Python绘制真正意义上的3D体素色温图

import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
#matplot模仿matlab,两者绘图函数大致相同.numpy用于创建数组,且内置计算函数很强

mycolormap = plt.get_cmap('plasma')

xyzvalues = np.random.choice(range(0,10), size=(10,10,10))
#数组大小:10*10*10, 数值范围0~9.

xyzminvalue=xyzvalues.min();xyzmaxvalue=xyzvalues.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((10,10,10))
#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]):
        for k in range(0,relativevalue.shape[2]):
            relativevalue[i][j][k]=round(xyzvalues[i][j][k]/xyzmaxvalue,1)
#round函数取小数点后1位

colorsvalues = np.empty(xyzvalues.shape, dtype=object)
alpha=0.5
#透明度,视显示效果决定

for i in range(0,relativevalue.shape[0]):
    for j in range(0,relativevalue.shape[1]):
        for k in range(0,relativevalue.shape[2]):
            tempc=mycolormap(relativevalue[i][j][k])
#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][k]=colorreal
#最终每个数值所对应的颜色

fig = plt.figure(figsize=(7, 4.5))
# Make a figure and axes with dimensions as desired.
#需要注意的是,3Dplot不支持设置xyz的比例尺相同,这就带来了一些麻烦:
#保存图片时长宽比例受限,这个问题以后再做说明解决

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

#ax.voxels(xyzvalues, facecolors=colorsvalues, edgecolor='k',shade=False,)
ax.voxels(xyzvalues, facecolors=colorsvalues, edgecolor=None,shade=False,)
#关键函数voxels:用以无缝绘制每个像素格

ax.set_xlabel('X');ax.set_ylabel('Y');ax.set_zlabel('Z')
ax.set_title('3D Voxel Map')

#新建区域ax1,用以额外绘制colorbar
#ref:https://matplotlib.org/examples/api/colorbar_only.html
#位置为figure的百分比,从figure 0%的位置开始绘制, 高是figure的80%
left, bottom, width, height = 0.1, 0.1, 0.05, 0.8
#获得绘制的句柄
ax1 = fig.add_axes([left, bottom, width, height])

# Set the colormap and norm to correspond to the data for which
# the colorbar will be used.
cmap = mpl.cm.plasma 
#colormap与绘制voxel图保持一致
norm = mpl.colors.Normalize(vmin=xyzminvalue, vmax=xyzmaxvalue)
#色温colorbar的数值范围可选择实际xyz数组中的数值范围(其实不应该从0开始)

cb1 = mpl.colorbar.ColorbarBase(ax1, cmap=cmap,
                                norm=norm,
                                orientation='vertical')
cb1.set_label('Units')

#plt.show() # do not save the fig behind the show() method, otherwise will be a white pad
plt.savefig('pic-20201017-3dvoxel-hsv.png',dpi=600)