CODEWITHSUNDEEP
pythonpython-3.xjupyter-notebook
Mayur Potdar
Mayur Potdar

Reputation: 451

How to get the Euclid distance from specified array in numpy?

I'm trying to generate specific array by calculating Euclid distance, I'm getting a different result

import numpy
def find_eucledian_distances(a_points, b_points):
  return numpy.sqrt(numpy.sum((a_points-b_points)**2))

a = np.array([[3.0, 4.0],
          [-3.0, -6.0],
          [-2.5, 6.3]])
b = np.array([[0.0, 0.0],
          [2.0, 6.0],
          [4.5, -8.3]])
d = find_eucledian_distances(a, b)

print(d)
print(d.shape)

These are two expected results expected result: [ 5. 13. 16.19135572] expected result: (3,)

but I'm getting 21.35790251873999 as a result. Can anyone explain?

Upvotes: 2

Views: 77

Answers (2)

Ashan Priyadarshana
Ashan Priyadarshana

Reputation: 3619

There is a numpy inbuilt way for this with the numpy's linear algebra library linalg:

return numpy.linalg.norm(a_points-b_points, axis=-1)

Upvotes: 1

one
one

Reputation: 2585

you should return bellows:

return  numpy.sqrt(numpy.sum((a_points-b_points)**2, axis=-1))

you should np.sum along the last axis. if you don't specific the axis=-1, the np.sum() will sum all of the elements.

Upvotes: 1

Related Questions