Python的Matplotlib库图像复现学习

时间:2022-05-14 03:14:22

Python的Matplotlib库图像复现学习

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from pylab import *
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='b',alpha=.25)
plt.plot (x, y-1, color='blue', alpha=1.00)
plt.fill_between(x,-1,y-1,(y-1)>-1,color='b',alpha=.25)
plt.fill_between(x,-1,y-1,(y-1)<-1,color='r',alpha=.25)
plt.xticks([])
plt.yticks([])
plt.show()

Python的Matplotlib库图像复现学习

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from pylab import *
n = 1024
x = np.random.normal(0,1,n)
y = np.random.normal(0,1,n)
t=np.arctan2(y,x)
plt.axes([0.025,0.025,0.95,0.95])
plt.scatter(x,y,s=60,c=t,alpha=.5)
plt.xlim(-1.5,1.5)
plt.ylim(-1.5,1.5)
plt.xticks([])
plt.yticks([])
plt.show()

Python的Matplotlib库图像复现学习

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from pylab import *
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='#9999ff', edgecolor='white')
plt.bar(x, -y2, facecolor='#ff9999', edgecolor='white')
for x,y in zip(x,y1):
    plt.text(x, y+0.05, '%.2f' % y, ha='center', va= 'bottom')
 
for x1,y1 in zip(x,y2):
    plt.text(x1, -y1-0.05, '%.2f' % y1, ha='center', va= 'top')
 
plt.xlim(-.5,n),plt.xticks([])
plt.ylim(-1.25,+1.25),plt.yticks([])
plt.show()

Python的Matplotlib库图像复现学习

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from pylab import *
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.axes([0.025,0.025,0.95,0.95])
plt.contourf(x,y,f(x,y),8, alpha=.75, cmap=plt.cm.hot)
c = plt.contour(x, y, f(x,y), 8, colors='black', linewidth=.5)
plt.clabel(c,inline=1,fontsize=10)
plt.xticks([]),plt.yticks([])
plt.show()

Python的Matplotlib库图像复现学习

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from pylab import *
def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
n = 10
x = np.linspace(-3,3,4*n)
y = np.linspace(-3,3,3*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='bicubic',cmap='bone',origin='lower')
plt.colorbar(shrink=.92)
plt.xticks([]), plt.yticks([])

Python的Matplotlib库图像复现学习

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from mpl_toolkits.mplot3d import axes3d
fig=plt.figure()
ax=axes3d(fig)
x=np.arange(-4.0,4.0,0.25)
y=np.arange(-4.0,4.0,0.25)
x,y=np.meshgrid(x,y)
z=np.sin(np.sqrt(x**2+y**2))
surf=ax.plot_surface(x,y,z,
 rstride=1,
 cstride=1,
 cmap=plt.get_cmap('rainbow'))
ax.contourf(x,y,z,zdir='z',offset=-2,cmap=plt.cm.hot)
ax.set_zlim(-2,2)
fig.colorbar(surf,shrink=0.5,aspect=8)

总结

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原文链接:https://blog.csdn.net/qq_41634258/article/details/119789922