def LU(matlist, K, reverse=0):
 nrow = len(matlist)
 (new_matlist1, new_matlist2) = (eye(nrow, K), copy.deepcopy(matlist))
 for i in range(nrow):
  for j in range((i + 1), nrow):
   if (new_matlist2[j][i] != 0):
    new_matlist1[j][i] = (new_matlist2[j][i] / new_matlist2[i][i])
    rowadd(new_matlist2, j, i, ((- new_matlist2[j][i]) / new_matlist2[i][i]), K)
 return (new_matlist1, new_matlist2)

def LU ( matlist , K , reverse = 0 ) : nrow = len ( matlist ) ( new_matlist1 , new_matlist2 ) = ( eye ( nrow , K ) , copy . deepcopy ( matlist ) ) for i in range ( nrow ) : for j in range ( ( i + 1 ) , nrow ) : if ( new_matlist2 [ j ] [ i ] != 0 ) : new_matlist1 [ j ] [ i ] = ( new_matlist2 [ j ] [ i ] / new_matlist2 [ i ] [ i ] ) rowadd ( new_matlist2 , j , i , ( ( - new_matlist2 [ j ] [ i ] ) / new_matlist2 [ i ] [ i ] ) , K ) return ( new_matlist1 , new_matlist2 )
it computes the lu decomposition of a matrix and returns l and u matrices .