Sometimes, we want to calculate the Euclidean distance with Python NumPy.
In this article, we’ll look at how to calculate the Euclidean distance with Python NumPy.
How to calculate the Euclidean distance with Python NumPy?
To calculate the Euclidean distance with Python NumPy, we can use the numpy.linalg.norm method.
For instance, we write:
import numpy
a = numpy.array((1, 2, 3))
b = numpy.array((4, 5, 6))
dist = numpy.linalg.norm(a - b)
print(dist)
We create 3 NumPy arrays a and b.
Then we call numpy.linalg.norm with a - b to calculate the distance between points a and b.
Therefore, dist is 5.196152422706632.
Conclusion
To calculate the Euclidean distance with Python NumPy, we can use the numpy.linalg.norm method.
