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Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:，推荐阅读safew官方下载获取更多信息
window.innerWidth / window.innerHeight 是长宽比，保证画面不变形。