山东大学《Python程序设计与大数据分析》lab9

矫情吗；* 2023-07-03 03:28 9阅读 0赞

## 实验九：科学计算和可视化 ##

##### 一、实验类型：验证型、设计型 #####

##### 二、建议学时：4 #####

##### 三、实验目的：掌握用Python 语言设计科学计算和可视化程序 #####

##### 四、实验内容： #####

1、阅读教材《Python 语言程序设计基础》第9章：科学计算和可视化  
2、验证型练习：

*  2.1、验证9.2 模块8：numpy库的使用中的表9.1-9.7中的各个方法和函数（不用交）
 *  2.2、验证9.3.2 图像的手绘效果中的实例代码17.1
 *  2.3、 验证9.4 模块9：matplotlib库的使用中的表9.8-914中的各个方法和函数（不用交）
 *  2.4、验证9.3.2 微实例9.1-9.3，实例18.1 2.5、9.6 中的验证实例19.1

3、设计型练习：教材P259的 9.3,9.4,9.5

##### 五、实验过程及代码： #####

**①验证性练习：**  
2.2、验证9.3.2 图像的手绘效果中的实例代码17.1

#e17.1HandDrawPic.py
    from PIL import Image
    import numpy as np
    vec_el = np.pi/2.2 # 光源的俯视角度，弧度值
    vec_az = np.pi/4. # 光源的方位角度，弧度值
    depth = 10. # (0-100)
    im = Image.open('C:\\Users\\pc\\Desktop\\sdurj1.jpg').convert('L')
    a = np.asarray(im).astype('float')
    grad = np.gradient(a) #取图像灰度的梯度值
    grad_x, grad_y = grad #分别取横纵图像梯度值
    grad_x = grad_x*depth/100.
    grad_y = grad_y*depth/100.
    dx = np.cos(vec_el)*np.cos(vec_az) #光源对x 轴的影响
    dy = np.cos(vec_el)*np.sin(vec_az) #光源对y 轴的影响
    dz = np.sin(vec_el) #光源对z 轴的影响
    A = np.sqrt(grad_x**2 + grad_y**2 + 1.)
    uni_x = grad_x/A
    uni_y = grad_y/A
    uni_z = 1./A
    a2 = 255*(dx*uni_x + dy*uni_y + dz*uni_z) #光源归一化
    a2 = a2.clip(0,255)
    im2 = Image.fromarray(a2.astype('uint8')) #重构图像
    im2.save('C:\\Users\\pc\\Desktop\\sdurj2.jpg')

`原图 （sdurj1.jpg）`![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70]  
`手绘图（sdurj2.jpg）`![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 1]

2.4、验证9.3.2 微实例9.1-9.3，实例18.1

#m9.1PlotTriangle.py
    import numpy as np
    import matplotlib.pyplot as plt
    x=np.linspace(0,6,100)
    y=np.cos(2*np.pi*x)*np.exp(-x)+0.8
    plt.plot(x,y,'k',color='r',linewidth=3,linestyle="-")
    plt.show()

验证结果：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 2]

#m9.2PlotCoordinate.py
    import matplotlib.pyplot as plt
    import matplotlib
    matplotlib.rcParams['font.family']=['SimHei']
    matplotlib.rcParams['font.sans-serif']=['SimHei']
    plt.plot([1,2,4],[1,2,3])
    plt.title("坐标系标题")
    plt.xlabel('时间(s)')
    plt.ylabel('范围(m)')
    plt.xticks([1,2,3,4,5],[r'$\pi/3$',r'$2\pi/3$',r'$\pi$',\
               r'$4\pi/3$',r'$5\pi/3$'])
    plt.show()

验证结果：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 3]

#m9.3PlotDarkCoordinate.py
    import matplotlib.pyplot as plt
    import numpy as np
    x=np.linspace(0,10,1000)
    y=np.cos(2*np.pi*x)*np.exp(-x)+0.8
    plt.plot(x,y,'k',color='r',label="$exp-decay$",linewidth=3)
    plt.axis([0,6,0,1.8])
    ix=(x>0.8)&(x<3)
    plt.fill_between(x,y,0,where=ix,\
                     facecolor='grey',alpha=0.25)
    plt.text(0.5*(0.8+3),0.2,r"$\int_a^b f(x)\mathrm{d}x$",\
             horizontalalignment='center')
    plt.legend()
    plt.show()

验证结果：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 4]

#e18.1PlotDamping.py
    import matplotlib.pyplot as plt
    import numpy as np
    import matplotlib
    matplotlib.rcParams['font.family']=['SimHei']
    matplotlib.rcParams['font.sans-serif']=['SimHei']
    def Draw(pcolor,nt_point,nt_text,nt_size):
        plt.plot(x,y,'k',color=pcolor,label="$exp-decay$",\
                 linewidth=3,linestyle="-")
        plt.plot(x,z,"b--",label="$cos(x^2)$",linewidth=1)
        plt.xlabel('时间(s)')
        plt.ylabel('幅度(mV)')
        plt.title("阻尼衰减曲线绘制")
        plt.annotate('$\cos(2 \pi t) \exp(-t)$',xy=nt_point,\
                     xytext=nt_text,fontsize=nt_size,arrowprops=\
                     dict(arrowstyle='->',connectionstyle="arc3,rad=.1"))
    def Shadow(a,b):
        ix=(x>a)&(x<b)
        plt.fill_between(x,y,0,where=ix,facecolor='grey',alpha=0.25)
        plt.text(0.5*(a+b),0.2,r"$\int_a^b f(x)\mathrm{d}x$",\
             horizontalalignment='center')
    def XY_Axis(x_start,x_end,y_start,y_end):
        plt.xlim(x_start,x_end)
        plt.ylim(y_start,y_end)
        plt.xticks([np.pi/3,2*np.pi/3,1*np.pi,4*np.pi/3,5*np.pi/3],\
                   ['$\pi/3$','$2\pi/3$','$\pi$','$4\pi/3$','$5\pi/3$'])    
    x=np.linspace(0.0,6.0,100)
    y=np.cos(2*np.pi*x)*np.exp(-x)+0.8
    z=0.5*np.cos(x**2)+0.8
    note_point,note_text,note_size=(1,np.cos(2*np.pi)*\
                                    np.exp(-1)+0.8),(1,1.4),14
    fig=plt.figure(figsize=(8,6),facecolor="white")
    plt.subplot(111)
    Draw("red",note_point,note_text,note_size)
    XY_Axis(0,5,0,1.8)
    Shadow(0.8,3)
    plt.legend()
    plt.savefig('sample.JPG')
    plt.show()

验证结果：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 5]

2.5、9.6 中的验证实例19.1

#e19.1DrawDotaRadar.py
    import matplotlib.pyplot as plt
    import numpy as np
    import matplotlib
    matplotlib.rcParams['font.family']=['SimHei']
    matplotlib.rcParams['font.sans-serif']=['SimHei']
    labels=np.array(['综合','KDA','发育','推进','生存','输出'])
    nAttr=6
    data=np.array([7,5,6,9,8,7])
    angles=np.linspace(0,2*np.pi,nAttr,endpoint=False)
    data=np.concatenate((data,[data[0]]))
    angles=np.concatenate((angles,[angles[0]]))
    fig=plt.figure(facecolor="white")
    plt.subplot(111,polar=True)
    plt.plot(angles,data,'bo-',color='g',linewidth=2)
    plt.fill(angles,data,facecolor='g',alpha=0.25)
    plt.thetagrids(angles*180/np.pi,labels)
    plt.figtext(0.52,0.95,'DOTA能力值雷达图',ha='center')
    plt.grid(True)
    plt.savefig('dota_radar.JPG')
    plt.show()

验证结果：![在这里插入图片描述][20200114234318851.png]

**②设计型练习：教材P259的 9.3,9.4,9.5**  
9.3、（通过修改相应参数得到想要的效果）

from PIL import Image
    import numpy as np
    vec_el = np.pi/2
    vec_az = np.pi/2
    depth = 10
    im = Image.open('C:\\Users\\pc\\Desktop\\哪吒.jpg').convert('L')
    a = np.asarray(im).astype('float')
    grad = np.gradient(a)
    grad_x, grad_y = grad
    grad_x = grad_x*depth/40.
    grad_y = grad_y*depth/40.
    dx = np.cos(vec_el)*np.cos(vec_az) 
    dy = np.cos(vec_el)*np.sin(vec_az)
    dz = np.sin(vec_el) 
    A = np.sqrt(grad_x**2 + grad_y**2 + 1.)
    uni_x = grad_x/A
    uni_y = grad_y/A
    uni_z = 1./A
    a2 = 255*(dx*uni_x + dy*uni_y + dz*uni_z)
    a2 = a2.clip(0,255)
    im2 = Image.fromarray(a2.astype('uint8'))
    im2.save('C:\\Users\\pc\\Desktop\\哪吒手绘.jpg')

验证结果：  
`原图:（cr微博@随手保存SE）`![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 6]  
`手绘版:`![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 7]

9.4、

import matplotlib.pyplot as plt
    import numpy as np
    import matplotlib
    import math
    matplotlib.rcParams['font.family']=['SimHei']
    matplotlib.rcParams['font.sans-serif']=['SimHei']
    def Draw(pcolor,nt_point,nt_text,nt_size):   
        plt.axhline(y=0,color='black',linewidth=2,linestyle='--')#绘制水平直线
        plt.plot(x,y,'k',color=pcolor,label="$sin(x)$",\
                 linewidth=3,linestyle="-")
        plt.plot(x,z,"b-",label="$cos(x)$",linewidth=3)
        plt.xlabel('x')
        plt.ylabel('y')
        plt.title("三角函数曲线绘制")
    def XY_Axis(x_start,x_end,y_start,y_end):
        plt.xlim(x_start,x_end)
        plt.ylim(y_start,y_end)
        plt.xticks([0,np.pi/2,np.pi,3*np.pi/2,2*np.pi],\
                   ['$0$','$\pi/2$','$\pi$','$3\pi/2$','$2\pi$'])    
    
    x=np.linspace(0.0,8.0,100)
    y=np.sin(x)
    z=np.cos(x)
    note_point,note_text,note_size=(1,np.cos(2*np.pi)*\
                                    np.exp(-1)+0.8),(1,1.4),14
    fig=plt.figure(figsize=(8,6),facecolor="white")
    plt.subplot(111)
    Draw("red",note_point,note_text,note_size)
    XY_Axis(0,np.pi/2,-1.2,1.2)
    plt.legend()
    plt.show()

验证结果：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 8]

9.5、

import matplotlib.pyplot as plt
    import numpy as np
    import matplotlib
    matplotlib.rcParams['font.family']=['SimHei']
    matplotlib.rcParams['font.sans-serif']=['SimHei']
    labels=np.array(['综合','发球','杀球','胜率'])
    nAttr=4
    data=np.array([7,6,8,5])
    angles=np.linspace(0,2*np.pi,nAttr,endpoint=False)
    data=np.concatenate((data,[data[0]]))
    angles=np.concatenate((angles,[angles[0]]))
    fig=plt.figure(facecolor="white")
    plt.subplot(111,polar=True)
    plt.plot(angles,data,'bo-',color='b',linewidth=2)
    plt.fill(angles,data,facecolor='b',alpha=0.25)
    plt.thetagrids(angles*180/np.pi,labels)
    plt.figtext(0.52,0.95,'乒乓球选手雷达图',ha='center')
    plt.grid(True)
    plt.show()

验证结果：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 9]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20200114235320737.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20200114235342340.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 2]: https://img-blog.csdnimg.cn/20200114234647681.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 3]: https://img-blog.csdnimg.cn/20200114234439641.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 4]: https://img-blog.csdnimg.cn/20200114234406290.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 5]: https://img-blog.csdnimg.cn/20200114234347475.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[20200114234318851.png]: https://img-blog.csdnimg.cn/20200114234318851.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 6]: https://img-blog.csdnimg.cn/20200114234248193.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 7]: https://img-blog.csdnimg.cn/20200114234248807.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 8]: https://img-blog.csdnimg.cn/20200114234232226.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ_size_16_color_FFFFFF_t_70 9]: https://img-blog.csdnimg.cn/20200114234200285.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80Mzk1OTQyMQ==,size_16,color_FFFFFF,t_70