def METHOD_NAME(df, ctf_id):
    max_ctf_score = 1.0
    min_ctf_score = 0.0
    df = df[df['SCORE'] < max_ctf_score]
    df = df[df['CTF_ESTIMATION_JOB_ID'] == ctf_id]
    score_mean = np.mean(df['SCORE'])
    fig, ax = plt.subplots(1, 1)
    sns.distplot(df['SCORE'], kde=False, ax=ax)
    #     ax.plot(df['DETECTED_RING_RESOLUTION'])
    plt.axvline(x=score_mean)
    plt.xlim(min_ctf_score, max_ctf_score)
    plt.ylabel('micrographs')
    plt.title('Distribution of CTF scores for ctf_id %s, mean = %3.2f ' % (ctf_id, score_mean))
    #     plt.savefig('ctf_res_histogram_CTF_ctf_id_%s' %ctf_id)
    return fig