Python绘制3D色温球

deflxz_plotball(mapdata,alpha=0.6,colormap='plasma'):
#deflxz_plotball(phinum,thetanum,mapdata,alpha=0.6,colormap='plasma'):
 
   %matplotlib widget
   from mpl_toolkits.mplot3d import Axes3D
   import matplotlib.pyplot as plt
   import numpy as np
   #from matplotlib import cm
   mapdata=np.rot90(mapdata);#行列的物理意义换算到显示维度。
   mycolormap = plt.get_cmap(colormap);
   mapminvalue=mapdata.min();mapmaxvalue=mapdata.max();
    #根据三维数组中的最大和最小值来定义每个数值的相对强度,范围0~1.0
 
   relativevalue=np.zeros((mapdata.shape[0],mapdata.shape[1]));
    #色温强度矩阵大小与xyz测试数组大小一致
 
   for i in range(0,relativevalue.shape[0]):
       for j in range(0,relativevalue.shape[1]):
                relativevalue[i][j]=round(mapdata[i][j]/mapmaxvalue,1);#保留1位小数，意味着10个色度，不过肉眼已经难以区分。
 
   colorsvalues = np.empty(mapdata.shape, dtype=object)
 
 
   for i in range(0,relativevalue.shape[0]):
       for j in range(0,relativevalue.shape[1]):
           tempc=mycolormap(relativevalue[i][j]);
   #tempc为tuple变量,存储当前数值的颜色值(R,G,B,Alpha)
   
           colorreal=(tempc[0],tempc[1],tempc[2],alpha);
   #tuple为不可变数据类型,所以替换自定义alpha值时需要重新定义
   
           colorsvalues[i][j]=colorreal;
    #最终每个数值所对应的颜色
   fsize = 15
   tsize = 18
   
   tdir = 'in'
   
   major = 5.0
   minor = 3.0
   
   style = 'default'
   plt.style.use(['science','ieee','no-latex'])
   plt.style.use(style)
   #plt.rcParams['text.usetex'] = True
   plt.rcParams['font.size'] = fsize
   plt.rcParams['legend.fontsize'] = tsize
   plt.rcParams['xtick.direction'] = tdir
   plt.rcParams['ytick.direction'] = tdir
   plt.rcParams['xtick.major.size'] = major
   plt.rcParams['xtick.minor.size'] = minor
   plt.rcParams['ytick.major.size'] = major
   plt.rcParams['ytick.minor.size'] = minor
 
   fig = plt.figure(num=1,figsize=(8,6));
   #ax = fig.add_subplot(111, projection='3d')
   ax = Axes3D(fig);#在窗口上添加3D坐标轴
   
    u= np.linspace(0,2*np.pi, mapdata.shape[0]);
    v= np.linspace(0, np.pi, mapdata.shape[1]);
   
    x= np.outer(np.cos(u), np.sin(v));
    y= np.outer(np.sin(u), np.sin(v));
    z= np.outer(np.ones(np.size(u)), np.cos(v));
    #
   #C = np.cos(x)
   #testc=cm.jet(x);
   #testc[2][2][2]=0.2;
   #c = np.random.random((32,16, 4))
    #
   #aa=ax.plot_surface(x, y, z, facecolors = c,edgecolor=None,cmap =plt.get_cmap('Spectral')) # Look how I gave a variable to the facecolors.
   #figmap=ax.plot_surface(x, y, z,edgecolor=None,cmap = plt.get_cmap(colormap),rstride=1,cstride=1) # Look how I gave a variable to the facecolors.
   figmap=ax.plot_surface(x, y, z, facecolors=colorsvalues,edgecolor=None,cmap = plt.get_cmap(colormap),rstride=1,cstride=1) # Look how I gave a variable to the facecolors.
 
   #ax.plot_surface(x, y, z, facecolors = cm.jet(C), rstride=4, cstride=4)# Look how I gave a variable to the facecolors.
   plt.colorbar(figmap,shrink=0.8);#防止bar太高
   
   plt.show();#plt.axis('equal');#plt.axis('scaled');

test_mapdata=pd.read_excel('test0816.xlsx',header=None)