First numpy 3rd party solution for Similar Triangles by alterGNU - python coding challenges

Enable Javascript in your browser and then refresh this page, for a much enhanced experience.

First numpy solution in 3rd party category for Similar Triangles by alterGNU

import numpy as np
from typing import List, Tuple

Coords = List[Tuple[int, int]]

def angle_between(pt1, pt2, pt3):
    u = (pt2[0]-pt1[0],pt2[1]-pt1[1])
    v = (pt3[0]-pt2[0],pt3[1]-pt2[1])
    prod_scal= u[0] * v[0] + u[1] * v[1]
    norm_u= np.sqrt(u[0]**2 + u[1]**2)
    norm_v= np.sqrt(v[0]**2 + v[1]**2)
    return round(np.arccos( prod_scal / (norm_u * norm_v) ) * 180 / np.pi,10) 

def similar_triangles(coords_1: Coords, coords_2: Coords) -> bool:
    angle1 = [ angle_between(coords_1[0], coords_1[1], coords_1[2]),angle_between(coords_1[1], coords_1[2], coords_1[0]),angle_between(coords_1[2], coords_1[0], coords_1[1])]
    angle2 = [ angle_between(coords_2[0], coords_2[1], coords_2[2]),angle_between(coords_2[1], coords_2[2], coords_2[0]),angle_between(coords_2[2], coords_2[0], coords_2[1])]
    angle1.sort()
    angle2.sort()
    if angle1 != angle2:
        return False
    return True


if __name__ == '__main__':
    print("Example:")
    print(similar_triangles([(0, 0), (1, 2), (2, 0)], [(3, 0), (4, 2), (5, 0)]))

    # These "asserts" are used for self-checking and not for an auto-testing
    assert similar_triangles([(0, 0), (1, 2), (2, 0)], [(3, 0), (4, 2), (5, 0)]) is True, 'basic'
    assert similar_triangles([(0, 0), (1, 2), (2, 0)], [(3, 0), (4, 3), (5, 0)]) is False, 'different #1'
    assert similar_triangles([(0, 0), (1, 2), (2, 0)], [(2, 0), (4, 4), (6, 0)]) is True, 'scaling'
    assert similar_triangles([(0, 0), (0, 3), (2, 0)], [(3, 0), (5, 3), (5, 0)]) is True, 'reflection'
    assert similar_triangles([(1, 0), (1, 2), (2, 0)], [(3, 0), (5, 4), (5, 0)]) is True, 'scaling and reflection'
    assert similar_triangles([(1, 0), (1, 3), (2, 0)], [(3, 0), (5, 5), (5, 0)]) is False, 'different #2'
    print("Coding complete? Click 'Check' to earn cool rewards!")

June 4, 2021

Comments:

ainoneko on June 18, 2021, 3:15 a.m.
An interesting choice to use angles instead of the lengths of the sides being scaled equally. ^_^ The only thing I don't like is the long lines 15 and 16 where it could be easy to make a mistake with numbers when copy-pasting or re-typing similar expressions.

alterGNU on June 18, 2021, 9:15 a.m.
Hi thx for your comment :) , and you're right...similar_triangles function is not really "nice" ^^ Maybe this version is a little bit less mistakable : ``` def angle(pts): u = (pts[1][0]-pts[0][0],pts[1][1]-pts[0][1]) v = (pts[2][0]-pts[1][0],pts[2][1]-pts[1][1]) prodscal= u[0] * v[0] + u[1] * v[1] normu= np.sqrt(u[0]2 + u[1]2) normv= np.sqrt(v[0]2 + v[1]2) return round(np.arccos( prodscal / (normu * normv) ) * 180 / np.pi,10) def similartriangles(coords1: Coords, coords2: Coords) -> bool: angle1 = sorted([ angle(coords1[i:]+coords1[0:i])for i in range(len(coords1))]) angle2 = sorted([ angle(coords2[i:]+coords2[0:i])for i in range(len(coords_2))]) return angle1 == angle2 ``` (but now it's `angle(pts)` function that's ugly XD)

Ice Base

0 %

You ClassRoom Demo is Ready With the new tool CheckiO ClassRoom, you will be able to analyze your students' progress, have your own leaderboard, change missions order on the map, and so on.