python - 如何在 3D 曲面图中绘制 x、y、z 的 numpy 数组？

Question

我有 reviewed both的 these threads ，但我仍在努力从 numpy 制作 3D 曲面图x, y, z 的数组坐标。

我的数组如下所示:

>>> points
array([[ 322697.1875    , 3663966.5       ,  -30000.        ],
       [ 325054.34375   , 3663966.5       ,  -30000.        ],
       [ 325054.34375   , 3665679.5       ,  -30000.        ],
       [ 322697.1875    , 3665679.5       ,  -30000.        ],
       [ 322697.1875    , 3663966.5       ,  -27703.12304688],
       [ 325054.34375   , 3663966.5       ,  -27703.15429688],
       [ 325054.34375   , 3665679.5       ,  -27703.70703125],
       [ 322697.1875    , 3665679.5       ,  -27703.67382812]])

ax.plot_surface接受 x, y, z点，所以我将上面的数组转换为下面的单独部分:

x = points[:, 0]
y = points[:, 1]
z = points[:, 2]

然后我将它放入网格中以传递给 ax.plot_surface() :
import numpy as np X, Y, Z = np.meshgrid(x, y, z)
然后尝试绘制:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure(figsize=(16,10))
ax = plt.axes(projection = '3d')
ax.plot_surface(X, Y, Z, alpha=0.5)
plt.show()

当我运行它时，我收到一个错误: rows, cols = Z.shape ValueError: too many values to unpack (expected 2) .

我现在不确定该怎么做，我不指望答案，但是朝着正确的方向插入会很棒。

我希望输出在外观上与此类似，但使用我的数据:


更新:如果我不包括 z在 meshgrid ，但只有 x和 y , 当我运行 ax.plot_surface(X, Y, z, alpha=0.5) 时得到这个输出:


这真的很接近，但我希望所有边都被填充。只有一个显示为填充。我添加了点坐标来显示边界。感觉跟 meshgrid有点关系我正在创造。这是 X, Y 的输出:

>>> X, Y = np.meshgrid(x, y)
(array([[322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ],
       [322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ],
       [322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ],
       [322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ],
       [322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ],
       [322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ],
       [322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ],
       [322697.1875 , 325054.34375, 325054.34375, 322697.1875 ,
        322697.1875 , 325054.34375, 325054.34375, 322697.1875 ]]), array([[3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5,
        3663966.5, 3663966.5],
       [3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5,
        3663966.5, 3663966.5],
       [3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5,
        3665679.5, 3665679.5],
       [3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5,
        3665679.5, 3665679.5],
       [3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5,
        3663966.5, 3663966.5],
       [3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5, 3663966.5,
        3663966.5, 3663966.5],
       [3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5,
        3665679.5, 3665679.5],
       [3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5, 3665679.5,
        3665679.5, 3665679.5]]))

如果我只取 x, y 唯一值，则会抛出错误:

x = np.unique(x)
y = np.unique(y)

>>> x
array([322697.1875 , 325054.34375])
>>> y
array([3663966.5, 3665679.5])

X, Y = np.meshgrid(x, y)
>>> X, Y
(array([[322697.1875 , 325054.34375],
       [322697.1875 , 325054.34375]]), array([[3663966.5, 3663966.5],
       [3665679.5, 3665679.5]]))

>>> ax.plot_surface(X, Y, z, alpha=0.5)
Traceback (most recent call last):
  File "<pyshell#61>", line 1, in <module>
    ax.plot_surface(X, Y, z, alpha=0.5)
  File "/Users/NaN/anaconda/envs/py36/lib/python3.6/site-packages/mpl_toolkits/mplot3d/axes3d.py", line 1586, in plot_surface
    X, Y, Z = np.broadcast_arrays(X, Y, Z)
  File "/Users/NaN/anaconda/envs/py36/lib/python3.6/site-packages/numpy/lib/stride_tricks.py", line 259, in broadcast_arrays
    shape = _broadcast_shape(*args)
  File "/Users/NaN/anaconda/envs/py36/lib/python3.6/site-packages/numpy/lib/stride_tricks.py", line 193, in _broadcast_shape
    b = np.broadcast(*args[:32])
ValueError: shape mismatch: objects cannot be broadcast to a single shape

Answer 1

数组 x, y, z 需要在二维中进行参数化。这样做的一种方法是使用球面坐标，例如在 Plot surfaces on a cube .

剩下的任务是从输入数据中提取唯一坐标。我在这里假设每个维度只有 2 个不同的值。

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

def get_cube():   
    phi = np.arange(1,10,2)*np.pi/4
    Phi, Theta = np.meshgrid(phi, phi)

    x = np.cos(Phi)*np.sin(Theta)
    y = np.sin(Phi)*np.sin(Theta)
    z = np.cos(Theta)/np.sqrt(2)
    return x,y,z


points = np.array([[ 322697.1875    , 3663966.5       ,  -30000. ],
                   [ 325054.34375   , 3663966.5       ,  -30000. ],
                   [ 325054.34375   , 3665679.5       ,  -30000. ],
                   [ 322697.1875    , 3665679.5       ,  -30000. ],
                   [ 322697.1875    , 3663966.5       ,  -27703.12],
                   [ 325054.34375   , 3663966.5       ,  -27703.12],
                   [ 325054.34375   , 3665679.5       ,  -27703.12],
                   [ 322697.1875    , 3665679.5       ,  -27703.12]])

ux = np.unique(points[:,0])
uy = np.unique(points[:,1])
uz = np.unique(points[:,2])

x,y,z = get_cube()
offset = lambda X, o: o[0] + (X+.5)*np.diff(o)[0]


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

ax.plot_surface(offset(x, ux), offset(y, uy), offset(z, uz))

plt.show()