2018-12-10 06:06:47 +00:00
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package day06
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2018-12-06 07:23:45 +00:00
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import (
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"strconv"
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"strings"
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)
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type Point struct {
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X int
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Y int
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RectArea int
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}
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2018-12-06 16:48:51 +00:00
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// Turn input data into useable structured point objects.
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2018-12-06 07:23:45 +00:00
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func ParsePoints(data []string) []*Point {
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points := []*Point{}
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for _, pointInfo := range data {
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components := strings.Split(pointInfo, ", ")
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x, _ := strconv.Atoi(components[0])
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y, _ := strconv.Atoi(components[1])
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points = append(points, &Point{
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X: x,
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Y: y,
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})
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}
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return points
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}
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// Mutates the passed-in data in-place, computing the rectilinear
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// area for all points within the space bounded by (0,0) and the points themselves.
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// Sets the area of the 4 corner-most points (which definitionally must have
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// unbounded areas) to -1
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func ComputeRectilinearAreas(data []*Point) {
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// first we find the bounds
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2018-12-06 16:48:51 +00:00
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maxX, maxY := findUpperBounds(data)
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2018-12-06 07:23:45 +00:00
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// now for each integer point in our range, we compute the distance to each
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// point. We save the closest point and its distance, then:
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// 1. If there are two or more identically closest points, we do nothing.
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// 2. Otherwise, we increment RectArea for the closest point.
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for x := -maxX; x <= maxX*2; x++ {
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for y := -maxY; y <= maxY*2; y++ {
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2018-12-06 16:48:51 +00:00
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closest := findClosest(data, &Point{X: x, Y: y})
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2018-12-06 07:23:45 +00:00
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if closest == nil {
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continue
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}
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closest.RectArea++
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}
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}
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// now we find any unbounded points and set their areas to the sentinel
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// value
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2018-12-06 16:48:51 +00:00
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detectUnboundedPoints(data)
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}
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// ComputeNearnessRegion takes a list of points, returns the number of points
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// whose rectilinear distance to *all* the listed points sums to less than the
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// target value.
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func ComputeNearnessRegion(points []*Point, target int) int {
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maxX, maxY := findUpperBounds(points)
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// this is a 'brute-force' solution that just picks a suitably wide
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// area to search.
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area := 0
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for x := -target; x < maxX+target; x++ {
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for y := -target; y < maxY+target; y++ {
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if sumDistances(points, &Point{X: x, Y: y}) < target {
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area++
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}
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}
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}
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return area
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2018-12-06 07:23:45 +00:00
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}
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2018-12-06 16:48:51 +00:00
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// sumDistances calculates the distance from each point in `points` to `target`, and
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// returns the sum of all of those distances
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func sumDistances(points []*Point, target *Point) int {
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area := 0
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for _, point := range points {
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area += Distance(point, target)
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}
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return area
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}
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// Find the nearest point in `data` to `point`, using rectilinear distance.
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func findClosest(data []*Point, point *Point) *Point {
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2018-12-06 07:23:45 +00:00
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closest := data[0]
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2018-12-06 16:48:51 +00:00
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distance := Distance(data[0], point)
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2018-12-06 07:23:45 +00:00
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for i := 1; i < len(data); i++ {
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candidate := data[i]
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2018-12-06 16:48:51 +00:00
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newDistance := Distance(candidate, point)
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2018-12-06 07:23:45 +00:00
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if newDistance < distance {
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closest = candidate
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distance = newDistance
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} else if newDistance == distance {
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closest = nil
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}
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}
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return closest
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}
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2018-12-06 16:48:51 +00:00
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func detectUnboundedPoints(data []*Point) {
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2018-12-06 07:23:45 +00:00
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for _, candidate := range data {
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// look in each direction
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2018-12-06 16:48:51 +00:00
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up := findClosest(data, &Point{X: candidate.X, Y: candidate.Y + 1000000})
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down := findClosest(data, &Point{X: candidate.X, Y: candidate.Y - 1000000})
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left := findClosest(data, &Point{X: candidate.X + 1000000, Y: candidate.Y})
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right := findClosest(data, &Point{X: candidate.X - 1000000, Y: candidate.Y})
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2018-12-06 07:23:45 +00:00
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// if any of those points are closest to our point, we're unbounded
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if up == candidate || down == candidate ||
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left == candidate || right == candidate {
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candidate.RectArea = -1
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}
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}
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}
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2018-12-06 16:48:51 +00:00
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func findUpperBounds(points []*Point) (int, int) {
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maxX := 0
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maxY := 0
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for _, point := range points {
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if point.X > maxX {
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maxX = point.X
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}
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if point.Y > maxY {
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maxY = point.Y
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}
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}
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return maxX, maxY
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}
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func Distance(p1 *Point, p2 *Point) int {
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2018-12-06 07:23:45 +00:00
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return abs(p2.Y-p1.Y) + abs(p2.X-p1.X)
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}
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func abs(x int) int {
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if x < 0 {
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return -x
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}
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return x
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}
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