绘制稍微复杂函数

import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签SimHei
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x = np.linspace(0.1, 30, 100)
y = np.sqrt(x)-np.log2(x)

plt.plot(x, y)
plt.xlabel('x')
plt.ylabel('y')
plt.title('f(x)图像')
plt.grid(True)
plt.show()

绘制条形图 一列有两条柱

# -*- coding: utf-8 -*-
    import matplotlib.pyplot as plt
    import numpy as np
    from pylab import mpl
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签SimHei
    plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号

    # 设置柱状图的宽度
    bar_width = 0.35

    # 计算每个柱状图的中心位置
    x = np.arange(len(dops))

    # 绘图
    fig, ax = plt.subplots()
    # print(ustore_vals)
    # print(astore_vals)
    bars1 = ax.bar(x - bar_width / 2, ustore_vals, bar_width, label='Ustore')
    bars2 = ax.bar(x + bar_width / 2, astore_vals, bar_width, label='Astore')

    # 添加标签、标题和图例
    ax.set_xlabel('query_dop')
    ax.set_ylabel('Values')
    ax.set_title(title)
    ax.set_xticks(x)
    ax.set_xticklabels(dops)
    ax.legend()

    # 显示图形
    plt.show()
    # plt.savefig(path)
    # plt.close()

绘制普通折线图

import matplotlib.pyplot as plt
    import numpy as np
    from pylab import mpl
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签SimHei
    plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
    # 创建折线图
    plt.plot(dops, end2end_imp_vals,color='red', linestyle='-', marker='o', label='端到端性能提升')
    plt.plot(dops, op_imp_vals,color='blue', linestyle='--', marker='s', label='Seq scan算子性能提升')

    # 设置x轴和y轴标签
    plt.xlabel('query_dop')
    plt.ylabel('性能提升倍数')
    plt.legend()

    # 设置图表标题
    plt.title('Ustore不同并行度下性能提升倍数')

    # 显示图表
    # plt.show()
    plt.savefig(path)
    plt.close()