Matplotlib: 3D Contour Plot

There is a function ax.contour3D() that can be used to create a 3-D function. It takes input data in the form of two-dimensional regular grids, with its Z-data evaluated at each point.

Example

from mpl_toolkits import mplot3d
import numpy as np
import matplotlib.pyplot as plt

a= np.linspace(-0.1,10,100)
b=np.linspace(-0.1,10,100)
a,b= np.meshgrid(a,b) 
c=(a**2)/4+(b**2)/9

fig = plt.figure()

ax = fig.add_subplot(121, projection='3d')
ax.contour(a,b,c, 100)
ax.set_title('3D contour')

plt.show()

Here is the explanation of the some function used in the above example are:

  • meshgrid: This is the function of numpy which is basically used to create a rectangular grid out of two given one-dimension arrays representing Matrix Indexing.
  • plt.axes(): It is used to create the axis of the object.
  • ax.contour3D: It is used to create contour.
  • ax.set_xlabel: It is used to label the X-axis.
  • ax.set_title: It is used to give a title to the plot.

Output:

countour plot

Tue, 12/07/2021 - 07:38

Authored by

Devanshi, is working as a Data Scientist with iVagus. She has expertise in Python, NumPy, Pandas and other data science technologies.
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