How can the Euclidean distance be calculated with NumPy?

Question

I have two points in 3D:

(xa, ya, za)
(xb, yb, zb)

And I want to calculate the distance:

dist = sqrt((xa-xb)^2 + (ya-yb)^2 + (         


        

Answer 1

You can just subtract the vectors and then innerproduct.

Following your example,

a = numpy.array((xa, ya, za))
b = numpy.array((xb, yb, zb))

tmp = a - b
sum_squared = numpy.dot(tmp.T, tmp)
result = numpy.sqrt(sum_squared)

Answer 2

With Python 3.8, it's very easy.

https://docs.python.org/3/library/math.html#math.dist

math.dist(p, q)

Return the Euclidean distance between two points p and q, each given as a sequence (or iterable) of coordinates. The two points must have the same dimension.

Roughly equivalent to:

sqrt(sum((px - qx) ** 2.0 for px, qx in zip(p, q)))

Answer 3

It can be done like the following. I don't know how fast it is, but it's not using NumPy.

from math import sqrt
a = (1, 2, 3) # Data point 1
b = (4, 5, 6) # Data point 2
print sqrt(sum( (a - b)**2 for a, b in zip(a, b)))

Answer 4

import numpy as np
from scipy.spatial import distance
input_arr = np.array([[0,3,0],[2,0,0],[0,1,3],[0,1,2],[-1,0,1],[1,1,1]]) 
test_case = np.array([0,0,0])
dst=[]
for i in range(0,6):
    temp = distance.euclidean(test_case,input_arr[i])
    dst.append(temp)
print(dst)

Answer 5

Find difference of two matrices first. Then, apply element wise multiplication with numpy's multiply command. After then, find summation of the element wise multiplied new matrix. Finally, find square root of the summation.

def findEuclideanDistance(a, b):
    euclidean_distance = a - b
    euclidean_distance = np.sum(np.multiply(euclidean_distance, euclidean_distance))
    euclidean_distance = np.sqrt(euclidean_distance)
    return euclidean_distance

Answer 6

Since Python 3.8

Since Python 3.8 the math module includes the function math.dist().
See here https://docs.python.org/3.8/library/math.html#math.dist.

math.dist(p1, p2)
Return the Euclidean distance between two points p1 and p2, each given as a sequence (or iterable) of coordinates.

import math
print( math.dist( (0,0),   (1,1)   )) # sqrt(2) -> 1.4142
print( math.dist( (0,0,0), (1,1,1) )) # sqrt(3) -> 1.7321