#
# To measure the total XOR row operations needed in forming triangular matrix in Systematic Random Code (SYSRC).
#
# By Chong Zan Kai [email protected]
# Written on 3-Feb-2015.
#


class Systematic_Random_Code_Matrix_Solver:
    def __init__(self):
        self.__total_xor_row_operation = 0

    #
    # Return the total execution of XOR row operations.
    #
    def get_total_xor_row_operation(self):
        return self.__total_xor_row_operation

    #
    # Search for a particular row in which its target_col is non-zero.
    #
    def search_pivot_row(self, target_col, target_mat):
        for row in range(target_mat.nrows()):
            if target_mat[row, target_col] == 1:
                return row

        return -1


    #
    # Form triangle matrix utilising the received identity matrix.
    #
    def form_triangle_matrix(self, idn_mat, rand_mat):
        # Result matrix -- zero row.
        result_mat = matrix(GF(2), 0, idn_mat.ncols())

        for pivot_col in range(idn_mat.ncols()):

            pivot_row = self.search_pivot_row(pivot_col, idn_mat)

            if pivot_row >=0 :
                result_mat = result_mat.stack( idn_mat[pivot_row] )
            else:
                pivot_row = self.search_pivot_row(pivot_col, rand_mat)
                assert (pivot_row >=0 ) # nothing I can do it cannot find any pivot row.

                result_mat = result_mat.stack( rand_mat[pivot_row] )
                rand_mat = rand_mat.delete_rows([pivot_row])

            for row in range(rand_mat.nrows()):
                # Note! I remove the following line such that the solver will XOR every row!!!!!!!!!
                # if rand_mat[row, pivot_col] == 1:
                    rand_mat[row] += result_mat[-1]
                    # XOR row operation.
                    self.__total_xor_row_operation += 1
        #
        return result_mat

    #
    #

#
# To measure the total XOR row operation in invert the (k+10) x k augmented matrix that
# consists of $total_idn_row identity rows.
#
def calc_xor_row_operation(total_idn_row, k):
    idn_mat = identity_matrix(GF(2), k)
    idn_mat = idn_mat[range(total_idn_row), :]

    total_rand_row = k+10 - idn_mat.nrows()
    rand_mat = random_matrix(GF(2), total_rand_row, k)

    # Inverting matrix
    solver = Systematic_Random_Code_Matrix_Solver()
    result_mat = solver.form_triangle_matrix(idn_mat,rand_mat)
    return solver.get_total_xor_row_operation()

#-----------------------------------------------------------------------
# Test
#-----------------------------------------------------------------------
import random

# set_random_seed(333)

k = 40
for i in range(0, 10):
    result = calc_xor_row_operation(i, k)
    print 'idn_row = %d, rand_row = %d and XOR row operation = %d' % (i, k+10-i, result)