如何使用Matplotlib缩放体素尺寸? [英] How to scale the voxel-dimensions with Matplotlib?

问题描述

想用Matplotlib缩放体素尺寸.我该怎么办?

将 numpy 导入为 np导入matplotlib.pyplot作为plt从mpl_toolkits.mplot3d导入Axes3D无花果= plt.figure()ax = fig.gca(投影='3d')#制作网格test2 = np.zeros((6, 6, 6))#激活单个体素test2 [1，0，4] = Trueax.voxels(test2, edgecolor="k")ax.set_xlabel('0 - Dim')ax.set_ylabel('1 - Dim')ax.set_zlabel('2 - Dim')plt.show()

取而代之的是位置 (1,0,4) 上的体素.我想将其缩放为(0.5,0,2).

解决方案

您可以将自定义坐标传递给 voxels 函数:

Want to scale the voxel-dimensions with Matplotlib. How can I do this?

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

fig = plt.figure()
ax = fig.gca(projection='3d')
# Make grid
test2 = np.zeros((6, 6, 6))
# Activate single Voxel
test2[1, 0, 4] = True

ax.voxels(test2, edgecolor="k")
ax.set_xlabel('0 - Dim')
ax.set_ylabel('1 - Dim')
ax.set_zlabel('2 - Dim')

plt.show()

Instead the voxel on position (1,0,4). I want to scale it on (0.5,0,2).

解决方案

You can pass custom coordinates to the voxels function: API reference.

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

fig = plt.figure()
ax = fig.gca(projection='3d')
# Make grid
test2 = np.zeros((6, 6, 6))
# Activate single Voxel
test2[1, 0, 4] = True

# Custom coordinates for grid
x,y,z = np.indices((7,7,7))/2

# Pass the custom coordinates as extra arguments
ax.voxels(x, y, z, test2, edgecolor="k")
ax.set_xlabel('0 - Dim')
ax.set_ylabel('1 - Dim')
ax.set_zlabel('2 - Dim')

plt.show()

Which would yield:

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