如何增加 3D 条形图在 y 轴上的间隙（matplotlib 问题）？

Question

我有一个 4*7 3D 条形图，我想在其中增加 y 轴上 7 个条形的间距或间距。

下面是我的代码：

import pandas as pd
import matplotlib.pyplot as plt  
from mpl_toolkits.mplot3d import axes3d
import numpy as np


# Set plotting style
plt.style.use('seaborn-white')

dz=[]
z0 = np.array([ 1.,  3.,  11.,   8.,   7.,   6.,   6.,   6.,   5.,   4.,
                3.,   11.,   10.,  1.,  1.,  7., 1.,  3.,  11.,   8.,
                8.,   7.,   6.,   6., 1.,  1.,  7., 1.,])
dz.append(z0)

z1 =[ 5.,   5.,   8.,   4.,   2.,   0.,   0.,   0.,   0.,   0.,   0.,
      1.,   6.,  5.,   7.,   2., 1.,  3.,  11.,   8., 8.,   7.,   6.,   6.,
      1.,  1.,  7., 1.,]

dz.append(z1)

z2 =[ 15.,   5.,   8.,   2.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,
      3.,   5.,  2.,   7.,   2., 1.,  3.,  11.,   8., 8.,   7.,   6.,   6.,
      1.,  1.,  7., 1.,]

dz.append(z2)

_zpos = z0*0


xlabels = pd.Index(['X01', 'X02', 'X03', 'X04'], dtype='object')

ylabels = pd.Index(['Y01', 'Y02', 'Y03', 'Y04', 'Y05', 'Y06', 'Y07'], dtype='object')

x = np.arange(xlabels.shape[0])

y = np.arange(ylabels.shape[0])

x_M, y_M = np.meshgrid(x, y, copy=False)

fig = plt.figure(figsize=(7, 7))
ax = fig.add_subplot(111, projection='3d')

# Making the intervals in the axes match with their respective entries
ax.w_xaxis.set_ticks(x + 0.5/2.)
ax.w_yaxis.set_ticks(y + 0.5/2.)

# Renaming the ticks as they were before
ax.w_xaxis.set_ticklabels(xlabels)
ax.w_yaxis.set_ticklabels(ylabels)

# Labeling the 3 dimensions
ax.set_xlabel('X label')
ax.set_ylabel('Y label')
ax.set_zlabel('Z label')

# Choosing the range of values to be extended in the set colormap
values = np.linspace(0.2, 1., x_M.ravel().shape[0])

# Selecting an appropriate colormap

colors = ['#FFC04C', 'blue', '#3e9a19', 
          '#599be5','#bf666f','#a235bf','#848381','#fb90d6','#fb9125']

# Increase the number of segment to 3 by changing the X in 'range(X)' to 3.
for i in range(3):
    ax.bar3d(x_M.ravel(), y_M.ravel(), _zpos, dx=0.3, dy=0.3, dz=dz[i], 
              color=colors[i])
    _zpos += dz[i]
 

#plt.gca().invert_xaxis()
#plt.gca().invert_yaxis()
Segment1_proxy         = plt.Rectangle((0, 0), 1, 1, fc="#FFC04C")   
Segment2_proxy         = plt.Rectangle((0, 0), 1, 1, fc="blue")
Segment3_proxy         = plt.Rectangle((0, 0), 1, 1, fc="#3e9a19")

ax.legend([Segment1_proxy,
           Segment2_proxy,
           Segment3_proxy],['Segment1',
                            'Segment2',
                            'Segment3'
         ])
plt.show()

我试图寻找解决方案，但找不到与 3D 条形图相关的任何解决方案。我想这些二维条形图的解决方案不能在这里应用（或者我可能错了），因此我不确定从哪里开始（一天前刚开始学习 matplotlib）。有人可以帮忙吗？

以下帖子于 2021 年 3 月 31 日编辑

感谢 Yozhikoff 为上述问题提供解决方案，但希望改进可视化...

我增加了x轴之间的间隙，即通过将语法更改为来增加X01和X02之间的间隙

ax.set_box_aspect((10, 3, 1)) 

和

for i in range(3):
    ax.bar3d(x_M.ravel(), y_M.ravel(), _zpos, dx=0.03, dy=0.3, dz=dz[i], 
              color=colors[i], lightsource=ls)
    _zpos += dz[i]

然后生成下图：

您可能会看到 z 轴被挤压，但如果我将 ax.set_box_aspect 的值更改为 (30,3,5)，x 轴之间的差距似乎并没有增加太多，整体身材变小了。

有什么建议吗？

Answer 1

您可以尝试使用ax.set_box_aspect() 方法。

fig = plt.figure(figsize=(7, 7))
ax = fig.add_subplot(111, projection='3d')
ax.set_box_aspect((1, 3, 1))

与精心挑选的ax.bar3d() 的dx 和dy 参数结合使用效果特别好。

有几种方法可以进一步提高美感：

1. 使用plt.gca().view_init(elev=15, azim=20) 找到更好的角度
2. 制作LightSource，以正确的方式突出您的情节

   ls = mpl.colors.LightSource(azdeg=30, altdeg=10)
   ax.bar3d(..., lightsource=ls)
   

在你的情况下，我会做这样的事情：

import pandas as pd
import matplotlib.pyplot as plt  
from mpl_toolkits.mplot3d import axes3d
import numpy as np
import matplotlib as mpl


# Set plotting style
plt.style.use('seaborn-white')

dz=[]
z0 = np.array([ 1.,  3.,  11.,   8.,   7.,   6.,   6.,   6.,   5.,   4.,
                3.,   11.,   10.,  1.,  1.,  7., 1.,  3.,  11.,   8.,
                8.,   7.,   6.,   6., 1.,  1.,  7., 1.,])
dz.append(z0)

z1 =[ 5.,   5.,   8.,   4.,   2.,   0.,   0.,   0.,   0.,   0.,   0.,
      1.,   6.,  5.,   7.,   2., 1.,  3.,  11.,   8., 8.,   7.,   6.,   6.,
      1.,  1.,  7., 1.,]

dz.append(z1)

z2 =[ 15.,   5.,   8.,   2.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,
      3.,   5.,  2.,   7.,   2., 1.,  3.,  11.,   8., 8.,   7.,   6.,   6.,
      1.,  1.,  7., 1.,]

dz.append(z2)

_zpos = z0*0


xlabels = pd.Index(['X01', 'X02', 'X03', 'X04'], dtype='object')

ylabels = pd.Index(['Y01', 'Y02', 'Y03', 'Y04', 'Y05', 'Y06', 'Y07'], dtype='object')

x = np.arange(xlabels.shape[0])

y = np.arange(ylabels.shape[0])

x_M, y_M = np.meshgrid(x, y, copy=False)

fig = plt.figure(figsize=(7, 7))
ax = fig.add_subplot(111, projection='3d')
ax.set_box_aspect((1, 3.5, 1))
plt.gca().view_init(15, 20)

ls = mpl.colors.LightSource(azdeg=30, altdeg=10)

# Making the intervals in the axes match with their respective entries
ax.w_xaxis.set_ticks(x + 0.5/2.)
ax.w_yaxis.set_ticks(y + 0.5/2.)

# Renaming the ticks as they were before
ax.w_xaxis.set_ticklabels(xlabels)
ax.w_yaxis.set_ticklabels(ylabels)

# Labeling the 3 dimensions
ax.set_xlabel('X label')
ax.set_ylabel('Y label')
ax.set_zlabel('Z label')

# Choosing the range of values to be extended in the set colormap
values = np.linspace(0.2, 1., x_M.ravel().shape[0])

# Selecting an appropriate colormap

colors = ['#FFC04C', 'blue', '#3e9a19', 
          '#599be5','#bf666f','#a235bf','#848381','#fb90d6','#fb9125']

# Increase the number of segment to 3 by changing the X in 'range(X)' to 3.
for i in range(3):
    ax.bar3d(x_M.ravel(), y_M.ravel(), _zpos, dx=0.2, dy=0.1, dz=dz[i], 
              color=colors[i], lightsource=ls)
    _zpos += dz[i]
 

Segment1_proxy         = plt.Rectangle((0, 0), 1, 1, fc="#FFC04C")   
Segment2_proxy         = plt.Rectangle((0, 0), 1, 1, fc="blue")
Segment3_proxy         = plt.Rectangle((0, 0), 1, 1, fc="#3e9a19")

ax.legend([Segment1_proxy,
           Segment2_proxy,
           Segment3_proxy],['Segment1',
                            'Segment2',
                            'Segment3'
         ])



plt.show()

Example