从三个1D阵列创建3D表面图 [英] Creating a 3D surface plot from three 1D arrays

问题描述

我有3个数组，如下所示，我正在尝试从中绘制3d表面图(线框或任何其他).我已经从中创建了一个散点图，但是不确定如何从3D表面图的角度来处理它.任何帮助将不胜感激.

I've got 3 arrays as shown below and I'm trying to plot a 3d surface plot (wireframe or any other) from it. I've created a scatter plot from it but not sure how to approach it from a 3D surface plot point of view. Any help would be greatly appreciated.

X = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8]

Y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]

Z =[21384, 29976, 15216, 4584, 10236, 7546, 6564, 2844, 4926, 7722, 4980, 2462, 12768, 9666, 2948, 6548, 10776, 8260, 8674, 5584, 5382, 10542, 12544, 5268, 25888, 31220, 9064, 7536, 6618, 1928, 9030, 5790, 6076, 8290, 8692, 4006, 14722, 11016, 2818, 9458, 3054, 5976, 1102, 1084, 9700, 8904, 12510, 11176, 10712, 6548, 2600, 5070, 6538, 4514, 1036, 292, 12572, 6534, 4478, 18500, 10452, 1912, 14254, 31050, 3880, 744, 990, 5534, 1670, 446, 2778, 8272, 14726, 27094, 872, 418, 884, 476, 2806, 1246, 1140, 922, 6202, 10848, 28828, 2360, 9660, 1412, 4296, 5272, 2854, 4150, 770, 5628, 4676, 3500, 31220, 10480, 5704, 5550, 1528, 3168, 2092, 2056, 1874, 7312, 938, 7428]

散点图代码

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

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

ax.scatter(x, y, z, c='y', marker='o')

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()

来自散点图的图像

我尝试使用下面的代码创建3D表面图，但是

I tried to use the code below to create a 3D surface plot but

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np

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

ax.plot_wireframe(x,y,z, rstride=2, cstride=2)

plt.show()

但不幸的是我得到一个错误.

but unfortunately I get an error.

推荐答案

有了常规网格，您可以使用numpy重塑数据，然后使用ax.plot_surface.在您的示例情况下，您想重塑为(9, 12)的形状:

As you have a regular grid, you can just use numpy to reshape your data, then use ax.plot_surface. In your example case, you want to reshape to a shape of (9, 12):

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

X = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8]

Y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]

Z = [21384, 29976, 15216, 4584, 10236, 7546, 6564, 2844, 4926, 7722, 4980, 2462, 12768, 9666, 2948, 6548, 10776, 8260, 8674, 5584, 5382, 10542, 12544, 5268, 25888, 31220, 9064, 7536, 6618, 1928, 9030, 5790, 6076, 8290, 8692, 4006, 14722, 11016, 2818, 9458, 3054, 5976, 1102, 1084, 9700, 8904, 12510, 11176, 10712, 6548, 2600, 5070, 6538, 4514, 1036, 292, 12572, 6534, 4478, 18500, 10452, 1912, 14254, 31050, 3880, 744, 990, 5534, 1670, 446, 2778, 8272, 14726, 27094, 872, 418, 884, 476, 2806, 1246, 1140, 922, 6202, 10848, 28828, 2360, 9660, 1412, 4296, 5272, 2854, 4150, 770, 5628, 4676, 3500, 31220, 10480, 5704, 5550, 1528, 3168, 2092, 2056, 1874, 7312, 938, 7428]

x = np.reshape(X, (9, 12))
y = np.reshape(Y, (9, 12))
z = np.reshape(Z, (9, 12))


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

ax.plot_surface(x, y, z)

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()

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