python - 如何在 3D 曲面图中绘制一个由 x、y、z 组成的 numpy 数组？

问题描述

我已经查看了这两个线程，但仍在努力从一numpy组x, y, z坐标中制作 3D 曲面图。

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]

然后我将其放入网格中以传递到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)。

我现在不知道该去哪里，我不期待答案，但朝着正确的方向推进会很棒。

我希望输出在外观上与此相似，但使用我的数据：

更新：如果我不包含z在meshgrid, 但只有xandy中，我会在运行时得到这个输出ax.plot_surface(X, Y, z, alpha=0.5)：

这真的很接近，但我希望所有边都被填充。只有一个显示为已填充。我添加了点坐标以显示边界。我觉得这与meshgrid我正在创造的东西有关。这是输出X, Y：

>>> 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，我会抛出一个错误：

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

标签： pythonpython-3.xnumpymatplotlib

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()

python - 如何在 3D 曲面图中绘制一个由 x、y、z 组成的 numpy 数组？

问题描述

解决方案

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