Credit: wikipedia |

**Problem Statement**: The closest pair of points problem or closest pair problem is a problem of computational geometry: given n points in metric space, find a pair of points with the smallest distance between them.

Basically you are given N points in a plane - and you ahve to find two closest points.

This is algorithm may be used to find the nearest location given your current geo location. This question was posted to me as -

**'Write the algorithm to find the nearest Star bucks coffee shop given your lat longs'**The first things that comes to the mind is a

**brute force**approach, which is O(n^2) and may not be ideal.

minDist = infinity for each p in P: for each q in P: if p ≠ q and dist(p, q) < minDist: minDist = dist(p, q) closestPair = (p, q) return closestPair

So, can we optimize it? Yes, lets get it in O(n log n).

This algorithm very similar to what we do in Merge Sort. The algorithm described here uses a divide and conquer approach to find out the closest pair of points in a plane. It takes an input array of points of the type described as input above

**PSEUDO CODE**

P set of points - SORTED by X-axis

procedure findclosest ( P, int n) { n is the number of elements in set P } Set: PLeft, PRight, Pleftmin, Prightmin, Pclosest if (n <= 3) return SHORTEST(P) else PLeft = { p(1), p(2), …. , p(n/2) } PRight = { p(n/2 + 1), ……. , p(n) } Pleftmin = findclosest (PLeft , n/2) Prightmin = findclosest (PRight , n/2) Pclosest = MERGEPLANES (Pleftmin, Pleft, Prightmin, Pright) return Pclosest endif endprocedure procedure MERGEPLANES (P1min, P1, P2min, P2min) D = MINIMUM among (P1min, P2min) There might be points in each around mid-x-axis that do not form the minimum on left/right but if joined across points on other side - might give min. We create a rectange to consider such points. xi - xj < D == Means any 2 points whoes x-axis coordinates are less than D distance apart. yi +D > yj > yi – D = means any 2 points with y-coordinates are less than D distance apart. Considering above and below 7-axis, means they lie in 2D range. for (every i in P1) for every j in P2 such that xi - xj < D AND (yi +D > yj > yi – D ) if DISTANCE (i, j) < D return (i, j) endfor endfor endprocedure

Inside loop will at the max have 6 elements falling in that range. O(constant)

Outer loop worst case goes n times. O(n)

Total complexity of MERGEPLANES - O(n) * O(constant) = O(n)

Recursive loop - O(log n)

Thus, Complexity - O(n log n)

Some places it is also said that it may be O(n)

It is because only points in both the planes which are not more than MinDistance distance apart will have to be considered in order to find the closest pair.

**Explanation**

- Say P is a set of points with x and y coordinates. - sort all points by by x-coordinate (Write a comparatr which does that) - Recursively, devide the list into halves. Pleft, Pright - pass halved lists recursively to the function. We follow bottoms up approach. We'll keep deviding till we reach base case of 2-3 points and we find nearest points amont them. - Then while keep coming out of recursion, we keep maitainining the closest pair amont Pleft and Pright. - leftClosest = recursive(Pleft) - rightClosest = recursive(Pright) - Sat we have ClosestPoint data structure: - that has Point1, Point2, distance - base case: if list.length < 3 -- return Shortest Distance ClosestPoint. - now we have closest point from left & right halves. - closest point will be either one of them, or points joining across the deviding line - ClosestPoint c = merge( leftClosest, Pleft, rightClosest, Pright ) - merge -- D = min distance from leftClosest, rightClosest -- find min reactangle around deviding line -- for(i: 0-Pleft.len) --- for (j: 0-Pright.len) ---- if(Mod(pi.x-pj.x) < D || Mod(pi.y-pj.y) < d) ----- d = Distance(...) ----- if(d < D) ------ maintain minDistance and closest pair

Some places it is also said that it may be O(n)

It is because only points in both the planes which are not more than MinDistance distance apart will have to be considered in order to find the closest pair.

**References**

- http:people.cis.ksu.edu/~subbu/Papers/Closest%20pair.pdf
- http:en.wikipedia.org/wiki/Closest_pair_of_points_problem

Hey Ashish - Good article. I like your site.

ReplyDeleteYou have a typo in your procedure MERGEPLANES (P1min, P1, P2min, P2min).

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