Question

How do I write a script for this in python in REPL or atom, NOT python shell

Consider the following simple “community” in Python . . .

triangle = [
["top", [0, 1]], ["bottom-left", [0, 0]], ["bottom-right", [2, 0]],

]

This is the calling of function. >>> nearestneighbor([0, 0.6], triangle, myeuclidean) 'top'

The new point is (0, 0.6) and the distance function is Euclidean. Now let’s confirm this result . . .

• >>> myeuclidean([0, 0.6], [0, 1])

• 0.4

• >>> myeuclidean([0, 0.6], [0, 0])

• 0.6

• >>> myeuclidean([0, 0.6], [2, 0])

• 2.08806130178211

Answer 1

Code Without Snippet:

# Implementation of myeuclidean function
def myeuclidean(point,point_):

   # Calculation Euclidean Distance
   distance = ((point[0]-point_[0])**2) + ((point[1]-point_[1])**2)
   distance = distance**(1/2)

   return distance

# Implementation of Nearest Neighbours
def nearestneighbor(point,triangle,myeuclidean):
   distances=[]

   # Calling myeuclidean for each point of triangle
   for i in range(0,len(triangle)):
       distances.append(myeuclidean(point,triangle[i][1]))

   # Finding out the minimum distance point index
   minimum_distance_position = distances.index(min(distances))

   return triangle[minimum_distance_position][0]

# Main Function
if __name__=="__main__":
   # Traingle Variable
   triangle = [ ["top", [0, 1]], ["bottom-left", [0, 0]], ["bottom-right", [2, 0]] ]

   # Function Call
   print(nearestneighbor([0, 0.6], triangle, myeuclidean))

Code With Snippet:

Input and Output Snippet:

Note:

• The complete code was saved in a file named check.py using Atom Editor.
• Please copy the complete code before running the script.
• Be aware of the indentation of the code.
• Please feel free to make changes, if required.
• Use print(distance) in myeuclidean function to see the computed distances for your reference, if required.
• Try around with other examples too.

Thank you!!!