论文实验常用图python绘制汇总

原作者仓库

新添部分图

1.折线图

代码如下：

def plot_line():

    x = np.array([1, 2, 3, 4, 5])
    model1 = np.array([0.2160, 0.1925, 0.1854, 0.1513, 0.1132])
    Ours = np.array([0.2416, 0.2331, 0.2165, 0.1943, 0.1715])

    # label在图示(legend)中显示。若为数学公式,则最好在字符串前后添加"$"符号
    # color：b:blue、g:green、r:red、c:cyan、m:magenta、y:yellow、k:black、w:white、、、
    # 线型：-  --   -.  :    ,
    # marker：.  ,   o   v    <    *    +    1
    plt.figure(figsize=(5, 4))
    # linestyle = "-"
    plt.grid(linestyle="-.")  # 设置背景网格线为虚线
    ax = plt.gca()
    # ax.spines['top'].set_visible(False)  # 去掉上边框
    # ax.spines['right'].set_visible(False)  # 去掉右边框

    linewidth = 2.0
    markersize = 7

    plt.plot(x, model1, marker='s', markersize=markersize, color="blue", label="Model1", linewidth=linewidth)
    plt.plot(x, Ours, marker='X', markersize=markersize, color="tomato", label="Ours", linewidth=linewidth)


    group_labels = ['-', '20%', '40%', '60%', '80%']
    plt.xticks(x, group_labels, fontsize=15)  # 默认字体大小为10
    y_ticks = [0.10, 0.15, 0.20, 0.25, 0.30]
    y_lables = ['0.10', '0.15', '0.20', '0.25', '0.30']
    plt.yticks(np.array(y_ticks), y_lables, fontsize=15)
    # plt.title("example", fontsize=12, fontweight='bold')  # 默认字体大小为12
    # plt.text(1, label_position, dataset,fontsize=25, fontweight='bold')
    # plt.xlabel("Edge Miss Rate", fontsize=15)
    plt.ylabel(f"HR@20", fontsize=15)
    plt.xlim(0.5, 5.5)  # 设置x轴的范围
    plt.ylim(0.08, 0.30)

    # plt.legend()
    # 显示各曲线的图例 loc=3 lower left
    plt.legend(loc=0, numpoints=1, ncol=2)
    leg = plt.gca().get_legend()
    ltext = leg.get_texts()
    plt.setp(ltext, fontsize=15)
    # plt.setp(ltext, fontsize=25, fontweight='bold')  # 设置图例字体的大小和粗细
    plt.tight_layout()
    plt.savefig(f'pics/line.png', format='png')  # 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
    plt.show()

2. 折线截断图

代码链接

3. 柱状图

代码如下：

def plot_bar():
    result1 = [0.0714, 0.0840, 0.0784, 0.0709]
    # Arial
    # plt.rcParams['font.sans-serif'] = ['Times New Roman']  # 如果要显示中文字体,则在此处设为：SimHei
    # plt.rcParams['axes.unicode_minus'] = False  # 显示负号

    plt.figure(figsize=(5, 4))
    plt.ylim(0.067, 0.088)
    labels = ['1', '2', '3', '4']

    # from matplotlib.font_manager import FontProperties
    # myfont = FontProperties(fname='times.ttf', size=25)
    plt.xticks(fontsize=15)
    plt.yticks(fontsize=15)

    colors = ['tomato'] * 4
    # /,  , |, -, +, x, o, O,., * 。
    plt.bar(np.arange(len(result1)), result1, ec='b', hatch=2 * '.', width=0.5,
            tick_label=labels,
            color=colors)
    plt.tight_layout()
    plt.savefig(f'pics/bar.png', format='png')  # 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
    plt.show()

4. 多柱状图

代码如下：

def plot_multi_bar():

    model1 = np.array([0.0409, 0.0543, 0.0943, 0.1115, 0.1363])
    model2 = np.array([0.0351, 0.0557, 0.0916, 0.1315, 0.1860])
    model3 = np.array([0.0586, 0.0865, 0.1046, 0.1476, 0.2160])

    Ours = np.array([0.1043, 0.1344, 0.1638, 0.2035, 0.2446])

    # label在图示(legend)中显示。若为数学公式,则最好在字符串前后添加"$"符号
    # color：b:blue、g:green、r:red、c:cyan、m:magenta、y:yellow、k:black、w:white、、、
    # 线型：-  --   -.  :    ,
    # marker：.  ,   o   v    <    *    +    1
    plt.figure(figsize=(7, 4))
    # linestyle = "-"
    x = np.arange(5)
    # n 为有几个柱子
    total_width, n = 0.8, 4
    width = total_width / n
    x = x - (total_width - width) / n


    # low = 0.05
    # up = 0.44
    low = 0.02
    up = 0.27
    plt.ylim(low, up)
    # plt.xlabel("Amount of Data", fontsize=15)
    plt.ylabel(f"HR@20", fontsize=20)
    labels = ['Model1', 'Model2', 'Model3', 'Ours']

    # 'tomato', 'blue', 'orange', 'green', 'purple', 'deepskyblue'
    plt.bar(x, model1, width=width, color='blue', edgecolor='w')  # , edgecolor='k',)
    plt.bar(x + width, model2, width=width, color='green', edgecolor='w')  # , edgecolor='k',)
    plt.bar(x + 2*width, model3, width=width, color='orange', edgecolor='w')  # , edgecolor='k',)
    plt.bar(x + 3*width, Ours, width=width, color='tomato', edgecolor='w')  # , edgecolor='k',)

    plt.xticks(x +1.5*width, labels=['20%', '40%', '60%', '80%', '100%'], fontsize=20)

    y_lables = ['0.02', '0.08', '0.14', '0.20', '0.26']
    y_ticks = [float(i) for i in y_lables]
    # plt.yscale('linear')
    # y_ticks = [0.25, 0.30, 0.35, 0.40, 0.45]
    # y_lables = ['0.25', '0.30', '0.35', '0.40', '0.45']
    plt.yticks(np.array(y_ticks), y_lables, fontsize=20)#bbox_to_anchor=(0.30, 1)
    plt.legend(labels=labels, ncol=2,
               prop={'size': 14})

    plt.tight_layout()
    plt.savefig('./pics/multi_bar.png', format='png')
    plt.show()
    # 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中

5. 柱状截断图

代码链接

6. 柱状折线图

代码如下：

def plot_bar_and_line():
    fontsize=20
    result1 = [0.1967, 0.2103, 0.2398, 0.2446, 0.2387]
    l = [i for i in range(5)]

    lx = ['2', '3', '4', '5', '6']

    fig = plt.figure()
    ax1 = fig.add_subplot(111)
    plt.bar(l, result1, alpha=0.3, color='blue', label='HR@20')

    # left_axis.set_ylim(0.80, 0.96)
    # left_axis.set_yticks(np.arange(0.80, 0.97, 0.04))
    ax1.set_ylim([0.18, 0.26])
    ax1.set_yticks(np.arange(0.18, 0.26, 0.015))
    # ax1.set_ylabel('AUC', fontsize=fontsize)
    plt.legend(loc="upper left", prop={'size': 15})
    plt.xticks(l, lx, fontsize=fontsize)
    plt.yticks(fontsize=fontsize)

    result2 = [0.0823, 0.0976, 0.1054, 0.1185, 0.1045]

    ax2 = ax1.twinx()  # this is the important function
    ax2.plot(l, result2, 'or-', label='NDCG@20', color='green')
    ax2.legend(loc=2)
    ax2.set_ylim([0.07, 0.13])
    ax2.set_yticks(np.arange(0.07, 0.13, 0.01))
    # ax2.set_ylabel('Log-loss', fontsize=fontsize)
    plt.text(1.5, 0.06, "Num", fontsize=20)
    plt.legend(loc="upper right", prop={'size': 15})
    plt.yticks(fontsize=fontsize)
    plt.tight_layout()
    # , bbox_inches='tight', pad_inches=0.05, dpi=100
    plt.savefig('pics/bar_and_line.png', format='png')
    plt.show()

7. 常规组合图

8. 其他组合图