 'Not Optimized_1')
# print_matrix(self.matrix)
# t = self.reduce_matrix(self.mdegree, self.matrix)
# print_matrix(t)
self._remove_repeat(self.matrix)
self.clean(self.matrix)
# xls.save_complete(self.matrix)
self.matrix = self.otimizator.sort(self.matrix)
self.clean(self.matrix)
self.matrix = self.reduce_matrix(self.mdegree, self.matrix)
# print_matrix(self.matrix)
xls.save(self.matrix, "Not Optimized")
self.p, self.matrix = self.otimizator.optimize(self.matrix, self.mdegree, xls)
self._remove_one(self.matrix)
# print_matrix(self.matrix)
row = [-1 for x in xrange(self.mdegree)]
self.matrix.append(row)
count = self._count_xor(self.matrix, self.p)
# count = count + self.countMatchs(otimizator.matches)
xls.save(self.matrix, "Optimized")
# self.p_, self.matrix_copy = otimizator.optimize(self.matrix_copy, self.mdegree, 1)
xls.save_matches(self.p)
# print_matrix(self.matrix)
# print self.p
del self.matrix
return count
def reduction(self,exp):
xls = Xslxsaver()
if self.debug:
xls.create_worksheet(exp)
self.otimizator = Ot()
exp_sorted = sorted(exp, reverse=True)
self.mdegree = exp_sorted[0]
self.max_collum = (2*exp_sorted[0])-1
nr = self._calc_NR(exp_sorted)
self.matrix = self._generate_matrix()
exp_sorted.remove(self.mdegree)
j = 0
for i in range(0,len(exp_sorted)):
self._reduce_first(self.matrix, exp_sorted[i])
if self.debug:
xls.save(self.matrix, 'step_reduction_'+str(j))
j = j+1
for i in range(0,nr):
self._reduce_others(self.matrix,exp_sorted)
j = j+1
if self.debug:
xls.save(self.matrix, 'step_reduction_'+str(j))
self._remove_repeat(self.matrix)
self.clean(self.matrix)
self.matrix = self.otimizator.sort(self.matrix)
self.clean(self.matrix)
self.matrix = self.reduce_matrix(self.mdegree, self.matrix)
if self.debug:
xls.save(self.matrix, 'Not Optimized')
if not self.debug:
self.p, self.matrix = self.otimizator.optimize(self.matrix, self.mdegree)
if self.debug:
self.p, self.matrix = self.otimizator.optimize(self.matrix, self.mdegree, xls, self.debug)
self._remove_one(self.matrix)
#print_matrix(self.matrix)
row = [-1 for x in xrange(self.mdegree)]
self.matrix.append(row)
count = self._count_xor(self.matrix,self.p)
#count = count + self.countMatchs(otimizator.matches)
if self.debug:
xls.save(self.matrix, 'Optimized')
#self.p_, self.matrix_copy = otimizator.optimize(self.matrix_copy, self.mdegree, 1)
if self.debug:
xls.save_matches(self.p)
#print_matrix(self.matrix)
#print self.p
del self.matrix
return count