import numpy as np
import matplotlib.pyplot as plt
def main():
#scatter
fig = plt.figure()
ax = fig.add_subplot(3,3,1)
n = 128
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])
ax.scatter(X,Y,s=75,c=T,alpha=.5)
plt.xlim(-1.5,1.5), plt.xticks([])
plt.ylim(-1.5,1.5), plt.yticks([])
plt.axis()
plt.title('scatter')
plt.xlabel('x')
plt.ylabel('y')

#bar  
fig.add\_subplot(332)  
n =10  
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 + 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')

#Pie  
fig.add\_subplot(333)  
n = 20  
Z = np.ones(n)  
Z\[-1\] \*=2  
plt.pie(Z,explode=Z \* .05,colors=\['%f' % (i / float(n)) for i in range(n)\],  
        labels=\['%.2f' % (i/float(n)) for i in range(n)\])  
plt.gca().set\_aspect('equal')  
plt.xticks(\[\]),plt.yticks(\[\])

#polar  
fig.add\_subplot(334,polar =True)  
n = 20  
theta = np.arange(0.0, 2\* np.pi, 2\*np.pi /n)  
radii = 10 \* np.random.rand(n)  

# plt.plot(theta, radii)
plt.polar(theta,radii)
#heatmap
fig.add_subplot(335)
from matplotlib import cm
data = np.random.rand(3,3)
# print(data)
cmap =cm.Blues
map= plt.imshow(data,interpolation='nearest',cmap=cmap,aspect='auto',vmin=0,vmax=1)
#3D
from mpl_toolkits.mplot3d import Axes3D
ax = fig.add_subplot(336,projection='3d')
ax.scatter(1,1,3,s =100)
#hot map
fig.add_subplot(313)
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=.75,cmap=plt.cm.hot)
plt.savefig('D:/fig.png')
plt.show()

if __name__ == '__main__':
main()