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Representing voxels with matplotlib
In 3D computer graphics, a voxel represents a value on a regular grid in three-dimensional space. We can say a voxel is a 3D equivalent of a pixel that is used in 2D. A pixel is a square inside of a 2D image with a position in a 2D grid and a single color value, whereas a voxel is a cube inside of a 3D model with a position inside a 3D grid and a single color value.
To represent voxels with matplotlib, we can take the following steps −
Set the figure size and adjust the padding between and around the subplots.
Create random choice data points between 0 and 1.
Create a new figure or activate an existing figure.
Get the current axes, creating one if necessary, with projection='3d'.
Plot a set of filled voxels, using voxels() method.
To display the figure, use show() method.
import numpy as np import matplotlib.pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Random data points between 0 and 1 data = np.random.choice([0, 1], size=(5, 7, 9), p=[0.65, 0.35]) # Create a new figure fig = plt.figure() # Axis with 3D projection ax = fig.gca(projection='3d') # Plot the voxels ax.voxels(data, edgecolor="k", facecolors='green') # Display the plot plt.show()
It will produce the following output −
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