从matplotlib中的3D散点图中提取数据 [英] Extracting data from a 3D scatter plot in matplotlib

问题描述

我正在编写一个用于在 matplotlib 中制作 3D 散点图的界面，我想从 python 脚本访问数据.对于二维散点图，我知道过程将是:

I'm writing an interface for making 3D scatter plots in matplotlib, and I'd like to access the data from a python script. For a 2D scatter plot, I know the process would be:

import numpy as np
from matplotlib import pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(111)
h = ax.scatter(x,y,c=c,s=15,vmin=0,vmax=1,cmap='hot')
data = h.get_offsets()

有了上面的代码，我知道数据将是一个(N，2) numpy数组，其中填充了我的(x，y)数据.当我尝试对 3D 数据执行相同的操作时:

With the above code, I know that data would be a (N,2) numpy array populated with my (x,y) data. When I try to perform the same operation for 3D data:

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

fig = plt.figure()
ax = Axes3D(fig)
h = ax.scatter(x,y,z,c=c,s=15,cmap='hot',vmin=0,vmax=1)
data = h.get_offsets()

结果 data 变量仍然是 (N,2) numpy 数组，而不是 (N,3) numpy 数组. data 的内容不再匹配我的任何输入数据；我以为 data 用我的3D数据的2D投影填充，但是我真的很想访问用于生成散点图的3D数据.这可能吗?

The resulting data variable is still an (N,2) numpy array rather than a (N,3) numpy array. The contents of data no longer match any of my input data; I assume that data is populated with the 2D projections of my 3D data, but I would really like to access the 3D data used to generate the scatter plot. Is this possible?

推荐答案

确实，通过get_offsets得到的坐标就是投影坐标.原始坐标隐藏在 mpl_toolkits.mplot3d.art3d.Path3DCollection 中，由 scatter 在三维轴上返回.您将从 ._offsets3d 属性获取原始坐标.(这是一个私有"属性，但不幸的是检索此信息的唯一方法.)

Indeed, the coordinates obtained via get_offsets are the projected coordinates. The original coordinates are hidden inside the mpl_toolkits.mplot3d.art3d.Path3DCollection which is returned by the scatter in three dimensional axes. You would obtain the original coordinates from the ._offsets3d attribute. (This is a "private" attribute, but unfortunately the only way to retrieve this information.)

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

fig = plt.figure()
ax = Axes3D(fig)
x = [1,2,3,4]
y = [1,3,3,5]
z = [10,20,30,40]
c= [1,2,3,1]
scatter = ax.scatter(x,y,z,c=c,s=15,cmap='hot',vmin=0,vmax=1)
data = np.array(scatter._offsets3d).T
print(scatter)  # prints mpl_toolkits.mplot3d.art3d.Path3DCollection
print(data)

# prints
# 
# [[  1.   1.  10.]
#  [  2.   3.  20.]
#  [  3.   3.  30.]
#  [  4.   5.  40.]]

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