matplotlib 不均匀刻度绘图

墨蓝 2022-12-08 14:19 184阅读 0赞

# -*- coding: utf-8 -*-
    import matplotlib.pyplot as plt
    import numpy as np
    
    def auto_text(rects):
        for rect in rects:
            ax.text(rect.get_x()+rect.get_width()/2, rect.get_height(), rect.get_height(), ha='center', va='bottom')
    
    # plt.figure(figsize=(20, 20), dpi=80)
    num_list = [211, 30, 51, 402, 137, 66, 39, 5124, 40, 59,
                63, 135, 8902, 152, 117, 113, 250, 4099, 260, 217,
                431, 802, 5790, 553, 779, 951, 1135, 2524, 2135, 1700,
                2842, 1342, 7610]
    
    index = [60, 65, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,
             86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]
    width = 0.7
    
    # xindex = [60, 65, 70, 75, 80, 85, 90, 95, 100]
    yindex = [1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000]
    
    fig, ax = plt.subplots(figsize=(20, 20), dpi=90)
    
    xindex = np.arange(len(index))
    
    #关键是下面ax.bar的第一个参数，要设置为X轴参数的数量list[0,...,len(index)-1]
    p = ax.bar(xindex, num_list, width, label="Number of QF")
    
    #x轴坐标也是设为X轴参数的数量list
    ax.set_xticks(xindex)
    ax.set_xticklabels(index)
    
    plt.yticks(yindex, yindex, fontsize="large")
    
    ax.set_xlabel('QF', fontsize="xx-large")
    ax.set_ylabel('Number', fontsize="xx-large")
    
    auto_text(p)
    
    ax.legend(loc="upper right", fontsize="xx-large")
    plt.show()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3p6bGRt_size_16_color_FFFFFF_t_70_pic_center]  
[参考1][1]  
[参考2][2]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3p6bGRt_size_16_color_FFFFFF_t_70_pic_center]: /images/20221123/84e1e9f73c114441b06484c62429a15f.png
[1]: https://blog.csdn.net/weixin_44521703/article/details/101937540
[2]: https://blog.csdn.net/qq_37851620/article/details/94838854?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-7.channel_param&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-7.channel_param