matplot线性图，散点图，柱状图的常用操作学习笔记

超、凢脫俗 2023-06-30 15:58 20阅读 0赞

import numpy as np
    import matplotlib.pyplot as plt
    
    # 线性图
    x = np.linspace(-5,5,100)
    y1 = x * 2 + 3
    y2 = (x ** 2) / 2
    
    plt.figure(num=1,figsize=(8,5))
    
    # plot绘制线条
    l1 = plt.plot(x,y1,label='line',linestyle='--')
    l2 = plt.plot(x,y2,label='curve',linewidth=5.0,alpha=0.5)
    
    # xlim,ylim限制x,y轴显示范围
    plt.xlim((-3,3))
    plt.ylim((-5,10))
    
    # xlabel,ylabel x,y轴名称
    plt.xlabel('x')
    plt.ylabel('y')
    
    # legend显示标框
    plt.legend(loc='best')
    
    # 移动x,y轴位置
    ax = plt.gca()
    ax.spines['right'].set_color('none')
    ax.spines['top'].set_color('none')
    ax.xaxis.set_ticks_position('bottom')
    ax.yaxis.set_ticks_position('left')
    ax.spines['bottom'].set_position(('data',0))
    ax.spines['left'].set_position(('data',-1))
    
    # xticks,yticks重定义坐标轴数据
    # new_ticks = np.linspace(-3,3,7)
    plt.xticks([-3,-2,-1,0,1,2,3],
               [-2,-1,0,1,2,3,4])
    
    # annotion注释
    x0 = 1
    y0 = x0 * 2 + 3
    # 散点图
    plt.scatter(x0,y0,s=50,color='b')
    plt.plot([x0,x0],[y0,0],'k--',lw=2.5)
    # method1
    plt.annotate(r'$2x+3=%s$' % y0, xy=(x0, y0), xycoords='data', xytext=(+30, -30),
                 textcoords='offset points', fontsize=16,
                 arrowprops=dict(arrowstyle='->', connectionstyle="arc3,rad=.2"))
    
    # 散点图
    # 0-平均值,1-方差,n个呈标准正态分布的数组
    n = 1024
    X = np.random.normal(0.25,1.5,n)
    Y = np.random.normal(0.25,1.5,n)
    C = np.arctan2(Y,X) # 颜色值
    
    plt.figure(num=2,figsize=(8,5))
    plt.scatter(X,Y,s=50,alpha=0.7,c=C)
    
    plt.xticks(())
    plt.yticks(())
    
    # 柱状图
    # n,柱状图数量
    n = 8
    X = np.arange(n)
    Y1 = 2*X + 3
    Y2 = -Y1
    plt.figure(num=3,figsize=(8,5))
    
    plt.bar(X,Y1,facecolor='#99ffff',edgecolor='white')
    plt.bar(X,Y2,facecolor='#ffff99',edgecolor='white')
    
    # 在bar上显示文本,ha横向居中对齐，va纵向底部/顶部对齐
    for x,y in zip(X,Y1):
        plt.text(x,y+0.05,'%.2f'%y,ha='center',va='bottom')
    
    for x,y in zip(X,Y2):
        plt.text(x,y-0.05,'%.2f'%y,ha='center',va='top')
    plt.show()