Visualize the NumPy Logo in 3D Voxel Plot

Introduction

This lab demonstrates how to use the Axes3D.voxels function in Matplotlib to create a 3D voxel plot of the NumPy logo.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Import libraries

First, we need to import the necessary libraries, which are Matplotlib and NumPy.

import matplotlib.pyplot as plt
import numpy as np

Define the explode function

Next, we define a function called explode that will be used to upscale the voxel image of the NumPy logo. This function takes in a NumPy array as its input and returns a new NumPy array that is twice the size of the input array.

def explode(data):
    size = np.array(data.shape)*2
    data_e = np.zeros(size - 1, dtype=data.dtype)
    data_e[::2, ::2, ::2] = data
    return data_e

Build the NumPy logo

Now we can begin to build the NumPy logo using a 3D NumPy array called n_voxels. We set certain elements in the array to True to represent the logo's shape. We also define two other NumPy arrays called facecolors and edgecolors that will be used to color the voxels.

n_voxels = np.zeros((4, 3, 4), dtype=bool)
n_voxels[0, 0, :] = True
n_voxels[-1, 0, :] = True
n_voxels[1, 0, 2] = True
n_voxels[2, 0, 1] = True

facecolors = np.where(n_voxels, '#FFD65DC0', '#7A88CCC0')
edgecolors = np.where(n_voxels, '#BFAB6E', '#7D84A6')

Upscale the voxel image

We now use the explode function defined earlier to upscale the voxel image, leaving gaps between each voxel.

filled = np.ones(n_voxels.shape)
filled_2 = explode(filled)
fcolors_2 = explode(facecolors)
ecolors_2 = explode(edgecolors)

Shrink the gaps

We shrink the gaps between each voxel by modifying the coordinates of each voxel using NumPy's indices function.

x, y, z = np.indices(np.array(filled_2.shape) + 1).astype(float) // 2
x[0::2, :, :] += 0.05
y[:, 0::2, :] += 0.05
z[:, :, 0::2] += 0.05
x[1::2, :, :] += 0.95
y[:, 1::2, :] += 0.95
z[:, :, 1::2] += 0.95

Create the voxel plot

Finally, we create the 3D voxel plot using the voxels function of the Axes3D class in Matplotlib.

ax = plt.figure().add_subplot(projection='3d')
ax.voxels(x, y, z, filled_2, facecolors=fcolors_2, edgecolors=ecolors_2)
ax.set_aspect('equal')

plt.show()

Summary

This lab demonstrated how to create a 3D voxel plot of the NumPy logo using Matplotlib. We used NumPy to build the logo, and the Axes3D.voxels function to create the plot. We also used a function called explode to upscale the voxel image of the logo.

3D Voxel Plot of the NumPy Logo