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Creating a 3D plot in Matplotlib from a 3D numpy array
To create a 3D plot from a 3D numpy array, we can create a 3D array using numpy and extract the x, y, and z points.
- Create a new figure or activate an existing figure using figure() method.
- Add an '~.axes.Axes' to the figure as part of a subplot arrangement using add_subplot() method.
- Create a random data of size=(3, 3, 3).
- Extract x, y, and z data from the 3D array.
- Plot 3D scattered points on the created axis
- To display the figure, use show() method.
Example
import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111, projection='3d') data = np.random.random(size=(3, 3, 3)) z, x, y = data.nonzero() ax.scatter(x, y, z, c=z, alpha=1) plt.show()
Output
Updated on: 15-May-2021
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