def METHOD_NAME():
    ln_ca_range = (-18, 4, 0.1)  # about 1e-9 to 1e2 in steps of 0.1 log unit
    v_range = (-80, 50, 1)  # -80mV to 50mV in 1mV steps
    casteps = vecrange(*ln_ca_range)
    vsteps = vecrange(*v_range)
    malp = h.Matrix(len(vsteps), len(casteps))
    mbet = malp.c()
    for i, v in enumerate(vsteps):
        for j, lnca in enumerate(casteps):
            malp.x[i][j] = alp(v, lnca)
            mbet.x[i][j] = bet(v, lnca)
            assert isclose(malp.x[i][j], h.alp_cagk(v, exp(lnca)), abs_tol=1e-9)
            assert isclose(mbet.x[i][j], h.bet_cagk(v, exp(lnca)), abs_tol=1e-9)
    # dimensions specified in size, min, max format
    h.table_alp_cagkftab(
        malp._ref_x[0][0],
        len(vsteps),
        vsteps[0],
        vsteps[len(vsteps) - 1],
        len(casteps),
        casteps[0],
        casteps[len(casteps) - 1],
    )
    # dimensions specified in size, pointer to array format (not efficient)
    h.table_bet_cagkftab(
        mbet._ref_x[0][0],
        len(vsteps),
        vsteps._ref_x[0],
        len(casteps),
        casteps._ref_x[0],
    )
    # must keep matrices and vectors in existence
    return malp, mbet, vsteps, casteps