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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def prior_neighbor(C, alpha=0.001):
 r"""Neighbor prior of strength alpha for the given count matrix. Prior is defined by b_ij = alpha if Z_ij+Z_ji > 0 b_ij = 0 else Parameters C : (M, M) scipy.sparse matrix Count matrix alpha : float (optional) Value of prior counts Returns ------- B : (M, M) scipy.sparse matrix Prior count matrix """

    C_sym = C + C.transpose()
    C_sym = C_sym.tocoo()
    data = C_sym.data
    row = C_sym.row
    col = C_sym.col

    data_B = alpha * np.ones_like(data)
    B = coo_matrix((data_B, (row, col)))
    return B