什么是最有效的算法找到适合空白区域的最大面积的矩形?
假设屏幕看起来像这样('#'代表填充区域):
....................
..............######
##..................
.................###
.................###
#####...............
#####...............
#####...............
一个可能的解决方案是:
....................
..............######
##...++++++++++++...
.....++++++++++++###
.....++++++++++++###
#####++++++++++++...
#####++++++++++++...
#####++++++++++++...
通常我会喜欢找出解决方案。虽然这次我想避免浪费时间自己摸索,因为这对我正在研究的项目有实际用途。有一个众所周知的解决方案吗?
Shog9写道:
您的输入是一个数组(如其他响应所暗示的那样),还是一个以任意大小的定位矩形形式的遮挡列表(在处理窗口位置时窗口系统中可能就是这种情况)?
是的,我有一个跟踪屏幕上放置的一组窗口的结构。我还有一个网格,可以跟踪每个边缘之间的所有区域,无论它们是空的还是填充的,以及它们左边或顶边的像素位置。我认为有一些修改后的形式可以利用这个属性。你知道吗?
我是Dobb博士的文章的作者,并偶尔被问及实施。这是C中的一个简单的:
#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
typedef struct {
int one;
int two;
} Pair;
Pair best_ll = { 0, 0 };
Pair best_ur = { -1, -1 };
int best_area = 0;
int *c; /* Cache */
Pair *s; /* Stack */
int top = 0; /* Top of stack */
void push(int a, int b) {
s[top].one = a;
s[top].two = b;
++top;
}
void pop(int *a, int *b) {
--top;
*a = s[top].one;
*b = s[top].two;
}
int M, N; /* Dimension of input; M is length of a row. */
void update_cache() {
int m;
char b;
for (m = 0; m!=M; ++m) {
scanf(" %c", &b);
fprintf(stderr, " %c", b);
if (b=='0') {
c[m] = 0;
} else { ++c[m]; }
}
fprintf(stderr, "\n");
}
int main() {
int m, n;
scanf("%d %d", &M, &N);
fprintf(stderr, "Reading %dx%d array (1 row == %d elements)\n", M, N, M);
c = (int*)malloc((M+1)*sizeof(int));
s = (Pair*)malloc((M+1)*sizeof(Pair));
for (m = 0; m!=M+1; ++m) { c[m] = s[m].one = s[m].two = 0; }
/* Main algorithm: */
for (n = 0; n!=N; ++n) {
int open_width = 0;
update_cache();
for (m = 0; m!=M+1; ++m) {
if (c[m]>open_width) { /* Open new rectangle? */
push(m, open_width);
open_width = c[m];
} else /* "else" optional here */
if (c[m]<open_width) { /* Close rectangle(s)? */
int m0, w0, area;
do {
pop(&m0, &w0);
area = open_width*(m-m0);
if (area>best_area) {
best_area = area;
best_ll.one = m0; best_ll.two = n;
best_ur.one = m-1; best_ur.two = n-open_width+1;
}
open_width = w0;
} while (c[m]<open_width);
open_width = c[m];
if (open_width!=0) {
push(m0, w0);
}
}
}
}
fprintf(stderr, "The maximal rectangle has area %d.\n", best_area);
fprintf(stderr, "Location: [col=%d, row=%d] to [col=%d, row=%d]\n",
best_ll.one+1, best_ll.two+1, best_ur.one+1, best_ur.two+1);
return 0;
}
它从控制台获取输入。你可以,例如将此文件传递给它:
16 12
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0
0 0 0 1 1 0 0 1 0 0 0 1 1 0 1 0
0 0 0 1 1 0 1 1 1 0 1 1 1 0 1 0
0 0 0 0 1 1 * * * * * * 0 0 1 0
0 0 0 0 0 0 * * * * * * 0 0 1 0
0 0 0 0 0 0 1 1 0 1 1 1 1 1 1 0
0 0 1 0 0 0 0 1 0 0 1 1 1 0 1 0
0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0
打印输入后,输出:
The maximal rectangle has area 12.
Location: [col=7, row=6] to [col=12, row=5]
上面的实现当然没什么特别的,但是它与Dobb博士的文章中的解释非常接近,应该很容易转化为所需要的东西。
@lassevk
我从DDJ找到了引用的文章:The Maximal Rectangle Problem
这是一个包含一些代码和一些分析的页面。
您的特定问题在页面上稍微开始,在页面中搜索文本最大矩形问题。
http://www.seas.gwu.edu/~simhaweb/cs151/lectures/module6/module6.html
@lassevk
// 4. Outer double-for-loop to consider all possible positions
// for topleft corner.
for (int i=0; i < M; i++) {
for (int j=0; j < N; j++) {
// 2.1 With (i,j) as topleft, consider all possible bottom-right corners.
for (int a=i; a < M; a++) {
for (int b=j; b < N; b++) {
哈哈... O(m2 n2)..这可能是我想出的。
我看到他们继续开发优化......看起来不错,我会读一读。
我在Java中实现了Dobbs的解决方案。
什么都不保证。
package com.test;
import java.util.Stack;
public class Test {
public static void main(String[] args) {
boolean[][] test2 = new boolean[][] { new boolean[] { false, true, true, false },
new boolean[] { false, true, true, false }, new boolean[] { false, true, true, false },
new boolean[] { false, true, false, false } };
solution(test2);
}
private static class Point {
public Point(int x, int y) {
this.x = x;
this.y = y;
}
public int x;
public int y;
}
public static int[] updateCache(int[] cache, boolean[] matrixRow, int MaxX) {
for (int m = 0; m < MaxX; m++) {
if (!matrixRow[m]) {
cache[m] = 0;
} else {
cache[m]++;
}
}
return cache;
}
public static void solution(boolean[][] matrix) {
Point best_ll = new Point(0, 0);
Point best_ur = new Point(-1, -1);
int best_area = 0;
final int MaxX = matrix[0].length;
final int MaxY = matrix.length;
Stack<Point> stack = new Stack<Point>();
int[] cache = new int[MaxX + 1];
for (int m = 0; m != MaxX + 1; m++) {
cache[m] = 0;
}
for (int n = 0; n != MaxY; n++) {
int openWidth = 0;
cache = updateCache(cache, matrix[n], MaxX);
for (int m = 0; m != MaxX + 1; m++) {
if (cache[m] > openWidth) {
stack.push(new Point(m, openWidth));
openWidth = cache[m];
} else if (cache[m] < openWidth) {
int area;
Point p;
do {
p = stack.pop();
area = openWidth * (m - p.x);
if (area > best_area) {
best_area = area;
best_ll.x = p.x;
best_ll.y = n;
best_ur.x = m - 1;
best_ur.y = n - openWidth + 1;
}
openWidth = p.y;
} while (cache[m] < openWidth);
openWidth = cache[m];
if (openWidth != 0) {
stack.push(p);
}
}
}
}
System.out.printf("The maximal rectangle has area %d.\n", best_area);
System.out.printf("Location: [col=%d, row=%d] to [col=%d, row=%d]\n", best_ll.x + 1, best_ll.y + 1,
best_ur.x + 1, best_ur.y + 1);
}
}
经过这么多努力我写了这个算法......只看代码......
你了解这一点。这段代码说话!!
import java.util.Scanner;
import java.util.Stack;
/**
* Created by BK on 05-08-2017.
*/
public class LargestRectangleUnderHistogram {
public static void main(String... args) {
Scanner scanner = new Scanner(System.in);
int n = scanner.nextInt();
int[] input = new int[n];
for (int j = 0; j < n; j++) {
input[j] = scanner.nextInt();
}
/*
* This is the procedure used for solving :
*
* Travel from first element to last element of the array
*
* If stack is empty add current element to stack
*
* If stack is not empty check for the top element of stack if
* it is smaller than the current element push into stack
*
* If it is larger than the current element pop the stack until we get an
* element smaller than the current element or until stack becomes empty
*
* After popping each element check if the stack is empty or not..
*
* If stack is empty it means that this is the smallest element encountered till now
*
* So we can multiply i with this element to get a big rectangle which is contributed by
*
* this
*
* If stack is not empty then check for individual areas(Not just one bar individual area means largest rectangle by this) (i-top)*input[top]
*
*
* */
/*
* Initializing the maxarea as we check each area with maxarea
*/
int maxarea = -1;
int i = 0;
Stack<Integer> stack = new Stack<>();
for (i = 0; i < input.length; i++) {
/*
* Pushing the element if stack is empty
* */
if (stack.isEmpty()) {
stack.push(i);
} else {
/*
* If stack top element is less than current element push
* */
if (input[stack.peek()] < input[i]) {
stack.push(i);
} else {
/*
* Else pop until we encounter an element smaller than this in stack or stack becomes empty
*
* */
while (!stack.isEmpty() && input[stack.peek()] > input[i]) {
int top = stack.pop();
/*
* If stack is empty means this is the smallest element encountered so far
*
* So we can multiply this with i
* */
if (stack.isEmpty()) {
maxarea = maxarea < (input[top] * i) ? (input[top] * i) : maxarea;
}
/*
* If stack is not empty we find areas of each individual rectangle
* Remember we are in while loop
*/
else {
maxarea = maxarea < (input[top] * (i - top)) ? (input[top] * (i - top)) : maxarea;
}
}
/*
* Finally pushing the current element to stack
* */
stack.push(i);
}
}
}
/*
* This is for checking if stack is not empty after looping the last element of input
*
* This happens if input is like this 4 5 6 1 2 3 4 5
*
* Here 2 3 4 5 remains in stack as they are always increasing and we never got
*
* a chance to pop them from stack by above process
*
* */
while (!stack.isEmpty()) {
int top = stack.pop();
maxarea = maxarea < (i - top) * input[top] ? (i - top) * input[top] : maxarea;
}
System.out.println(maxarea);
}
}
我是关于LeetCode的Maximal Rectangle Solution的作者,这是这个答案的基础。
由于基于堆栈的解决方案已经在其他答案中讨论过,我想提出一个源自用户O(NM)
的最佳morrischen2008动态编程解决方案。
直觉
想象一个算法,对于每个点,我们通过执行以下操作来计算矩形:
我们知道最大矩形必须是以这种方式构造的矩形之一(最大矩形必须在其底部有一个点,下一个填充的正方形高于该点的高度)。
对于每个点,我们定义一些变量:
h
- 由该点定义的矩形的高度
l
- 由该点定义的矩形的左边界
r
- 由该点定义的矩形的右边界
这三个变量唯一地定义了该点的矩形。我们可以用h * (r - l)
计算这个矩形的面积。所有这些领域的全球最大值是我们的结果。
使用动态编程,我们可以使用前一行中每个点的h
,l
和r
来计算线性时间中下一行中每个点的h
,l
和r
。
算法
给定行matrix[i]
,我们通过定义三个数组 - h
,l
和r
来跟踪行中每个点的height
,left
和right
。
height[j]
将对应于matrix[i][j]
的高度,依此类推,与其他阵列相对应。
现在的问题是如何更新每个阵列。
height
h
定义为从我们的点开始的一行中连续未填充空格的数量。如果有一个新空间,我们递增,如果空间被填充则设置为零(我们使用'1'表示空白,'0'表示填充空格)。
new_height[j] = old_height[j] + 1 if row[j] == '1' else 0
left
:
考虑导致矩形左边界变化的原因。由于在当前版本的left
中已经考虑了当前版本的left
中所有填充空格的所有实例,因此我们当前行中遇到填充空间的唯一因素是影响我们的new_left[j] = max(old_left[j], cur_left)
。
结果我们可以定义:
cur_left
right
比我们遇到的最右边的空间更大。当我们将矩形“展开”到左侧时,我们知道它不能扩展到该点之外,否则它将进入填充空间。
left
:
在这里,我们可以在new_right[j] = min(old_right[j], cur_right)
中重用我们的推理并定义:
cur_right
def maximalRectangle(matrix):
if not matrix: return 0
m = len(matrix)
n = len(matrix[0])
left = [0] * n # initialize left as the leftmost boundary possible
right = [n] * n # initialize right as the rightmost boundary possible
height = [0] * n
maxarea = 0
for i in range(m):
cur_left, cur_right = 0, n
# update height
for j in range(n):
if matrix[i][j] == '1': height[j] += 1
else: height[j] = 0
# update left
for j in range(n):
if matrix[i][j] == '1': left[j] = max(left[j], cur_left)
else:
left[j] = 0
cur_left = j + 1
# update right
for j in range(n-1, -1, -1):
if matrix[i][j] == '1': right[j] = min(right[j], cur_right)
else:
right[j] = n
cur_right = j
# update the area
for j in range(n):
maxarea = max(maxarea, height[j] * (right[j] - left[j]))
return maxarea
是我们遇到的最充满空间的最左边的事件。
履行
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