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Given a list of non-overlapping axis-aligned rectangles rects, write a function pick which randomly and uniformily picks an integer point in the space covered by the rectangles.
Note:
An integer point is a point that has integer coordinates.
A point on the perimeter of a rectangle is included in the space covered by the rectangles.
ith rectangle = rects[i] = [x1,y1,x2,y2], where [x1, y1] are the integer coordinates of the bottom-left corner, and [x2, y2] are the integer coordinates of the top-right corner.
length and width of each rectangle does not exceed 2000.
1 <= rects.length <= 100
pick return a point as an array of integer coordinates [p_x, p_y]
The input is two lists: the subroutines called and their arguments. Solution's constructor has one argument, the array of rectangles rects. pick has no arguments. Arguments are always wrapped with a list, even if there aren't any.
这道题给了我们一些非重叠的矩形,让我们返回一个这些矩形中的一个随机的点。那么博主的第一直觉就是首先要在这些矩形中随机挑出来一个,然后在这个随机的矩形中再随机生成一个点,通过随机生成一个长和宽即可。博主最开始想到的方法是用rand随机生成一个 [0, n) 范围内的数字,n为输入矩形的个数,这样就得到了一个随机的矩形。但是这种方法貌似行不通,会跪在一个很长的输入测试数据。这使得博主比较困惑了,没有想出原因是为何,有哪位看官大神们知道的,麻烦留言告知博主哈!哈,已经知道了,参见评论区二楼留言~ 论坛上的解法有一种是用水塘抽样Reservoir Sampling的方法的,LeetCode之前有过几道需要用这种方法的题目 Random Pick Index,Shuffle an Array 和 Linked List Random Node。这里我们使用其来随机出一个矩形,做法是遍历所有的矩形,用变量sumArea来计算当前遍历过的所有矩形面积之和,然后变量area是当前遍历的矩形的面积(注意这里不是严格意义上的面积,而是该区域内整数坐标的点的个数,所以长宽相乘的时候都要加1),然后我们在当前所有矩形面积之和内随机生成一个值,如果这个值小于area,那么选择当前的矩阵为随机矩形。这里相当于一个大小为area的水塘,在这个值之内的话,就更换selected。这个方法是没啥问题,但是博主还是没想通为啥不能直接随机生成矩形的index。当我们拿到随机矩形后,之后就随机出宽和高返回即可,参见代码如下:
解法一:
class Solution {
public:
Solution(vector<vector<int>> rects) {
_rects = rects;
}
vector<int> pick() {
int sumArea = 0;
vector<int> selected;
for (auto rect : _rects) {
int area = (rect[2] - rect[0] + 1) * (rect[3] - rect[1] + 1);
sumArea += area;
if (rand() % sumArea < area) selected = rect;
}
int x = rand() % (selected[2] - selected[0] + 1) + selected[0];
int y = rand() % (selected[3] - selected[1] + 1) + selected[1];
return {x, y};
}
private:
vector<vector<int>> _rects;
};
Given a list of non-overlapping axis-aligned rectangles
rects
, write a functionpick
which randomly and uniformily picks an integer point in the space covered by the rectangles.Note:
i
th rectangle =rects[i]
=[x1,y1,x2,y2]
, where[x1, y1]
are the integer coordinates of the bottom-left corner, and[x2, y2]
are the integer coordinates of the top-right corner.2000
.1 <= rects.length <= 100
pick
return a point as an array of integer coordinates[p_x, p_y]
pick
is called at most10000
times.Example 1:
Example 2:
Explanation of Input Syntax:
The input is two lists: the subroutines called and their arguments.
Solution
's constructor has one argument, the array of rectanglesrects
.pick
has no arguments. Arguments are always wrapped with a list, even if there aren't any.这道题给了我们一些非重叠的矩形,让我们返回一个这些矩形中的一个随机的点。那么博主的第一直觉就是首先要在这些矩形中随机挑出来一个,然后在这个随机的矩形中再随机生成一个点,通过随机生成一个长和宽即可。博主最开始想到的方法是用rand随机生成一个 [0, n) 范围内的数字,n为输入矩形的个数,这样就得到了一个随机的矩形。但是这种方法貌似行不通,会跪在一个很长的输入测试数据。这使得博主比较困惑了,没有想出原因是为何,有哪位看官大神们知道的,麻烦留言告知博主哈!哈,已经知道了,参见评论区二楼留言~ 论坛上的解法有一种是用水塘抽样Reservoir Sampling的方法的,LeetCode之前有过几道需要用这种方法的题目 Random Pick Index,Shuffle an Array 和 Linked List Random Node。这里我们使用其来随机出一个矩形,做法是遍历所有的矩形,用变量sumArea来计算当前遍历过的所有矩形面积之和,然后变量area是当前遍历的矩形的面积(注意这里不是严格意义上的面积,而是该区域内整数坐标的点的个数,所以长宽相乘的时候都要加1),然后我们在当前所有矩形面积之和内随机生成一个值,如果这个值小于area,那么选择当前的矩阵为随机矩形。这里相当于一个大小为area的水塘,在这个值之内的话,就更换selected。这个方法是没啥问题,但是博主还是没想通为啥不能直接随机生成矩形的index。当我们拿到随机矩形后,之后就随机出宽和高返回即可,参见代码如下:
解法一:
这道题在论坛上的主流解法其实是这个,我们用TreeMap来建立当前遍历过的矩形面积之和跟该矩形位置之间的映射。然后当我们求出所有的矩形面积之和后,我们随机生成一个值,然后在TreeMap中找到第一个大于这个值的矩形,这里博主还是有疑问,为啥不能直接随机矩形的位置,而是非要跟面积扯上关系。之后的步骤就跟上面的没啥区别了,参见代码如下:
解法二:
类似题目:
Random Pick with Weight
Generate Random Point in a Circle
参考资料:
https://leetcode.com/problems/random-point-in-non-overlapping-rectangles/
https://leetcode.com/problems/random-point-in-non-overlapping-rectangles/discuss/155005/C%2B%2B-single-rand()-call
https://leetcode.com/problems/random-point-in-non-overlapping-rectangles/discuss/169185/Short-C%2B%2B-solution-with-upper_bound
https://leetcode.com/problems/random-point-in-non-overlapping-rectangles/discuss/170503/C%2B%2B-solution-using-reservoir-sampling-with-explanation-concise-and-easy-to-understand
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