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python - matplotlib 曲面图隐藏了应该在前面的散点

转载 作者:行者123 更新时间:2023-11-28 18:10:03 25 4
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关于 matplotlib 3d 曲面的另一个问题...我有代码将散点添加到 matplotlib 曲面图。

from above我遇到的问题是,无论从哪个角度观察,点总是出现在表面后面。 from below

如果我使用 3 条短线来标记同一点来拼凑一个(公认的丑陋的)版本,它是可见的。 enter image description here

我关闭了depthshade功能,所以不是这个。任何人都可以解释发生了什么以及我如何纠正它吗?这是代码的简化版本:

import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

df = pd.DataFrame({10: {10: 1,15: 1,20: 1,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
15: {10: 4,15: 1,20: 1,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
20: {10: 6,15: 3,20: 1,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
25: {10: 7,15: 5,20: 3,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
30: {10: 9,15: 6,20: 4,25: 3,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
35: {10: 10,15: 7,20: 5,25: 4,30: 2,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
40: {10: 11,15: 8,20: 6,25: 4,30: 3,35: 2,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
45: {10: 12,15: 9,20: 7,25: 5,30: 4,35: 3,40: 2,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
50: {10: 13,15: 9,20: 7,25: 6,30: 5,35: 4,40: 3,45: 2,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
55: {10: 14,15: 10,20: 8,25: 7,30: 5,35: 4,40: 3,45: 3,50: 2,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
60: {10: 15,15: 11,20: 9,25: 7,30: 6,35: 5,40: 4,45: 3,50: 3,55: 2,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
65: {10: 16,15: 12,20: 9,25: 8,30: 6,35: 5,40: 5,45: 4,50: 3,55: 2,60: 2,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
70: {10: 17,15: 12,20: 10,25: 8,30: 7,35: 6,40: 5,45: 4,50: 4,55: 3,60: 2,65: 2,70: 1,75: 1,80: 1,85: 1,90: 1},
75: {10: 18,15: 13,20: 10,25: 9,30: 7,35: 6,40: 5,45: 5,50: 4,55: 3,60: 3,65: 2,70: 2,75: 1,80: 1,85: 1,90: 1},
80: {10: 19,15: 14,20: 11,25: 9,30: 8,35: 7,40: 6,45: 5,50: 4,55: 4,60: 3,65: 3,70: 2,75: 2,80: 1,85: 1,90: 1},
85: {10: 21,15: 14,20: 11,25: 10,30: 8,35: 7,40: 6,45: 6,50: 5,55: 4,60: 4,65: 3,70: 3,75: 2,80: 2,85: 1,90: 1},
90: {10: 23,15: 15,20: 12,25: 10,30: 9,35: 8,40: 7,45: 6,50: 5,55: 5,60: 4,65: 3,70: 3,75: 3,80: 2,85: 2,90: 1}})




xv, yv = np.meshgrid(df.index, df.columns)
ma = np.nanmax(df.values)
norm = matplotlib.colors.Normalize(vmin = 0, vmax = ma, clip = True)

fig = plt.figure(1)
ax = Axes3D(fig)
surf = ax.plot_surface(yv,xv,df, cmap='viridis_r', linewidth=0.3,
alpha = 0.8, edgecolor = 'k', norm=norm)
ax.scatter(25,35,4, c='k', depthshade=False, alpha = 1, s=100)

fig = plt.figure(2)
ax = Axes3D(fig)
surf = ax.plot_surface(yv,xv,df, cmap='viridis_r', linewidth=0.3,
alpha = 0.8, edgecolor = 'k', norm=norm)
line1_x = [25,25]
line1_y = [35,35]
line1_z = [3,5]

line2_x = [25,25]
line2_y = [33,37]
line2_z = [4,4]

line3_x = [23,27]
line3_y = [35,35]
line3_z = [4,4]

ax.plot(line1_x, line1_y, line1_z, alpha = 1, linewidth = 1, color='k')
ax.plot(line2_x, line2_y, line2_z, alpha = 1, linewidth = 1, color='k')
ax.plot(line3_x, line3_y, line3_z, alpha = 1, linewidth = 1, color='k')
plt.show()

最佳答案

一个有用的解决方法是使用选项 computed_zorder=False(添加到 Feb 2021 中,参见 doc ),并按所需顺序绘制不同的元素。唯一需要注意的是,它需要知道哪些点在表面下方,哪些点在表面上方。

Et Voilà !

import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

df = pd.DataFrame({10: {10: 1,15: 1,20: 1,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
15: {10: 4,15: 1,20: 1,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
20: {10: 6,15: 3,20: 1,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
25: {10: 7,15: 5,20: 3,25: 1,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
30: {10: 9,15: 6,20: 4,25: 3,30: 1,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
35: {10: 10,15: 7,20: 5,25: 4,30: 2,35: 1,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
40: {10: 11,15: 8,20: 6,25: 4,30: 3,35: 2,40: 1,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
45: {10: 12,15: 9,20: 7,25: 5,30: 4,35: 3,40: 2,45: 1,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
50: {10: 13,15: 9,20: 7,25: 6,30: 5,35: 4,40: 3,45: 2,50: 1,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
55: {10: 14,15: 10,20: 8,25: 7,30: 5,35: 4,40: 3,45: 3,50: 2,55: 1,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
60: {10: 15,15: 11,20: 9,25: 7,30: 6,35: 5,40: 4,45: 3,50: 3,55: 2,60: 1,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
65: {10: 16,15: 12,20: 9,25: 8,30: 6,35: 5,40: 5,45: 4,50: 3,55: 2,60: 2,65: 1,70: 1,75: 1,80: 1,85: 1,90: 1},
70: {10: 17,15: 12,20: 10,25: 8,30: 7,35: 6,40: 5,45: 4,50: 4,55: 3,60: 2,65: 2,70: 1,75: 1,80: 1,85: 1,90: 1},
75: {10: 18,15: 13,20: 10,25: 9,30: 7,35: 6,40: 5,45: 5,50: 4,55: 3,60: 3,65: 2,70: 2,75: 1,80: 1,85: 1,90: 1},
80: {10: 19,15: 14,20: 11,25: 9,30: 8,35: 7,40: 6,45: 5,50: 4,55: 4,60: 3,65: 3,70: 2,75: 2,80: 1,85: 1,90: 1},
85: {10: 21,15: 14,20: 11,25: 10,30: 8,35: 7,40: 6,45: 6,50: 5,55: 4,60: 4,65: 3,70: 3,75: 2,80: 2,85: 1,90: 1},
90: {10: 23,15: 15,20: 12,25: 10,30: 9,35: 8,40: 7,45: 6,50: 5,55: 5,60: 4,65: 3,70: 3,75: 3,80: 2,85: 2,90: 1}})




xv, yv = np.meshgrid(df.index, df.columns)
ma = np.nanmax(df.values)
norm = matplotlib.colors.Normalize(vmin = 0, vmax = ma, clip = True)

fig = plt.figure(1)
ax = Axes3D(fig, computed_zorder=False)

ax.scatter(10,70,4, c='k', depthshade=False, alpha = 1, s=100)
surf = ax.plot_surface(yv,xv,df, cmap='viridis_r', linewidth=0.3,
alpha = 0.8, edgecolor = 'k', norm=norm)
ax.scatter(25,35,4, c='k', depthshade=False, alpha = 1, s=100)

plt.show()

关于python - matplotlib 曲面图隐藏了应该在前面的散点,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/51241367/

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