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How to Generate a 3D Meshgrid Array in Numpy

Posted on April 14, 2021November 4, 2023 By Pythoneo

We will learn how to generate a 3D meshgrid array in Numpy.

my 3d meshgrid array

Generating Three Arrays

First, we will generate 3 arrays:

import numpy as np

xs = np.linspace(0., 1., 2)
ys = np.linspace(1., 2., 2)
zs = np.linspace(3., 4., 2)

print(f"X values: \n {xs}")
print(f"Y values: \n {ys}")
print(f"Z values: \n {zs}")

Obviously, they look like this:

Numpy meshgrid 3 arrays x y z

Generating a 3D Meshgrid Array

To generate a 3D meshgrid array, we can use the meshgrid() function and pass the created arrays as parameters.

import numpy as np

xs = np.linspace(0., 1., 2)
ys = np.linspace(1., 2., 2)
zs = np.linspace(3., 4., 2)

meshgrid_array = np.meshgrid(xs, ys, zs)
print(f"My 3d meshgrid array: \n {meshgrid_array}")

This will create a 3D array that contains all the possible combinations of the values in the three input arrays.

See also  How to rotate a matrix with Numpy

Here is what a 3D meshgrid array looks like:

my 3d meshgrid array

Other Ways to Generate a 3D Meshgrid Array

In addition to the meshgrid() function, there are other ways to generate a 3D meshgrid array in Numpy. Here are a few examples:

Use the product() function. The product() function takes a list of arrays and returns a new array that contains the product of all the elements in the list.

See also  How to calculate sum of columns and rows in Numpy?

Use the itertools.product() function. The itertools.product() function takes a list of iterables and returns a generator that produces all possible combinations of the elements in the iterables.

You can learn more about meshgrid arrays in Numpy by reading the Numpy documentation.

numpy Tags:array, dimension, grid, meshgrid

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