search/random-pick-with-weight
Random Pick with Weight
描述
You are given an array of positive integers w
where w[i]
describes the weight of i
th index (0-indexed).
We need to call the function pickIndex()
which randomly returns an integer in the range [0, w.length - 1]
. pickIndex() should return the integer proportional to its weight in the w
array. For example, for w = [1, 3]
, the probability of picking the index 0
is 1 / (1 + 3) = 0.25
(i.e 25%) while the probability of picking the index 1
is 3 / (1 + 3) = 0.75
(i.e 75%).
More formally, the probability of picking index i
is w[i] / sum(w)
.
Example 1:
Input: ["Solution","pickIndex"]
[[[1]],[]]
Output:
[null,0]Explanation:
Solution solution = new Solution([1]);
solution.pickIndex(); // return 0. Since there is only one single element on the array
the only option is to return the first element.
Example 2:
Input: ["Solution","pickIndex","pickIndex","pickIndex","pickIndex","pickIndex"]
[[[1,3]],[],[],[],[],[]]
Output:
[null,1,1,1,1,0]Explanation:
Solution solution = new Solution([1, 3]);
solution.pickIndex(); // return 1. It's returning the second element (index = 1) that has probability of 3/4.
solution.pickIndex(); // return 1
solution.pickIndex(); // return 1
solution.pickIndex(); // return 1
solution.pickIndex(); // return 0. It's returning the first element (index = 0) that has probability of 1/4.Since this is a randomization problem, multiple answers are allowed so the following outputs can be considered correct :
[null,1,1,1,1,0]
[null,1,1,1,1,1]
[null,1,1,1,0,0]
[null,1,1,1,0,1]
[null,1,0,1,0,0]
......
and so on.
Constraints:
- 1 <= w.length <= 10000
- 1 <= w[i] <= 10^5
pickIndex()
will be called at most 10000 times.
分析
先构造一个累加的概率数组,然后用二分查找。
代码
// Random Pick with Weight
class Solution {
private double[] p; // probability of each element
// Time Complexity: O(n), Space Complexity: O(n)
public Solution(int[] w) {
double sum = 0;
for(int x : w) sum += x;
this.p = new double[w.length];
for(int i = 0; i < w.length; i++){
w[i] += (i == 0) ? 0 : w[i - 1];
p[i] = w[i] / sum;
}
}
// Time Complexity: O(logn), Space Complexity: O(1)
public int pickIndex() {
// upper bound
return Math.abs(Arrays.binarySearch(this.p, Math.random())) - 1;
}
}
// TODO