''' mbinary ######################################################################### # File : min_distance_of_n_points.py # Author: mbinary # Mail: zhuheqin1@gmail.com # Blog: https://mbinary.xyz # Github: https://github.com/mbinary # Created Time: 2018-11-24 22:03 # Description: ######################################################################### ''' from random import randint from time import time from functools import total_ordering @total_ordering class point: def __init__(self, x, y): self.x = x self.y = y def __neg__(self): return pont(-self.x, -self.y) def __len__(self): return self.norm(2) def __lt__(self, p): return self.x < p.x or (self.x == p.x and self.y < p.y) def __eq__(self, p): return self.x == p.x and self.y == p.y def __hash__(self): return hash((self.x, self.y)) def __repr__(self): return 'point({},{})'.format(self.x, self.y) def __str__(self): return self.__repr__() def norm(self, n=2): if n <= 0: return max(abs(self.x), abs(self.y)) return (abs(self.x)**n+abs(self.y)**n)**(1/n) def distance(self, p): return ((self.x-p.x)**2+(self.y-p.y)**2)**0.5 def minDistance_n2(points): n = len(points) if n <= 1: return 0 p, q = points[:2] minD = points[0].distance(points[1]) for i in range(n-1): for j in range(i+1, n): d = points[i].distance(points[j]) if d < minD: minD = d p = points[i] q = points[j] return minD, p, q def findif(points, f, reverse=False): n = len(points) rg = range(n-1, -1, -1) if reverse else range(n) for i in rg: if not f(points[i]): return points[i+1:] if reverse else points[:i] return points.copy() # note that don't return exactly points, return a copy one def floatEql(f1, f2, epsilon=1e-6): return abs(f1-f2) < epsilon def minDistance_nlogn(n_points): def _min(pts): n = len(pts) if n == 2: return pts[0].distance(pts[1]), pts[0], pts[1] if n == 3: minD = pts[0].distance(pts[1]) p, q = pts[0], pts[1] d2 = pts[2].distance(pts[1]) if minD > d2: minD = d2 p, q = pts[1], pts[2] d2 = pts[0].distance(pts[2]) if minD > d2: return d2, pts[0], pts[2] else: return minD, p, q n2 = n//2 mid = (pts[n2].x + pts[n2-1].x)/2 s1 = pts[:n2] s2 = pts[n2:] minD, p, q = _min(s1) d2, p2, q2 = _min(s2) # print('\n\n',minD,p,q,s1) # print(d2,p2,q2,s2) if minD > d2: minD, p, q = d2, p2, q2 linePoints = findif(s1, lambda pt: floatEql(pt.x, mid), reverse=True) linePoints += findif(s2, lambda pt: floatEql(pt.x, mid)) n = len(linePoints) if n > 1: for i in range(1, n): dis = linePoints[i].y - linePoints[i-1].y if dis < minD: minD = dis p, q = linePoints[i-1], linePoints[i] leftPoints = findif(s1, lambda pt: pt.x >= mid-minD, reverse=True) rightPoints = findif(s2, lambda pt: pt.x <= mid+minD) for lp in leftPoints: y1, y2 = lp.y-minD, lp.y+minD for rp in rightPoints: if y1 < rp.y < y2: dis = lp.distance(rp) if dis < minD: minD = dis p, q = lp, rp return minD, p, q return _min(sorted(n_points)) def test(f=minDistance_n2): print('\ntest : ', f.__name__) begin = time() minD, p, q = f(points) print('time : {:.6f} s'.format(time()-begin)) print('result: {:.2f} {} {}\n'.format(minD, p, q)) def genData(n, unique=True): upper = 1000000 if unique: points = set() for i in range(n): points.add(point(randint(1, upper), randint(1, upper))) return list(points) else: return [point(randint(1, upper), randint(1, upper)) for i in range(n)] if __name__ == '__main__': n = 1000 points = genData(n, unique=True) print('min distance of {} points'.format(n)) # print(sorted(points)) test(minDistance_n2) test(minDistance_nlogn)