What is the equivalent of Matlab's surf(x,y,z,c) in Matplotlib?

In MATLAB, surf(x,y,z,c) creates a 3D surface plot where the color is determined by the matrix c. In Matplotlib, the equivalent functionality is achieved using plot_surface() with appropriate parameters.

Basic Surface Plot

The simplest equivalent uses plot_surface() with a colormap ?

import matplotlib.pyplot as plt
import numpy as np

# Set figure properties
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create figure and 3D axis
fig = plt.figure()
ax = fig.add_subplot(projection='3d')

# Generate data for a sphere
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)

# Create surface plot with colormap
surface = ax.plot_surface(x, y, z, cmap='YlGnBu_r')

plt.show()

Surface Plot with Custom Color Data

To specify custom colors like MATLAB's c parameter, use the facecolors argument ?

import matplotlib.pyplot as plt
import numpy as np

# Create figure and 3D axis
fig = plt.figure(figsize=(8, 6))
ax = fig.add_subplot(projection='3d')

# Generate grid data
x = np.linspace(-2, 2, 20)
y = np.linspace(-2, 2, 20)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X**2 + Y**2))

# Custom color data (equivalent to MATLAB's 'c' parameter)
C = np.sqrt(X**2 + Y**2)

# Create surface with custom colors
surface = ax.plot_surface(X, Y, Z, facecolors=plt.cm.viridis(C/C.max()), alpha=0.8)

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
ax.set_title('Surface Plot with Custom Colors')

plt.show()

Comparison Table

Key Parameters

• cmap ? Colormap for automatic coloring based on Z values

• facecolors ? Custom color array for each face (equivalent to MATLAB's 'c')

• alpha ? Transparency level (0.0 to 1.0)

• shade ? Enable/disable shading effects

Conclusion

Matplotlib's plot_surface() provides equivalent functionality to MATLAB's surf(). Use cmap for automatic coloring or facecolors to specify custom colors like MATLAB's c parameter.