Let's take an example to see how to get the same effect as MatLab's surf(x,y,z,c) in Matplotlib. steps −
Set the figure size and adjust the padding between and around the subplots.
Create a new figure or activate an existing figure.
Add an 'ax' to the figure as part of a subplot arrangement.
Create r, u, v, x, y and z data points using Numpy.
Create a surface plot.
To display the figure, use show() method.
Example
import matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(projection='3d') r = 0.05 u, v = np.mgrid[0:2 * np.pi:30j, 0:np.pi:20j] x = np.cos(u) * np.sin(v) y = np.sin(u) * np.sin(v) z = np.cos(v) ax.plot_surface(x, y, z, cmap=plt.cm.YlGnBu_r) plt.show()
Output
