根据值更改matplotlib中3D条形图中的条形颜色

问题描述

我在matplotlib中有一个3D条形图，其中总共有165条，现在非常混乱.

I have a 3D bar plot in matplotlib which consists of a total 165 bars and at the moment it is quite chaotic.

.

我想根据谨慎的z值(0、1、2)更改条形的颜色.

I would like to change the colour of the bars based on the discreet z-values: 0,1,2.

我知道可以使用.

还有一个关于如何根据值更改条形颜色的问题:定义Matplotlib 3D条形图的颜色

And there is also a question on how to change bar colour based on values:Defining colors of Matplotlib 3D bar plot

我不确定我是否能完全理解给出的答案，但是在这种情况下我无法使其正常工作.

I am not sure If i perfectly comprehend the given answer but I cannot make it work in this case.

代码是:

，color可以是一个数组，每个条带一种颜色. 

As seen from the documentation of bar3d, color can be an array, with one color per bar. 
这使得在一次调用bar3d的所有条上着色变得非常容易；我们只需要将data数组转换为可以使用颜色图完成的颜色数组
This makes it quite easy to colorize all bars in a single call to  bar3d; we just need to convert the data array to an array of colors which can be done using a colormap, 
colors = plt.cm.jet(data.flatten()/float(data.max()))
(请注意，颜色表的值介于0到1之间，因此我们需要将这些值归一化到该范围内.)
(Note, that a colormap takes values between 0 and 1, so we need to normalize the values into this range.)
完整示例:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

data = np.array([ [0, 0, 0, 2, 0, 0, 1, 2, 0, 0, 0],
         [0, 0, 2, 2, 0, 0, 0, 0, 2, 0, 0],
         [1, 0, 2, 2, 1, 2, 0, 0, 2, 0, 2],
         [1, 0, 2, 2, 0, 2, 0, 2, 2, 2, 2],
         [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2],
         [2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2],
         [0, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2],
         [1, 2, 0, 0, 2, 1, 2, 2, 0, 0, 2],
         [0, 0, 2, 1, 0, 0, 2, 0, 0, 0, 0],
         [2, 1, 2, 2, 0, 0, 0, 2, 0, 0, 2],
         [2, 2, 2, 0, 2, 0, 0, 0, 2, 2, 2],
         [2, 2, 0, 0, 2, 2, 2, 2, 2, 0, 0],
         [2, 2, 1, 2, 0, 0, 0, 2, 2, 2, 0],
         [2, 0, 0, 2, 0, 0, 2, 2, 2, 2, 2],
         [2, 0, 0, 2, 0, 2, 2, 2, 2, 2, 2]])


ypos, xpos  = np.indices(data.shape)

xpos = xpos.flatten()
ypos = ypos.flatten()
zpos = np.zeros(xpos.shape)

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

colors = plt.cm.jet(data.flatten()/float(data.max()))
ax.bar3d(xpos,ypos,zpos, .5,.5,data.flatten(), color=colors)

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.show()
                        
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