Euclidean Distance numpy code example

Example 1: np euclidean distance python

import numpy as np
a = np.array((1,1,1))
b = np.array((2,2,2))
dist = np.linalg.norm(a-b)

Example 2: distance euc of two arrays python

# Use numpy.linalg.norm:
import numpy as np

a = np.array([1.0, 3.5, -6.3])
b = np.array([4.5, 1.6,  1.2])

dist = np.linalg.norm(a-b)

Example 3: euclidean distance python

# I hope to be of help and to have understood the request
from math import sqrt # import square root from the math module
# the x and y coordinates are the points on the Cartesian plane
pointA = (x, y) # first point
pointB = (x, y) # second point
distance = calc_distance(pointA, pointB) # here your beautiful result
def calc_distance(p1, p2): # simple function, I hope you are more comfortable
  return sqrt((p1[0]-p2[0])**2+(p1[1]-p2[1])**2) # Pythagorean theorem

Example 4: numpy euclidean distance

dist = numpy.linalg.norm(a-b)