chore(i18n,curriculum): processed translations - new ukrainian (#44447)
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---
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id: 5951a53863c8a34f02bf1bdc
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title: Задача про найближчу пару
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challengeType: 5
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forumTopicId: 302232
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dashedName: closest-pair-problem
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---
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# --description--
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Надайте функцію для пошуку двох найближчих точок серед поданого набору точок у двох вимірах.
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Найпростіше рішення це $O(n^2)$ алгоритм (який ми можемо назвати *brute-force algorithm*); цей псевдо-код (з використанням індексів) може бути простим:
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<pre><strong>bruteForceClosestPair</strong> of P(1), P(2), ... P(N)
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<strong>if</strong> N < 2 <strong>then</strong>
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<strong>return</strong> ∞
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<strong>else</strong>
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minDistance ← |P(1) - P(2)|
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minPoints ← { P(1), P(2) }
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<strong>foreach</strong> i ∈ [1, N-1]
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<strong>foreach</strong> j ∈ [i+1, N]
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<strong>if</strong> |P(i) - P(j)| < minDistance <strong>then</strong>
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minDistance ← |P(i) - P(j)|
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minPoints ← { P(i), P(j) }
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<strong>endif</strong>
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<strong>endfor</strong>
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<strong>endfor</strong>
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<strong>return</strong> minDistance, minPoints
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<strong>endif</strong>
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</pre>
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Кращий алгоритм базується на рекурсивному розподілі та підхопленні, який є псевдо-кодом $O(n\log n)$:
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<pre><strong>closestPair</strong> of (xP, yP)
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where xP is P(1) .. P(N) sorted by x coordinate, and
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yP is P(1) .. P(N) sorted by y coordinate (ascending order)
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<strong>if</strong> N ≤ 3 <strong>then</strong>
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<strong>return</strong> closest points of xP using brute-force algorithm
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<strong>else</strong>
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xL ← points of xP from 1 to ⌈N/2⌉
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xR ← points of xP from ⌈N/2⌉+1 to N
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xm ← xP(⌈N/2⌉)<sub>x</sub>
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yL ← { p ∈ yP : p<sub>x</sub> ≤ xm }
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yR ← { p ∈ yP : p<sub>x</sub> > xm }
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(dL, pairL) ← closestPair of (xL, yL)
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(dR, pairR) ← closestPair of (xR, yR)
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(dmin, pairMin) ← (dR, pairR)
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<strong>if</strong> dL < dR <strong>then</strong>
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(dmin, pairMin) ← (dL, pairL)
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<strong>endif</strong>
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yS ← { p ∈ yP : |xm - p<sub>x</sub>| < dmin }
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nS ← number of points in yS
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(closest, closestPair) ← (dmin, pairMin)
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<strong>for</strong> i <strong>from</strong> 1 <strong>to</strong> nS - 1
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k ← i + 1
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<strong>while</strong> k ≤ nS <strong>and</strong> yS(k)<sub>y</sub> - yS(i)<sub>y</sub> < dmin
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<strong>if</strong> |yS(k) - yS(i)| < closest <strong>then</strong>
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(closest, closestPair) ← (|yS(k) - yS(i)|, {yS(k), yS(i)})
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<strong>endif</strong>
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k ← k + 1
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<strong>endwhile</strong>
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<strong>endfor</strong>
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<strong>return</strong> closest, closestPair
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<strong>endif</strong>
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</pre>
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Для вхідних даних, слід очікувати, що аргумент буде масивом з `Point` об'єктами, і `x` та `y` заданими числами. Поверніть об'єкт, що містить ключові пари значень для `distance` та `pair` (пара двох найближчих точок).
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Наприклад, `getClosestPair` з вхідним масивом `points`:
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```js
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const points = [
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new Point(1, 2),
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new Point(3, 3),
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new Point(2, 2)
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];
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```
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Має повернути:
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```js
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{
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distance: 1,
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pair: [
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{
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x: 1,
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y: 2
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},
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{
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x: 2,
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y: 2
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}
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]
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}
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```
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**Note:** Сортуйте `pair` масиви за їхніми `x` значеннями у зростаючому порядку.
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# --hints--
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`getClosestPair` має бути функцією.
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```js
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assert(typeof getClosestPair === 'function');
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```
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`getClosestPair(points1).distance` має бути `0.0894096443343775`.
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```js
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assert.equal(getClosestPair(points1).distance, answer1.distance);
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```
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`getClosestPair(points1).pair` має бути `[ { x: 7.46489, y: 4.6268 }, { x: 7.46911, y: 4.71611 } ]`.
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```js
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assert.deepEqual(
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JSON.parse(JSON.stringify(getClosestPair(points1))).pair,
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answer1.pair
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);
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```
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`getClosestPair(points2).distance` має бути `65.06919393998976`.
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```js
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assert.equal(getClosestPair(points2).distance, answer2.distance);
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```
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`getClosestPair(points2).pair` має бути `[ { x: 37134, y: 1963 }, { x: 37181, y: 2008 } ]`.
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```js
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assert.deepEqual(
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JSON.parse(JSON.stringify(getClosestPair(points2))).pair,
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answer2.pair
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);
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```
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`getClosestPair(points3).distance` має бути `6754.625082119658`.
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```js
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assert.equal(getClosestPair(points3).distance, answer3.distance);
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```
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`getClosestPair(points3).pair` має бути `[ { x: 46817, y: 64975 }, { x: 48953, y: 58567 } ]`.
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```js
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assert.deepEqual(
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JSON.parse(JSON.stringify(getClosestPair(points3))).pair,
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answer3.pair
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);
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```
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# --seed--
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## --after-user-code--
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```js
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const points1 = [
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new Point(0.748501, 4.09624),
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new Point(3.00302, 5.26164),
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new Point(3.61878, 9.52232),
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new Point(7.46911, 4.71611),
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new Point(5.7819, 2.69367),
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new Point(2.34709, 8.74782),
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new Point(2.87169, 5.97774),
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new Point(6.33101, 0.463131),
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new Point(7.46489, 4.6268),
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new Point(1.45428, 0.087596)
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];
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const answer1 = {
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distance: 0.0894096443343775,
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pair: [
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{
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x: 7.46489,
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y: 4.6268
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},
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{
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x: 7.46911,
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y: 4.71611
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}
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]
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};
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const points2 = [
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new Point(37100, 13118),
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new Point(37134, 1963),
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new Point(37181, 2008),
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new Point(37276, 21611),
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new Point(37307, 9320)
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];
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const answer2 = {
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distance: 65.06919393998976,
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pair: [
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{
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x: 37134,
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y: 1963
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},
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{
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x: 37181,
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y: 2008
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}
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]
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};
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const points3 = [
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new Point(16910, 54699),
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new Point(14773, 61107),
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new Point(95547, 45344),
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new Point(95951, 17573),
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new Point(5824, 41072),
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new Point(8769, 52562),
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new Point(21182, 41881),
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new Point(53226, 45749),
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new Point(68180, 887),
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new Point(29322, 44017),
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new Point(46817, 64975),
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new Point(10501, 483),
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new Point(57094, 60703),
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new Point(23318, 35472),
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new Point(72452, 88070),
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new Point(67775, 28659),
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new Point(19450, 20518),
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new Point(17314, 26927),
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new Point(98088, 11164),
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new Point(25050, 56835),
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new Point(8364, 6892),
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new Point(37868, 18382),
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new Point(23723, 7701),
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new Point(55767, 11569),
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new Point(70721, 66707),
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new Point(31863, 9837),
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new Point(49358, 30795),
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new Point(13041, 39744),
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new Point(59635, 26523),
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new Point(25859, 1292),
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new Point(1551, 53890),
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new Point(70316, 94479),
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new Point(48549, 86338),
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new Point(46413, 92747),
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new Point(27186, 50426),
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new Point(27591, 22655),
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new Point(10905, 46153),
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new Point(40408, 84202),
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new Point(52821, 73520),
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new Point(84865, 77388),
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new Point(99819, 32527),
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new Point(34404, 75657),
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new Point(78457, 96615),
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new Point(42140, 5564),
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new Point(62175, 92342),
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new Point(54958, 67112),
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new Point(4092, 19709),
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new Point(99415, 60298),
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new Point(51090, 52158),
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new Point(48953, 58567)
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];
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const answer3 = {
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distance: 6754.625082119658,
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pair: [
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{
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x: 46817,
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y: 64975
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},
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{
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x: 48953,
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y: 58567
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}
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]
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}
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```
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## --seed-contents--
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```js
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const Point = function(x, y) {
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this.x = x;
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this.y = y;
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};
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Point.prototype.getX = function() {
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return this.x;
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};
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Point.prototype.getY = function() {
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return this.y;
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};
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function getClosestPair(pointsArr) {
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return true;
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}
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```
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# --solutions--
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```js
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const Point = function(x, y) {
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this.x = x;
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this.y = y;
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};
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Point.prototype.getX = function() {
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return this.x;
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};
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Point.prototype.getY = function() {
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return this.y;
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};
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const mergeSort = function mergeSort(points, comp) {
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if(points.length < 2) return points;
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var n = points.length,
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i = 0,
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j = 0,
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leftN = Math.floor(n / 2),
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rightN = leftN;
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var leftPart = mergeSort( points.slice(0, leftN), comp),
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rightPart = mergeSort( points.slice(rightN), comp );
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var sortedPart = [];
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while((i < leftPart.length) && (j < rightPart.length)) {
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if(comp(leftPart[i], rightPart[j]) < 0) {
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sortedPart.push(leftPart[i]);
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i += 1;
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}
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else {
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sortedPart.push(rightPart[j]);
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j += 1;
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}
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}
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while(i < leftPart.length) {
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sortedPart.push(leftPart[i]);
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i += 1;
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}
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while(j < rightPart.length) {
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sortedPart.push(rightPart[j]);
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j += 1;
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}
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return sortedPart;
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};
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const closestPair = function _closestPair(Px, Py) {
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if(Px.length < 2) return { distance: Infinity, pair: [ new Point(0, 0), new Point(0, 0) ] };
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if(Px.length < 3) {
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//find euclid distance
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var d = Math.sqrt( Math.pow(Math.abs(Px[1].x - Px[0].x), 2) + Math.pow(Math.abs(Px[1].y - Px[0].y), 2) );
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return {
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distance: d,
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pair: [ Px[0], Px[1] ]
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};
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}
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var n = Px.length,
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leftN = Math.floor(n / 2),
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rightN = leftN;
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var Xl = Px.slice(0, leftN),
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Xr = Px.slice(rightN),
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Xm = Xl[leftN - 1],
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Yl = [],
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Yr = [];
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//separate Py
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for(var i = 0; i < Py.length; i += 1) {
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if(Py[i].x <= Xm.x)
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Yl.push(Py[i]);
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else
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Yr.push(Py[i]);
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}
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var dLeft = _closestPair(Xl, Yl),
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dRight = _closestPair(Xr, Yr);
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var minDelta = dLeft.distance,
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closestPair = dLeft.pair;
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if(dLeft.distance > dRight.distance) {
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minDelta = dRight.distance;
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closestPair = dRight.pair;
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}
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//filter points around Xm within delta (minDelta)
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var closeY = [];
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for(i = 0; i < Py.length; i += 1) {
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if(Math.abs(Py[i].x - Xm.x) < minDelta) closeY.push(Py[i]);
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}
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//find min within delta. 8 steps max
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for(i = 0; i < closeY.length; i += 1) {
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for(var j = i + 1; j < Math.min( (i + 8), closeY.length ); j += 1) {
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var d = Math.sqrt( Math.pow(Math.abs(closeY[j].x - closeY[i].x), 2) + Math.pow(Math.abs(closeY[j].y - closeY[i].y), 2) );
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if(d < minDelta) {
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minDelta = d;
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closestPair = [ closeY[i], closeY[j] ]
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}
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}
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}
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return {
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distance: minDelta,
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pair: closestPair.sort((pointA, pointB) => pointA.x - pointB.x)
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};
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};
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function getClosestPair(points) {
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const sortX = function(a, b) { return (a.x < b.x) ? -1 : ((a.x > b.x) ? 1 : 0); }
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const sortY = function(a, b) { return (a.y < b.y) ? -1 : ((a.y > b.y) ? 1 : 0); }
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const Px = mergeSort(points, sortX);
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const Py = mergeSort(points, sortY);
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return closestPair(Px, Py);
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}
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```
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Reference in New Issue
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