NP Euclidean Dystans Python
import numpy as np
a = np.array((1,1,1))
b = np.array((2,2,2))
dist = np.linalg.norm(a-b)
Lovely Lark
import numpy as np
a = np.array((1,1,1))
b = np.array((2,2,2))
dist = np.linalg.norm(a-b)
# 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)# 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 theoremdist = numpy.linalg.norm(a-b)