如何绘制轴形状不同的 3D 数据？

Question

我有这样的数据：

[
    [1, 2, 3, 4, 5],  #x
    [6, 7, 8, 9, 0],  #y
    [[1, 2, 3], [0, 2, 3], [1, 7, 3], [1, 2, 9], [1, 1, 3]]  #z is 3 values for each one value in x and y
]

如何在 matplotlib 中 plot/visualize 这样的数据？

我尝试了以下但没有成功：

ax.scatter3D(data[0], data[1], data[2], c=data[2], cmap='Greens');
# and
ax.plot3D(data[0], data[1], data[2], 'gray')

它给我错误：

# first line ==> ValueError: shape mismatch: objects cannot be broadcast to a single shape
# second line ==> ValueError: input operand has more dimensions than allowed by the axis remapping

Answer 1

您需要重塑数据以扩展 x 和 y 以匹配 z。

使用纯 python:

from itertools import product
a,b,c = zip(*(e for x,y,z in zip(*data) for e in product([x],[y],z)))

import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(projection='3d')

ax.scatter3D(a, b, c, c=c, cmap='Greens');

使用 numpy:

import numpy as np
x, y = np.repeat(np.array(data[:2]), 3, axis=1)
z = data[2]

import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(projection='3d')
ax.scatter3D(x, y, z, c=z, cmap='Greens')

输出：

如何绘制轴形状不同的 3D 数据？

How to plot a 3D data whose axis are not the same shape?

python

matplotlib

multidimensional-array