Python: surface color is RGB coloar but colorbar is not

Question

My question is how to match RGB color with the colorbar. The input data is normalized to put in color.

My project is to represents the local indoor CO2 concentration, so I first made a cube with the help of the site below.

python draw parallelepiped

In sample code, the RGB color corresponds the random sampled coordinates.Later, the concentration is added and normalized to corresponds to color. My terminal goal is to represent cubes like this. enter image description here

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection

def plot_cube(cube_definition):
    cube_definition_array = [
        np.array(list(item))
        for item in cube_definition
    ]

 points = []
    points += cube_definition_array
    vectors = [
        cube_definition_array[1] - cube_definition_array[0],
        cube_definition_array[2] - cube_definition_array[0],
        cube_definition_array[3] - cube_definition_array[0]
    ]

    points += [cube_definition_array[0] + vectors[0] + vectors[1]]
    points += [cube_definition_array[0] + vectors[0] + vectors[2]]
    points += [cube_definition_array[0] + vectors[1] + vectors[2]]
    points += [cube_definition_array[0] + vectors[0] + vectors[1] + vectors[2]]

    points = np.array(points)

    edges = [
        [points[0], points[3], points[5], points[1]],
        [points[1], points[5], points[7], points[4]],
        [points[4], points[2], points[6], points[7]],
        [points[2], points[6], points[3], points[0]],
        [points[0], points[2], points[4], points[1]],
        [points[3], points[6], points[7], points[5]]
    ]
     faces = Poly3DCollection(edges, linewidths=1, edgecolors='k')

    faces.set_facecolor(cube_definition[0])
    ax.add_collection3d(faces)



data_number = 20
pre_data = np.random.random((data_number,3))

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.set_xlim(-1,2.2) 
ax.set_ylim(-1,2.2)
ax.set_zlim(-1,2.2)
ax.set_ylabel(r'y')  
ax.set_xlabel(r'x')  
ax.set_zlabel(r'z')
p= ax.scatter(pre_data[:,0], pre_data[:,1], pre_data[:,2] ,s=0, c=pre_data)
fig.colorbar(p)
for i in range(0,data_number):
    data = [pre_data[i],pre_data[i]+(0,1,0),pre_data[i]+(0,0,1),pre_data[i]+(1,0,0)]    
    plot_cube(data)

enter image description here

============================== I did

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection
import matplotlib.colorbar as cbar
from matplotlib import cm
from pylab import get_cmap
import matplotlib as mpl

def edges(crd):

delta = 0.5
start_crd= crd - (delta, delta, delta)

cube_definition_array = [
    start_crd,start_crd+(0,delta,0),start_crd+(0,0,delta),start_crd+(delta,0,0)
]

points = []
points += cube_definition_array
vectors = [
    cube_definition_array[1] - cube_definition_array[0],
    cube_definition_array[2] - cube_definition_array[0],
    cube_definition_array[3] - cube_definition_array[0]
]

points += [cube_definition_array[0] + vectors[0] + vectors[1]]
points += [cube_definition_array[0] + vectors[0] + vectors[2]]
points += [cube_definition_array[0] + vectors[1] + vectors[2]]
points += [cube_definition_array[0] + vectors[0] + vectors[1] + vectors[2]]

points = np.array(points)

edges = [
    [points[0], points[3], points[5], points[1]],
    [points[1], points[5], points[7], points[4]],
    [points[4], points[2], points[6], points[7]],
    [points[2], points[6], points[3], points[0]],
    [points[0], points[2], points[4], points[1]],
    [points[3], points[6], points[7], points[5]]
]
return edges

data_number = 20
pre_data = np.random.random((data_number,3)) # coordinate
concentration = np.linspace(0,20, data_number)

def plot_cube(crd, concentration):
    norm = mpl.colors.Normalize(vmin=-1, vmax=1)
    norm_c = norm(concentration)
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    for i in range(0,len(crd)):
        faces = Poly3DCollection(edges(crd[i]), linewidths=1, edgecolors='k', alpha=0.3)
        viridis = cm.get_cmap('viridis')
        color = viridis(np.linspace(0,1,data_number))
        faces.set_facecolor(color[i])
        ax.add_collection3d(faces)
    img = ax.scatter(crd[0:,0], crd[0:,1],crd[0:,2], c=concentration, s=0)
    ax.set_xlim(-2,2) #background range
    ax.set_ylim(-2,2)
    ax.set_zlim(-2,2)
    ax.set_ylabel(r'y')  # background label
    ax.set_xlabel(r'x')  
    ax.set_zlabel(r'z')
    faces.set_clim([min(concentration),max(concentration)])
    fig.colorbar(img)
    plt.show()