Python绘制图形之Matplotllib绘图

Love The Way You Lie 2022-02-05 13:47 579阅读 0赞

# Python绘制图形之Matplotllib绘图 #

一、绘制二维函数图

1.1 绘制 f(x)=sin2(x−2)e−x2

1.2 、绘制 sigmoid函数图: f(x)=11+e−x

1.3、绘制正态分布图

二、绘制三维图

2.1 绘制三维螺旋图

2.2 绘制三维线性点图

2.3 绘制三维柱状图

2.4 绘制三维 鞍部 曲面图

2.5 绘制山区图 f(x,y)=xe−x2−y2

2.6 三维动态图

--------------------

## 一、绘制二维函数图 ##

### 1.1 绘制 f(x)=sin2(x−2)e−x2 ###

函数图

代码1：
    import matplotlib.pyplot as plt
    import numpy as np
    plt.rcParams["font.sans-serif"]=['SimHei']  # 用于正常显示中文标签
    plt.rcParams['axes.unicode_minus']=False    # 用来正常显示负号
    
    x = np.linspace(-2.5,2,256,endpoint=True)   # 绘制X轴（-2.5,2）的图像
    
    f =(np.sin(x-2))**2*(np.e)**(-x**2)         # y值
    
    plt.plot(x,f,"g-",lw=2.5,label="f(x)")
    plt.title('f(x) = sin^2(x-2)e^{-x^2}函数图')
    plt.legend()
    plt.show()
    
    _______________________________________________
    代码2（对于复杂函数，我们可以将其拆分成多单一函数）
            分析：sin^2(x-2)e^{-x^2}分解：
                 sin(x1)*sin(x1)*e^x2
            其中：x1 = x-2;    x2 = -x^2
    import matplotlib.pyplot as plt
    import numpy as np
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签 
    plt.rcParams['axes.unicode_minus'] = False    # 用来正常显示负号 
    
    x = np.linspace(0, 2,300, endpoint=True) 
    x_1 = x-2
    S_1 = np.sin(x_1)
    S_2 = S_1**2
    
    E_1 = -x**2
    E_2 = np.exp(E_1)
    f = S_2*E_2    
    plt.figure(figsize = ((8,6)))     # 设置画布大小（可省略）
    
    plt.plot(x,f,'b-',lw=2.5,label='f(x)=sin^2(x-2)e^{-x^2}') 
    
    plt.legend()                      # 显示图例 
    plt.show()

![这里写图片描述][70]

### 1.2 、绘制 sigmoid函数图: f(x)=11+e−x ###

import matplotlib.pyplot as plt
    import numpy as np
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签 
    plt.rcParams['axes.unicode_minus'] = False    # 用来正常显示负号 
    
    x = np.linspace(-10, 10,300, endpoint=True) 
    
    E_1 = -x
    E_2 = np.exp(E_1)
    f = 1/(1+E_2)    
    plt.figure(figsize = ((8,6)))     # 设置画布大小（可省略）
    ax1 = plt.subplot(111)
    
    plt.plot(x,f,'b-',lw=2.5,label='f(x)=\\frac{1}{1+e^{-x}}') 
    
    plt.legend()                      # 显示图例 
    ax1.grid(True)                    # 显示网格 
    plt.show()

![这里写图片描述][70 1]

##  ##

### 1.3、绘制正态分布图 ###

其中 s 为 σ, m为 μ

import math
    import matplotlib.pyplot as plt
    import numpy as np
    def gd(x,m,s):                       #其中s为sigma ,m为 mu
        left=1/(math.sqrt(2*math.pi)*s)
        right=math.exp(-math.pow(x-m,2)/(2*math.pow(s,2)))
        return left*right
    def showfigure():
        plt.figure(figsize = ((8,6)))   #设置画布大小（可省略）
        x=np.arange(-4,5,0.1)           #绘制x（-4,5）
        y=[]
        for i in x:
            y.append(gd(i,0,1))         #m为0，s为1
        plt.plot(x,y) 
        plt.xlim(-4.0,5.0)
        plt.ylim(-0.2,0.5)
        ax = plt.gca()
        ax.spines['right'].set_color('none')
        ax.spines['top'].set_color('none')
        ax.xaxis.set_ticks_position('bottom')
        ax.spines['bottom'].set_position(('data',0))
        ax.yaxis.set_ticks_position('left')
        ax.spines['left'].set_position(('data',0))
    
        #设置并添加标签
        label_f1 = "$\mu=0,\ \sigma=1$"
        plt.text(2.5,0.3,label_f1,fontsize=15,verticalalignment="top",
                horizontalalignment="left")
        label_f2 = r"$f(x)=\frac{1}{\sqrt{2\pi}\sigma}exp(-\frac{(x-\mu)^2}{2\sigma^2})$"
        plt.text(1.5,0.4,label_f2,fontsize=15,verticalalignment="top"
                ,horizontalalignment="left")
        plt.show()
    
    def main():
        showfigure()
        gd()
    main()

![这里写图片描述][70 2]

##  ##

## 二、绘制三维图 ##

### 2.1 绘制三维螺旋图 ###

from mpl_toolkits.mplot3d import Axes3D
    import numpy as np
    import matplotlib.pyplot as plt
    
    fig = plt.figure(figsize = ((8,6)))
    ax = fig.add_subplot(1,1,1,projection='3d')
    theta = np.linspace(-4 * np.pi, 4 * np.pi, 500) # theta旋转角从-4pi到4pi，相当于两圈
    z = np.linspace(0, 2, 500)  # z轴从下到上,从-2到2之间画100个点
    r = z                       # 半径设置为z大小
    x = r * np.sin(theta)       # x和y画圆
    y = r * np.cos(theta)       # x和y画圆
    ax.plot(x, y, z, label='curve')
    ax.legend()                 # 图例
    
    plt.show()

![这里写图片描述][70 3]

### 2.2 绘制三维线性点图 ###

from mpl_toolkits.mplot3d import Axes3D
    import numpy as np
    import matplotlib.pyplot as plt
    
    fig = plt.figure()
    ax = fig.add_subplot(1,1,1,projection='3d')
    x = np.linspace(0, 5, 10)      # 在0-5之间生成10个点的向量
    y = np.linspace(0, 5, 10)      # 在0-5之间生成10个点的向量
    z1 = x
    z2 = 2*x
    z3 = 3*x
    ax.scatter(xx, yy, zz1, c='red', marker='o')   # o型符号
    ax.scatter(xx, yy, zz2, c='green', marker='^') # 三角型符号
    ax.scatter(xx, yy, zz3, c='black', marker='*') # 星型符号
    ax.legend()                                    # 显示图例  
    
    plt.show()

![这里写图片描述][70 4]

### 2.3 绘制三维柱状图 ###

import random
    import matplotlib as mpl
    import matplotlib.dates as mdates
    from mpl_toolkits.mplot3d import Axes3D
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签 
    plt.rcParams['axes.unicode_minus'] = False    # 用来正常显示负号 
    
    mpl.rcParams['font.size'] = 10
    
    fig = plt.figure(figsize=((8,6)))
    ax = fig.add_subplot(111, projection='3d')
    for z in [2011, 2012, 2013, 2014]:
        xs = range(1,13)
        ys = 1000 * np.random.rand(12)
        color = plt.cm.Set2(random.choice(range(plt.cm.Set2.N)))
        ax.bar(xs, ys, zs=z, zdir='y', color=color, alpha=0.8)
    
    ax.xaxis.set_major_locator(mpl.ticker.FixedLocator(xs))
    ax.yaxis.set_major_locator(mpl.ticker.FixedLocator(ys))
    ax.set_xlabel('月份')
    ax.set_ylabel('年份')
    ax.set_zlabel('销售额 ')
    plt.show()

![这里写图片描述][70 5]

###  ###

### 2.4 绘制三维 鞍部 曲面图 ###

import numpy as np
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    from matplotlib import cm
    
    n_angles = 1000                #曲面衔接角度（平滑度）
    n_radii = 20                   #鞍部半径（1：锐角，20：平滑角）
    fig = plt.figure(figsize=((10,10)))
    radii = np.linspace(0.125, 1.0, n_radii)
    angles = np.linspace(0, 2 * np.pi, n_angles, endpoint=False)
    angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
    
    x = np.append(0, (radii * np.cos(angles)).flatten())
    y = np.append(0, (radii * np.sin(angles)).flatten())
    
    z = np.sin(-x * y)
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    ax.plot_trisurf(x, y, z,   
                    cmap=cm.jet,    #曲面颜色
                    linewidth=0.2)

![这里写图片描述][70 6]

###  ###

### 2.5 绘制山区图 f(x,y)=xe−x2−y2 ###

import numpy as np
    import matplotlib.pyplot as plt
    import mpl_toolkits.mplot3d
    
    x,y = np.mgrid[-2:2:100j,-2:2:100j] #100j为设置曲面平滑度
    z=x*np.exp(-x**2-y**2)
    ax = plt.subplot(111, projection='3d')
    ax.set_title('山区图');
    ax.plot_surface(x,y,z,rstride=2, cstride=1, cmap=cm.jet)
    
    ax.set_xlabel('X')                #设置坐标轴标签
    ax.set_ylabel('Y')
    ax.set_zlabel('Z')
    plt.show()

![这里写图片描述][70 7]

###  ###

### 2.6 三维动态图 ###

from pyecharts import Bar3D
    bar3d = Bar3D("3D 柱状图示例", width=1200, height=600)
    
    x_axis = ["12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a", "11a",
              "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p", "10p", "11p"]
    y_axis = [ "Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"]
    
    data = [
        [0, 0, 5], [0, 1, 1], [0, 2, 0], [0, 3, 0], [0, 4, 0], [0, 5, 0],
        [0, 6, 0], [0, 7, 0], [0, 8, 0], [0, 9, 0], [0, 10, 0], [0, 11, 2],
        [0, 12, 4], [0, 13, 1], [0, 14, 1], [0, 15, 3], [0, 16, 4], [0, 17, 6],
        [0, 18, 4], [0, 19, 4], [0, 20, 3], [0, 21, 3], [0, 22, 2], [0, 23, 5],
        [1, 0, 7], [1, 1, 0], [1, 2, 0], [1, 3, 0], [1, 4, 0], [1, 5, 0],
        [1, 6, 0], [1, 7, 0], [1, 8, 0], [1, 9, 0], [1, 10, 5], [1, 11, 2],
        [1, 12, 2], [1, 13, 6], [1, 14, 9], [1, 15, 11], [1, 16, 6], [1, 17, 7],
        [1, 18, 8], [1, 19, 12], [1, 20, 5], [1, 21, 5], [1, 22, 7], [1, 23, 2],
        [2, 0, 1], [2, 1, 1], [2, 2, 0], [2, 3, 0], [2, 4, 0], [2, 5, 0],
        [2, 6, 0], [2, 7, 0], [2, 8, 0], [2, 9, 0], [2, 10, 3], [2, 11, 2],
        [2, 12, 1], [2, 13, 9], [2, 14, 8], [2, 15, 10], [2, 16, 6], [2, 17, 5],
        [2, 18, 5], [2, 19, 5], [2, 20, 7], [2, 21, 4], [2, 22, 2], [2, 23, 4],
        [3, 0, 7], [3, 1, 3], [3, 2, 0], [3, 3, 0], [3, 4, 0], [3, 5, 0],
        [3, 6, 0], [3, 7, 0], [3, 8, 1], [3, 9, 0], [3, 10, 5], [3, 11, 4],
        [3, 12, 7], [3, 13, 14], [3, 14, 13], [3, 15, 12], [3, 16, 9], [3, 17, 5],
        [3, 18, 5], [3, 19, 10], [3, 20, 6], [3, 21, 4], [3, 22, 4], [3, 23, 1],
        [4, 0, 1], [4, 1, 3], [4, 2, 0], [4, 3, 0], [4, 4, 0], [4, 5, 1],
        [4, 6, 0], [4, 7, 0], [4, 8, 0], [4, 9, 2], [4, 10, 4], [4, 11, 4],
        [4, 12, 2], [4, 13, 4], [4, 14, 4], [4, 15, 14], [4, 16, 12], [4, 17, 1],
        [4, 18, 8], [4, 19, 5], [4, 20, 3], [4, 21, 7], [4, 22, 3], [4, 23, 0],
        [5, 0, 2], [5, 1, 1], [5, 2, 0], [5, 3, 3], [5, 4, 0], [5, 5, 0],
        [5, 6, 0], [5, 7, 0], [5, 8, 2], [5, 9, 0], [5, 10, 4], [5, 11, 1],
        [5, 12, 5], [5, 13, 10], [5, 14, 5], [5, 15, 7], [5, 16, 11], [5, 17, 6],
        [5, 18, 0], [5, 19, 5], [5, 20, 3], [5, 21, 4], [5, 22, 2], [5, 23, 0],
        [6, 0, 1], [6, 1, 0], [6, 2, 0], [6, 3, 0], [6, 4, 0], [6, 5, 0],
        [6, 6, 0], [6, 7, 0], [6, 8, 0], [6, 9, 0], [6, 10, 1], [6, 11, 0],
        [6, 12, 2], [6, 13, 1], [6, 14, 3], [6, 15, 4], [6, 16, 0], [6, 17, 0],
        [6, 18, 0], [6, 19, 0], [6, 20, 1], [6, 21, 2], [6, 22, 2], [6, 23, 6]
        ]
    range_color = ['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
                   '#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026']
    bar3d.add("", x_axis, y_axis, [[d[1], d[0], d[2]] for d in data],
              is_visualmap=True, visual_range=[0, 20],
              visual_range_color=range_color, 
              grid3d_width=200, grid3d_depth=80,
              grid3d_shading='lambert',             #柱状图显示更真实（可省略）
              is_grid3d_rotate=True,                #自动旋转（可省略）
              grid3d_rotate_speed=10)               #旋转速度（可省略）
    bar3d.render()

![这里写图片描述][70 8]

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