def adjugate(self):
        assert self.is_square(), "Adjugate MatrixN can only be computed for a square MatrixN"
        n = self.nrow
        if n == 1 :
            a = self.__class__([[1]])
        elif n == 2 :
            a = self.__class__( [ [ self[1,1], -self[0,1] ],    \
                                  [-self[1,0], self[0,0] ] ] )
        elif n == 3 :
            a = self.__class__( [ [  (self[1,1]*self[2,2]-self[1,2]*self[2,1]), -(self[0,1]*self[2,2]-self[0,2]*self[2,1]),  (self[0,1]*self[1,2]-self[0,2]*self[1,1]) ], \
                                  [ -(self[1,0]*self[2,2]-self[1,2]*self[2,0]),  (self[0,0]*self[2,2]-self[0,2]*self[2,0]), -(self[0,0]*self[1,2]-self[0,2]*self[1,0]) ], \
                                  [  (self[1,0]*self[2,1]-self[1,1]*self[2,0]), -(self[0,0]*self[2,1]-self[0,1]*self[2,0]),  (self[0,0]*self[1,1]-self[0,1]*self[1,0]) ] ] )
        else :
            # generic cofactor expansion method
            a = self.__class__([[self.cofactor(j, i) for j in xrange(n)] for i in xrange(n)])

        return a
Filter ouput.
dataset/ETHPy150Open CountZer0/PipelineConstructionSet/python/maya/site-packages/pymel-1.0.3/pymel/util/arrays.py/MatrixN.adjugate--crossover with--dataset/ETHPy150Open openstack/compass-core/compass/db/api/utils.py/filter_output