diff --git a/curriculum/challenges/english/10-coding-interview-prep/rosetta-code/closest-pair-problem.md b/curriculum/challenges/english/10-coding-interview-prep/rosetta-code/closest-pair-problem.md index d8d9f7b246..9221d424b3 100644 --- a/curriculum/challenges/english/10-coding-interview-prep/rosetta-code/closest-pair-problem.md +++ b/curriculum/challenges/english/10-coding-interview-prep/rosetta-code/closest-pair-problem.md @@ -8,9 +8,9 @@ dashedName: closest-pair-problem # --description-- -Provide a function to find the closest two points among a set of given points in two dimensions, i.e. to solve the [Closest pair of points problem]( "wp: Closest pair of points problem") in the *planar* case. +Provide a function to find the closest two points among a set of given points in two dimensions. -The straightforward solution is a O(n2) algorithm (which we can call *brute-force algorithm*); the pseudo-code (using indexes) could be simply: +The straightforward solution is a $O(n^2)$ algorithm (which we can call *brute-force algorithm*); the pseudo-code (using indexes) could be simply: 
bruteForceClosestPair of P(1), P(2), ... P(N)
 if N < 2 then
@@ -30,7 +30,7 @@ The straightforward solution is a O(n2) algorithm (which we can call
 endif
-A better algorithm is based on the recursive divide and conquer approach, as explained also at [Wikipedia's Closest pair of points problem]( "wp: Closest pair of points problem#Planar_case"), which is `O(nlog(n))` a pseudo-code could be: +A better algorithm is based on the recursive divide and conquer approach, which is $O(n\log n)$ a pseudo-code could be: 
closestPair of (xP, yP)
   where xP is P(1) .. P(N) sorted by x coordinate, and
@@ -65,16 +65,38 @@ A better algorithm is based on the recursive divide and conquer approach, as exp
 endif
-For the input, expect the argument to be an array of objects (points) with `x` and `y` members set to numbers. For the output, return an object containing the key:value pairs for `distance` and `pair` (the pair of two closest points). +For the input, expect the argument to be an array of `Point` objects with `x` and `y` members set to numbers. Return an object containing the key:value pairs for `distance` and `pair` (the pair of two closest points). -**References and further readings:** +For example `getClosestPair` with input array `points`: + +```js +const points = [ + new Point(1, 2), + new Point(3, 3), + new Point(2, 2) +]; +``` + +Would return: + +```js +{ + distance: 1, + pair: [ + { + x: 1, + y: 2 + }, + { + x: 2, + y: 2 + } + ] +} +``` + +**Note:** Sort the `pair` array by their `x` values in incrementing order. - # --hints-- @@ -84,13 +106,13 @@ For the input, expect the argument to be an array of objects (points) with `x` a assert(typeof getClosestPair === 'function'); ``` -Distance should be the following. +`getClosestPair(points1).distance` should be `0.0894096443343775`. ```js assert.equal(getClosestPair(points1).distance, answer1.distance); ``` -Points should be the following. +`getClosestPair(points1).pair` should be `[ { x: 7.46489, y: 4.6268 }, { x: 7.46911, y: 4.71611 } ]`. ```js assert.deepEqual( @@ -99,13 +121,13 @@ assert.deepEqual( ); ``` -Distance should be the following. +`getClosestPair(points2).distance` should be `65.06919393998976`. ```js assert.equal(getClosestPair(points2).distance, answer2.distance); ``` -Points should be the following. +`getClosestPair(points2).pair` should be `[ { x: 37134, y: 1963 }, { x: 37181, y: 2008 } ]`. ```js assert.deepEqual( @@ -114,6 +136,21 @@ assert.deepEqual( ); ``` +`getClosestPair(points3).distance` should be `6754.625082119658`. + +```js +assert.equal(getClosestPair(points3).distance, answer3.distance); +``` + +`getClosestPair(points3).pair` should be `[ { x: 46817, y: 64975 }, { x: 48953, y: 58567 } ]`. + +```js +assert.deepEqual( + JSON.parse(JSON.stringify(getClosestPair(points3))).pair, + answer3.pair +); +``` + # --seed-- ## --after-user-code-- @@ -132,14 +169,6 @@ const points1 = [ new Point(1.45428, 0.087596) ]; -const points2 = [ - new Point(37100, 13118), - new Point(37134, 1963), - new Point(37181, 2008), - new Point(37276, 21611), - new Point(37307, 9320) -]; - const answer1 = { distance: 0.0894096443343775, pair: [ @@ -154,6 +183,14 @@ const answer1 = { ] }; +const points2 = [ + new Point(37100, 13118), + new Point(37134, 1963), + new Point(37181, 2008), + new Point(37276, 21611), + new Point(37307, 9320) +]; + const answer2 = { distance: 65.06919393998976, pair: [ @@ -168,8 +205,8 @@ const answer2 = { ] }; -const benchmarkPoints = [ - new Point(16909, 54699), +const points3 = [ + new Point(16910, 54699), new Point(14773, 61107), new Point(95547, 45344), new Point(95951, 17573), @@ -196,7 +233,7 @@ const benchmarkPoints = [ new Point(70721, 66707), new Point(31863, 9837), new Point(49358, 30795), - new Point(13041, 39745), + new Point(13041, 39744), new Point(59635, 26523), new Point(25859, 1292), new Point(1551, 53890), @@ -220,6 +257,20 @@ const benchmarkPoints = [ new Point(51090, 52158), new Point(48953, 58567) ]; + +const answer3 = { + distance: 6754.625082119658, + pair: [ + { + x: 46817, + y: 64975 + }, + { + x: 48953, + y: 58567 + } + ] +} ``` ## --seed-contents-- @@ -347,7 +398,7 @@ const closestPair = function _closestPair(Px, Py) { return { distance: minDelta, - pair: closestPair + pair: closestPair.sort((pointA, pointB) => pointA.x - pointB.x) }; };