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Plotting an imshow() image in 3d in Matplotlib
To plot an imshow() image in 3D in Matplotlib, we can take the following steps −
Create xx and yy data points using numpy.
Get the data (2D) using X, Y and Z.
Create a new figure or activate an existing figure using figure() method.
Add an 'ax1' to the figure as part of a subplot arrangement.
Display the data as an image, i.e., on a 2D regular raster with data.
Add an 'ax2' to the figure as part of a subplot arrangement.
Create and store a set of contour lines or filled regions.
To display the figure, use show() method.
Example
import matplotlib.pyplot as plt import numpy as np from matplotlib import cm plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True xx, yy = np.meshgrid(np.linspace(0, 1, 10), np.linspace(0, 1, 10)) X = xx Y = yy Z = 10 * np.ones(X.shape) data = np.cos(xx) * np.cos(xx) + np.sin(yy) * np.sin(yy) fig = plt.figure() ax1 = fig.add_subplot(121) ax1.imshow(data, cmap="plasma", interpolation='nearest', origin='lower', extent=[0, 1, 0, 1]) ax2 = fig.add_subplot(122, projection='3d') ax2.contourf(X, Y, data, 100, zdir='z', offset=0.5, cmap="plasma") plt.show()
Output
Updated on: 10-Aug-2021
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