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 index `0` is `1 / (1 + 3) = 0.25` (i.e., `25%`), and the probability of picking index `1` is `3 / (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 most `104` times.