numpy库和matplotlib库的使用
1 import matplotlib.pyplot as plt 2 import numpy as np 3 x=np.linspace(0,10,100) 4 y=np.cos(2*np.pi*x)*np.exp(-x)+0.8 5 plt.plot(x,y,'k',color='r',label="$exp-decay$",linewidth=3) 6 plt.axis([0,6,0,1.8]) 7 ix=(x>0.8)&(x<3) 8 plt.fill_between(x,y,where=ix,facecolor='grey',alpha=0.25) 9 plt.text(0.5*(0.8+3),0.2,r"$\int_a^b f(x)\mathrm{d}x$",horizontalalignment='center') 10 plt.legend() 11 plt.show()
1.带阴影部分的坐标系
2.成绩雷达图
1 import numpy as np 2 import matplotlib.pyplot as plt 3 import matplotlib 4 matplotlib.rcParams['font.family']='SimHei' 5 matplotlib.rcParams['font.sans-serif']=['SimHei'] 6 labels=np.array(['第一周','第二周','第三周','第四周','第五周','第六周']) 7 nAttr=6 8 data=np.array([50,86.7,90,100,105,60]) 9 angles=np.linspace(0,2*np.pi,nAttr,endpoint=False) 10 data=np.concatenate((data,[data[0]])) 11 angles=np.concatenate((angles,[angles[0]])) 12 fig=plt.figure(facecolor="white") 13 plt.subplot(111,polar=True) 14 plt.plot(angles,data,'bo-',color='b',linewidth=2) 15 plt.fill(angles,data,facecolor='b',alpha=0.25) 16 plt.thetagrids(angles*180/np.pi,labels) 17 plt.figtext(0.52,0.95,'python123作业成绩',ha='center') 18 plt.grid(True) 19 plt.savefig('dota_radar.JPG') 20 plt.show
3.手绘
1 from PIL import Image 2 import numpy as np 3 vec_el=np.pi/2.2 4 vec_az=np.pi/4 5 depth=10 6 im=Image.open("manhua.jpg").convert('L') 7 a=np.asarray(im).astype('float') 8 grad=np.gradient(a) 9 grad_x,grad_y=grad 10 grad_x=grad_x*depth/100 11 grad_y=grad_y*depth/100 12 dx=np.cos(vec_el)*np.cos(vec_az) 13 dy=np.cos(vec_el)*np.sin(vec_az) 14 dz=np.sin(vec_el) 15 A=np.sqrt(grad_x**2+grad_y**2+1) 16 uni_x=grad_x/A 17 uni_y=grad_y/A 18 uni_z=1/A 19 a2=255*(dx*uni_x+dy*uni_y+dz*uni_z) 20 a2=a2.clip(0,255) 21 im2=Image.fromarray(a2.astype('uint8')) 22 im2.save('shouhui.jpg')
