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#encoding=utf-8 import numpy as np def main(): import matplotlib.pyplot as plt ##lesson1:画图 # x = np.linspace(-1, 1, 50) # x=np.linspace(-np.pi,np.pi,256,endpoint=True) # c,s=np.cos(x),np.sin(x) # plt.figure(1) # plt.plot(x,c,color="blue",linewidth=1.0,linestyle="-",label="COS",alpha=0.5) # plt.plot(x,s,"r*",label="SIN") # plt.title("COS & SIN") # ##设置坐标轴 # ax=plt.gca() # ax.spines["right"].set_color("none") # ax.spines["top"].set_color("none") # ax.spines["left"].set_position(("data",0)) # ax.spines["bottom"].set_position(("data",0)) # ax.xaxis.set_ticks_position("bottom") # ax.yaxis.set_ticks_position("left") # ##网格填充 # plt.grid() # plt.fill_between(x,np.abs(x)<0.5,c,c>0.5,color="green",alpha=0.25) # ##注释 # t=1 # plt.plot([t,t],[0,np.cos(t)],"y",linewidth=3,linestyle="--") # plt.annotate("cos(1)",xy=(t,np.cos(1)),xycoords="data",xytext=(+10,+30),textcoords="offset points",arrowprops=dict(arrowstyle="->",connectionstyle="arc3,rad=.2")) # # plt.show() ##lesson2:数据分析常见图形 ##散点图scatter # fig=plt.figure() # ax=fig.add_subplot(3,3,1) # n=128 # X=np.random.normal(0,1,n)#随机数 # Y=np.random.normal(0,1,n)#随机数 # T=np.arctan2(Y,X)#上色 # #plt.axes([0.025,0.025,0.95,0.95])#指定现实范围 # #plt.scatter(X,Y,s=75,c=T,alpha=0.5)#画散点 # ax.scatter(X, Y, s=75, c=T, alpha=0.5) # 画散点 # plt.xlim(-1.5,1.5),plt.xticks([])#X范围 # plt.ylim(-1.5,1.5),plt.yticks([])#Y范围 # plt.axis() # plt.title("scatter") # plt.xlabel("x") # plt.ylabel("y") # plt.show() # #bar柱状图 # fig = plt.figure() # 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') # # plt.show() # #pie饼状图 # fig = plt.figure() # 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([]) # plt.show() # #polar极线图 # fig = plt.figure() # 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) # plt.show() #heatmap热力图 # fig=plt.figure() # fig.add_subplot(335) # from matplotlib import cm # data=np.random.rand(3,3) # cmap=cm.Blues # map=plt.imshow(data,interpolation='nearest',cmap=cmap,aspect='auto',vmin=0,vmax=1) # plt.show() # #3D图 # fig=plt.figure() # ax=fig.add_subplot(336,projection="3d") # ax.scatter(1,1,3,s=100) # plt.show() # #hot map热图 # fig=plt.figure() # 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.show() # # ##保存图片 # plt.savefig("./data/fig.png") if __name__ == '__main__': main()
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