第python繪制三維圖的詳細新手教程#Makeradiiandanglesspaces(radiusr=0omittedtoeliminateduplication).

radii=np.linspace(0.125,1.0,n_radii)

angles=np.linspace(0,2*np.pi,n_angles,endpoint=False)

#Repeatallanglesforeachradius.

angles=np.repeat(angles[...,np.newaxis],n_radii,axis=1)

#Convertpolar(radii,angles)coordstocartesian(x,y)coords.

#(0,0)ismanuallyaddedatthisstage,sotherewillbenoduplicate

#pointsinthe(x,y)plane.

x=np.append(0,(radii*np.cos(angles)).flatten())

y=np.append(0,(radii*np.sin(angles)).flatten())

#Computeztomakethepringlesurface.

z=np.sin(-x*y)

fig=plt.figure()

ax=fig.gca(projection='3d')

ax.plot_trisurf(x,y,z,linewidth=0.2,antialiased=True)

plt.show()

七、等高線（Contourplots）

基本用法：

ax.contour(X,Y,Z,*args,**kwargs)

code:

frommpl_toolkits.mplot3dimportaxes3d

importmatplotlib.pyplotasplt

frommatplotlibimportcm

fig=plt.figure()

ax=fig.add_subplot(111,projection='3d')

X,Y,Z=axes3d.get_test_data(0.05)

cset=ax.contour(X,Y,Z,cmap=cm.coolwarm)

ax.clabel(cset,fontsize=9,inline=1)

plt.show()

二維的等高線，同樣可以配合三維表面圖一起繪制：

code:

frommpl_toolkits.mplot3dimportaxes3d

frommpl_toolkits.mplot3dimportaxes3d

importmatplotlib.pyplotasplt

frommatplotlibimportcm

fig=plt.figure()

ax=fig.gca(projection='3d')

X,Y,Z=axes3d.get_test_data(0.05)

ax.plot_surface(X,Y,Z,rstride=8,cstride=8,alpha=0.3)

cset=ax.contour(X,Y,Z,zdir='z',offset=-100,cmap=cm.coolwarm)

cset=ax.contour(X,Y,Z,zdir='x',offset=-40,cmap=cm.coolwarm)

cset=ax.contour(X,Y,Z,zdir='y',offset=40,cmap=cm.coolwarm)

ax.set_xlabel('X')

ax.set_xlim(-40,40)

ax.set_ylabel('Y')

ax.set_ylim(-40,40)

ax.set_zlabel('Z')

ax.set_zlim(-100,100)

plt.show()

也可以是三維等高線在二維平面的投影：

code:

frommpl_toolkits.mplot3dimportaxes3d

importmatplotlib.pyplotasplt

frommatplotlibimportcm

fig=plt.figure()

ax=fig.gca(projection='3d')

X,Y,Z=axes3d.get_test_data(0.05)

ax.plot_surface(X,Y,Z,rstride=8,cstride=8,alpha=0.3)

cset=ax.contourf(X,Y,Z,zdir='z',offset=-100,cmap=cm.coolwarm)

cset=ax.contourf(X,Y,Z,zdir='x',offset=-40,cmap=cm.coolwarm)

cset=ax.contourf(X,Y,Z,zdir='y',offset=40,cmap=cm.coolwarm)

ax.set_xlabel('X')

ax.set_xlim(-40,40)

ax.set_ylabel('Y')

ax.set_ylim(-40,40)

ax.set_zlabel('Z')

ax.set_zlim(-100,100)

plt.show()

八、Barplots（條形圖）

基本用法：

ax.bar(left,height,zs=0,zdir='z',*args,**kwargs

x，y，zs=z，數(shù)據(jù)zdir:條形圖平面化的方向，具體可以對應代碼理解。

code:

frommpl_toolkits.mplot3dimportAxes3D

importmatplotlib.pyplotasplt

importnumpyasnp

fig=plt.figure()

ax=fig.add_subplot(111,projection='3d')

forc,zinzip(['r','g','b','y'],[30,20,10,0]):

xs=np.arange(20)

ys=np.random.rand(20)

#Youcanprovideeitherasinglecolororanarray.Todemonstratethis,

#thefirstbarofeachsetwillbecoloredcyan.

cs=[c]*len(xs)

cs[0]='c'

ax.bar(xs,ys,zs=z,zdir='y',color=cs,alpha=0.8)

ax.set_xlabel('X')

ax.set_ylabel('Y')

ax.set_zlabel('Z')

plt.show()

九、子圖繪制（subplot）

A-不同的2-D圖形，分布在3-D空間，其實就是投影空間不空，對應code:

frommpl_toolkits.mplot3dimportAxes3D

importnumpyasnp

importmatplotlib.pyplotasplt

fig=plt.figure()

ax=fig.gca(projection='3d')

#Plotasincurveusingthexandyaxes.

x=np.linspace(0,1,100)

y=np.sin(x*2*np.pi)/2+0.5

ax.plot(x,y,zs=0,zdir='z',label='curvein(x,y)')

#Plotscatterplotdata(202Dpointspercolour)onthexandzaxes.

colors=('r','g','b','k')

x=np.random.sample(20*len(colors))

y=np.random.sample(20*len(colors))

c_list=[]

forcincolors:

c_list.append([c]*20)

#Byusingzdir='y',theyvalueofthesepointsisfixedtothezsvalue0

#andthe(x,y)pointsareplottedonthexandzaxes.

ax.scatter(x,y,zs=0,zdir='y',c=c_list,label='pointsin(x,z)')

#Makelegend,setaxeslimitsandlabels

ax.legend()

ax.set_xlim(0,1)

ax.set_ylim(0,1)

ax.set_zlim(0,1)

ax.set_xlabel('X')

ax.set_ylabel('Y')

ax.set_zlabel('Z')

B-子圖Subplot用法

與MATLAB不同的是，如果一個四子圖效果，如：

MATLAB：

subplot(2,2,1)

subplot(2,2,2)

subplo