matplotlib实例(各种图形)

阳光穿透心脏的1/2处 2023-06-06 03:44 79阅读 0赞

matplotlib是一个Python的2D绘图库，通过Matplotlib，可以仅需几行代码，便可生成绘图，直方图，条形图，散点图等。  
绘图步骤：  
\-> 创建图纸（figure）  
\-> 在图纸上创建一个或多个绘图（plot）区域（也叫子图，坐标系/轴，axis）  
\-> 在plot区域上描绘点、线等各种marker  
\-> 为plot添加修饰标签（绘图线上的或坐标轴上的）

import matplotlib.pyplot as plt
    import numpy as np
    x = np.linspace(0, 2, 100)
    
    plt.plot(x, x, label='linear')
    plt.plot(x, x**2, label='quadratic')
    plt.plot(x, x**3, label='cubic')
    
    plt.xlabel('x label')
    plt.ylabel('y label')
    
    plt.title("Simple Plot")
    
    plt.legend()
    
    plt.show()

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import numpy as np
    t = np.arange(0., 5., 0.2)
    plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')
    plt.show()

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x = np.random.rand(10)
    y = np.random.rand(10)
    plt.scatter(x,y)
    plt.show()

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data = { 'a': np.arange(50),
            'c': np.random.randint(0, 50, 50),
            'd': np.random.randn(50)}
    data['b'] = data['a'] + 10 * np.random.randn(50)
    data['d'] = np.abs(data['d']) * 100
    
    plt.scatter('a', 'b', c='c', s='d', data=data)
    plt.xlabel('entry a')
    plt.ylabel('entry b')
    plt.show()

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def f(t):
        return np.exp(-t) * np.cos(2*np.pi*t)
    
    t1 = np.arange(0.0, 5.0, 0.1)
    t2 = np.arange(0.0, 5.0, 0.02)
    
    plt.figure(1)
    plt.subplot(211)
    plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')
    
    plt.subplot(212)
    plt.plot(t2, np.cos(2*np.pi*t2), 'r--')
    plt.show()

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import numpy as np
    import matplotlib. pyplot as plt
    np.random.seed(19680801)
    
    dt = 0.01
    t = np.arange(0, 30, dt)
    nse1 = np.random. randn(len(t))  
    nse2 = np.random.randn(len(t)) 
    
    # Two signals with a coherent part at 10Hz and a random part
    s1 = np.sin(2*np.pi*10*t)+nse1
    s2 = np.sin(2*np.pi*10*t)+nse2
    
    fig, axs = plt.subplots(2, 1)
    axs[0].plot(t, s1, t, s2)
    axs[0].set_xlim(0,2)
    axs[0].set_xlabel('time')
    axs[0].set_ylabel('s1 and s2')
    axs[0].grid(True)
    
    cxy, f = axs[1].cohere(s1,s2,256, 1./ dt)
    axs[1].set_ylabel(' coherence')
    
    fig.tight_layout()
    plt. show()

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import matplotlib.pyplot as plt
    import numpy as np
    n = 1204
    X = np.random.normal(0,1,n)
    Y = np.random.normal(0,1,n)
    T = np.arctan2(Y,X)
    plt.scatter(X,Y,s=75,c=T,alpha=0.5)
    plt.xlim((-1,1))
    plt.ylim((-1,1))
    plt.xticks(())
    plt.yticks(())
    plt.show()

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import matplotlib.pyplot as plt
    import numpy as np
    
    x = np.arange(9)
    y = np.sin(x)
    z = np.cos(x)
    # marker数据点样式，linewidth线宽，linestyle线型样式，color颜色
    plt.plot(x, y, marker="*", linewidth=3, linestyle="--", color="red")
    plt.plot(x, z)
    plt.title("matplotlib")
    plt.xlabel("height")
    plt.ylabel("width")
    # 设置图例
    plt.legend(["Y","Z"], loc="upper right")
    plt.grid(True)
    plt.show()

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x = np.arange(10)
    y = np.random.randint(0,30,10)
    plt.bar(x, y)
    plt.show()

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import matplotlib.pyplot as plt  
      
    num_list = [1.5,0.6,7.8,6]  
    plt.bar(range(len(num_list)), num_list,color='rbgy')  
    plt.show()

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import matplotlib.pyplot as plt  
      
    name_list = ['Monday','Tuesday','Friday','Sunday']  
    num_list = [1.5,0.6,7.8,6]  
    num_list1 = [1,2,3,1]  
    x =list(range(len(num_list)))  
    total_width, n = 0.8, 2  
    width = total_width / n  
      
    plt.bar(x, num_list, width=width, label='boy',fc = 'y')  
    for i in range(len(x)):  
        x[i] = x[i] + width  
    plt.bar(x, num_list1, width=width, label='girl',tick_label = name_list,fc = 'r')  
    plt.legend()  
    plt.show()

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import numpy as np
    import matplotlib.pyplot as plt
    
    n = 12
    X = np.arange(n)
    Y1 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n)
    Y2 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n)
    
    plt.axes([0.025,0.025,0.95,0.95])
    plt.bar(X, +Y1, facecolor='#9999ff', edgecolor='white')
    plt.bar(X, -Y2, facecolor='#ff9999', edgecolor='white')
    
    for x,y in zip(X,Y1):
        plt.text(x+0.4, y+0.05, '%.2f' % y, ha='center', va= 'bottom')
    
    for x,y in zip(X,Y2):
        plt.text(x+0.4, -y-0.05, '%.2f' % y, ha='center', va= 'top')
    
    plt.xlim(-.5,n), plt.xticks([])
    plt.ylim(-1.25,+1.25), plt.yticks([])
    plt.show()

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import matplotlib.pyplot as plt
    import numpy as np
     
    n = 12
    X = np.arange(n)
    Y1 = (1-X/(float(n))*np.random.uniform(0.5,1.0,n))
    Y2 = (1-X/(float(n))*np.random.uniform(0.5,1.0,n))
     
    plt.bar(X,+Y1,facecolor='r',edgecolor='w')
    plt.bar(X,-Y2,facecolor='b',edgecolor='w')
     
    for x,y in zip(X,Y1):
        plt.text(x-0.1,y+0.05,'%.2f'%y,ha='center',va='bottom')  #居中对齐
    for x,y in zip(X,Y2):
        plt.text(x+0.1,-y-0.05,'-%.2f'%y,ha='center',va='top')
     
    plt.xlim((-0.5,n))
    plt.ylim((-2,2))
    plt.xticks(())
    plt.yticks(())
    plt.show()

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mean, sigma = 0, 1
    x = mean + sigma * np.random.randn(10000)
    plt.hist(x,50)
    plt.show()

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import pandas as pd
    import numpy as np
     
    df = pd.DataFrame(3 * np.random.rand(5), index=['a', 'b', 'c', 'd','e'], columns=['x'])
    df.plot.pie(subplots=True)

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import pandas as pd
    import numpy as np
     
    df = pd.DataFrame(np.random.rand(15, 4), columns=['a', 'b', 'c', 'd'])
    df.plot.area()

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import numpy as np
    import matplotlib.pyplot as plt
    
    n = 256
    X = np.linspace(-np.pi,np.pi,n,endpoint=True)
    Y = np.sin(2*X)
    
    plt.axes([0.025,0.025,0.95,0.95])
    
    plt.plot (X, Y+1, color='blue', alpha=1.00)
    plt.fill_between(X, 1, Y+1, color='blue', alpha=.25)
    
    plt.plot (X, Y-1, color='blue', alpha=1.00)
    plt.fill_between(X, -1, Y-1, (Y-1) > -1, color='blue', alpha=.25)
    plt.fill_between(X, -1, Y-1, (Y-1) < -1, color='red',  alpha=.25)
    
    plt.xlim(-np.pi,np.pi), plt.xticks([])
    plt.ylim(-2.5,2.5), plt.yticks([])
    plt.show()

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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(-np.pi,np.pi,256,endpoint=True)   #获取x坐标
    
    sin,cos = np.sin(X),np.cos(X)  #获取y坐标
    
    plt.plot(X,sin,"b-",lw=2.5,label="正弦Sin()")  #X：x轴；sin:y轴；b-:color="blue",linestyle="-"的简写；lw:linewidth
    plt.plot(X,cos,"r-",lw=2.5,label="余弦Cos()")
    
    plt.xlim(X.min()*1.5,X.max()*1.5)
    plt.ylim(cos.min()*1.5,cos.max()*1.5)
    
    plt.xticks([-np.pi,-np.pi/2,0,np.pi/2,np.pi],[r'$-\pi$',r'$-\pi/2$',r'$0$',r'$\pi/2$',r'$\pi$'])
    plt.yticks([-1,0,1])
    
    plt.title("绘图实例之COS()&SIN()",fontsize=16,color="green")
    
    plt.text(+2.1,-1.4,"By:biyoulin",fontsize=16,color="purple")
    
    ax=plt.gca()  #获取Axes对象
    ax.spines['right'].set_color('none')    #隐藏右边界
    ax.spines['top'].set_color('none')      #隐藏上边界
    
    ax.xaxis.set_ticks_position('bottom')   #x轴坐标刻度设置在坐标轴下面
    ax.spines['bottom'].set_position(('data',0))  #x轴坐标轴平移至经过零点（0,0）位置
    
    ax.yaxis.set_ticks_position('left')           #y轴坐标刻度设置在坐标轴下面
    ax.spines['left'].set_position(('data',0))    #y轴坐标轴平移至经过零点（0,0）位置
    
    plt.legend(loc="upper left",fontsize=12)
    
    t1 = 2*np.pi/3 #设定第一个点的x轴值
    t2 = -np.pi   #设定第二个点的x轴值
    plt.plot([t1,t1],[0,np.sin(t1)],color ='b',linewidth=1.5,linestyle="--")
    #第一个列表是x轴坐标值，第二个列表是y轴坐标值
    #这两个点坐标分别为（t1,0）和（t1，np.sin(t1)），根据两点画直线l1
    plt.plot([t2,t2],[0,np.cos(t2)],color ='r',linewidth=1.5,linestyle="--")
    #这两个点坐标分别为（t2,0）和（t2，np.cos(t2)），根据两点画直线l2
    
    plt.scatter([t1,],[np.sin(t1),], 50, color ='b')
    plt.scatter([t2,],[np.cos(t2),], 50, color ='r')
    
    plt.annotate(r'$\sin(\frac{2\pi}{3})=\frac{\sqrt{3}}{2}$',
                 xy=(t1,np.sin(t1)),    #点的位置
                 xycoords='data',       #注释文字的偏移量
                 xytext=(+10,+30),      #文字离点的横纵距离
                 textcoords='offset points',
                 fontsize=14,      #注释的大小
                 arrowprops=dict(arrowstyle="->",connectionstyle="arc3,rad=.2"))   #箭头指向的弯曲度
    
    plt.annotate(r'$\cos(-\pi)=-1$',
                 xy=(t2,np.cos(t2)),   #点的位置
                 xycoords='data',      #注释文字的偏移量
                 xytext=(0,-40),       #文字离点的横纵距离
                 textcoords='offset points',
                 fontsize=14,    #注释的大小
                 arrowprops=dict(arrowstyle="->",connectionstyle="arc3,rad=.2"))
                                                                      #箭头指向的弯曲度
    for label in ax.get_xticklabels()+ax.get_yticklabels():           #获取刻度
        label.set_fontsize(18)                                        #设置刻度字体大小
    
    plt.fill_between(X,np.abs(X)<0.5,sin,sin>0.5,color='g',alpha=0.8)
    #设置正弦函数的填充区域，其中的一种方式
    plt.fill_between(X,cos,where=(-2.5<X)&(X<-0.5),color='purple')
    #设置余弦函数的填充区域，另外一种方式
    
    plt.grid()
    
    plt.savefig("C:\\绘图实例之COS()&SIN().PNG",dpi=300)
    
    plt.show()   #显示图表

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from mpl_toolkits.mplot3d import axes3d
    import matplotlib.pyplot  as plt
    from matplotlib import cm
    
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    X,Y,Z = axes3d.get_test_data(0.05)
    
    # Plot the 3D surface
    ax.plot_surface(X,Y,Z,rstride=8,cstride=8,alpha=0.3)
    
    cset = ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm. coolwarm)
    cset = ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm. coolwarm)
    cset = ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm. coolwarm)
    
    ax.set_xlim(-40, 40)
    ax.set_ylim(-40, 40)
    ax.set_zlim(-100, 100)
    
    ax.set_xlabel('X') 
    ax.set_ylabel('Y')
    ax.set_zlabel('Z')
    
    plt.show()

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import matplotlib.pyplot as plt
    import numpy as np
    from mpl_toolkits.mplot3d import Axes3D
     
    fig = plt.figure()
    ax = Axes3D(fig)
    X = np.arange(-4,4,0.25)
    Y = np.arange(-4,4,0.25)
    X,Y = np.meshgrid(X,Y)
    R = np.sqrt(X**2+Y**2)
     
    #Z是高度值
    Z = np.sin(R)
    ax.plot_surface(X,Y,Z,rstride=1,cstride=1,cmap=plt.get_cmap('rainbow'))  #stride表示跨度
    # ax.contourf(X,Y,Z,zdir='z',offset=-2,cmap='rainbow')
    # ax.set_zlim(-2,2)
    plt.show()

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import numpy as np
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    
    fig = plt.figure()
    ax = Axes3D(fig)
    X = np.arange(-4, 4, 0.25)
    Y = np.arange(-4, 4, 0.25)
    X, Y = np.meshgrid(X, Y)
    R = np.sqrt(X**2 + Y**2)
    Z = np.sin(R)
    
    ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=plt.cm.hot)
    ax.contourf(X, Y, Z, zdir='z', offset=-2, cmap=plt.cm.hot)
    ax.set_zlim(-2,2)
    plt.show()

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import numpy as np
    import matplotlib.pyplot as plt
    
    ax = plt.axes([0.025,0.025,0.95,0.95], polar=True)
    
    N = 20
    theta = np.arange(0.0, 2*np.pi, 2*np.pi/N)
    radii = 10*np.random.rand(N)
    width = np.pi/4*np.random.rand(N)
    bars = plt.bar(theta, radii, width=width, bottom=0.0)
    
    for r,bar in zip(radii, bars):
        bar.set_facecolor( plt.cm.jet(r/10.))
        bar.set_alpha(0.5)
    
    ax.set_xticklabels([])
    ax.set_yticklabels([])
    # savefig('../figures/polar_ex.png',dpi=48)
    plt.show()

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import numpy as np
    import matplotlib.pyplot as plt
    
    def f(x,y):
        return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
    
    n = 10
    x = np.linspace(-3,3,3.5*n)
    y = np.linspace(-3,3,3.0*n)
    X,Y = np.meshgrid(x,y)
    Z = f(X,Y)
    
    plt.axes([0.025,0.025,0.95,0.95])
    plt.imshow(Z,interpolation='nearest', cmap='bone', origin='lower')
    plt.colorbar(shrink=.92)
    
    plt.xticks([]), plt.yticks([])
    plt.show()

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import numpy as np
    import matplotlib.pyplot as plt
    
    n = 8
    X,Y = np.mgrid[0:n,0:n]
    T = np.arctan2(Y-n/2.0, X-n/2.0)
    R = 10+np.sqrt((Y-n/2.0)**2+(X-n/2.0)**2)
    U,V = R*np.cos(T), R*np.sin(T)
    
    plt.axes([0.025,0.025,0.95,0.95])
    plt.quiver(X,Y,U,V,R, alpha=.5)
    plt.quiver(X,Y,U,V, edgecolor='k', facecolor='None', linewidth=.5)
    
    plt.xlim(-1,n), plt.xticks([])
    plt.ylim(-1,n), plt.yticks([])
    plt.show()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NDQ5NTY3OA_size_16_color_FFFFFF_t_70 24]

import numpy as np
    import matplotlib.pyplot as plt
    
    eqs = []
    eqs.append((r"$W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2} \int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{ U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_{\rho_1 \sigma_2} }{U^{0\beta}_{\rho_1 \sigma_2}}\right]$"))
    eqs.append((r"$\frac{d\rho}{d t} + \rho \vec{v}\cdot\nabla\vec{v} = -\nabla p + \mu\nabla^2 \vec{v} + \rho \vec{g}$"))
    eqs.append((r"$\int_{-\infty}^\infty e^{-x^2}dx=\sqrt{\pi}$"))
    eqs.append((r"$E = mc^2 = \sqrt{ {m_0}^2c^4 + p^2c^2}$"))
    eqs.append((r"$F_G = G\frac{m_1m_2}{r^2}$"))
    
    plt.axes([0.025,0.025,0.95,0.95])
    
    for i in range(24):
        index = np.random.randint(0,len(eqs))
        eq = eqs[index]
        size = np.random.uniform(12,32)
        x,y = np.random.uniform(0,1,2)
        alpha = np.random.uniform(0.25,.75)
        plt.text(x, y, eq, ha='center', va='center', color="#11557c", alpha=alpha,
                 transform=plt.gca().transAxes, fontsize=size, clip_on=True)
    
    plt.xticks([]), plt.yticks([])
    plt.show()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NDQ5NTY3OA_size_16_color_FFFFFF_t_70 25]

import matplotlib.pyplot as plt
    import numpy as np
    def f(x,y):
        return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
    n = 256
    x = np.linspace(-3,3,n)
    y = np.linspace(-3,3,n)
    X,Y = np.meshgrid(x,y)
    plt.contourf(X,Y,f(X,Y),8,alpha=0.75,cmap=plt.cm.hot)
    C = plt.contour(X,Y,f(X,Y),8,colors='black',lw=0.5)    #等高线分多少部分
    plt.clabel(C,inline=True,fontsize=10)
     
    plt.xticks(())
    plt.yticks(())
    plt.show()

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