#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,line,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,line)

    # plt.annotate("cos(1)",xy=(t,np.cos(1)),xycoords="data",xytext=(+10,+30),textcoords="offset points",arrowprops=dict(arrow,connection))

    #

    # 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()