
- Matplotlib Tutorial
- Matplotlib - Home
- Matplotlib - Introduction
- Matplotlib - Environment Setup
- Matplotlib - Anaconda distribution
- Matplotlib - Jupyter Notebook
- Matplotlib - Pyplot API
- Matplotlib - Simple Plot
- Matplotlib - PyLab module
- Object-oriented Interface
- Matplotlib - Figure Class
- Matplotlib - Axes Class
- Matplotlib - Multiplots
- Matplotlib - Subplots() Function
- Matplotlib - Subplot2grid() Function
- Matplotlib - Grids
- Matplotlib - Formatting Axes
- Matplotlib - Setting Limits
- Setting Ticks and Tick Labels
- Matplotlib - Twin Axes
- Matplotlib - Bar Plot
- Matplotlib - Histogram
- Matplotlib - Pie Chart
- Matplotlib - Scatter Plot
- Matplotlib - Contour Plot
- Matplotlib - Quiver Plot
- Matplotlib - Box Plot
- Matplotlib - Violin Plot
- Three-dimensional Plotting
- Matplotlib - 3D Contour Plot
- Matplotlib - 3D Wireframe plot
- Matplotlib - 3D Surface plot
- Matplotlib - Working With Text
- Mathematical Expressions
- Matplotlib - Working with Images
- Matplotlib - Transforms
- Matplotlib Useful Resources
- Matplotlib - Quick Guide
- Matplotlib - Useful Resources
- Matplotlib - Discussion
Matplotlib - 3D Surface plot
Surface plot shows a functional relationship between a designated dependent variable (Y), and two independent variables (X and Z). The plot is a companion plot to the contour plot. A surface plot is like a wireframe plot, but each face of the wireframe is a filled polygon. This can aid perception of the topology of the surface being visualized. The plot_surface() function x,y and z as arguments.
from mpl_toolkits import mplot3d import numpy as np import matplotlib.pyplot as plt x = np.outer(np.linspace(-2, 2, 30), np.ones(30)) y = x.copy().T # transpose z = np.cos(x ** 2 + y ** 2) fig = plt.figure() ax = plt.axes(projection='3d') ax.plot_surface(x, y, z,cmap='viridis', edgecolor='none') ax.set_title('Surface plot') plt.show()
The above line of code will generate the following output −

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