528. Random Pick with Weight
Description
You are given a 0-indexed array of positive integers w
where w[i]
describes the weight of the ith
index.
You need to implement the function pickIndex()
, which randomly picks an index in the range [0, w.length - 1]
(inclusive) and returns it. The probability of picking an index i
is w[i] / sum(w)
.
- For example, if
w = [1, 3]
, the probability of picking index0
is1 / (1 + 3) = 0.25
(i.e.,25%
), and the probability of picking index1
is3 / (1 + 3) = 0.75
(i.e.,75%
).
Example 1:
Input ["Solution","pickIndex"] [[[1]],[]] Output [null,0] Explanation Solution solution = new Solution([1]); solution.pickIndex(); // return 0. The only option is to return 0 since there is only one element in w.
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 is returning the second element (index = 1) that has a probability of 3/4. solution.pickIndex(); // return 1 solution.pickIndex(); // return 1 solution.pickIndex(); // return 1 solution.pickIndex(); // return 0. It is returning the first element (index = 0) that has a probability of 1/4. Since this is a randomization problem, multiple answers are allowed. All of 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 <= 104
1 <= w[i] <= 105
pickIndex
will be called at most104
times.
Solution
random-pick-with-weight.py
class Solution:
def __init__(self, w: List[int]):
self.A = list(accumulate(w))
self.n = self.A[-1]
def pickIndex(self) -> int:
x = random.randint(0, self.n - 1)
return bisect_right(self.A, x)
# Your Solution object will be instantiated and called as such:
# obj = Solution(w)
# param_1 = obj.pickIndex()