XericLibrary-OLD/Runtime/MicroLibrary/MacroList.cs

using System;
using System.Collections;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Linq;
using System.Threading;

using UnityEngine;

namespace XericLibrary.Runtime.MacroLibrary
{
	public static partial class MacroMath
	{
		#region 洗牌算法

		/// <summary>
		/// Fisher-Yates洗牌算法，时间复杂度为O(n*n),空间复杂度为O(n);
		/// 缺点是元素0很大概率会在最后出现
		/// </summary>
		/// <param name="length">待选项目的索引长度</param>
		/// <param name="select">输出项目的索引长度</param>
		/// <returns></returns>
		public static List<int> FisherYatesShuffle(int length, int select)
		{
			if(select > length)
				throw new ArgumentOutOfRangeException("在进行洗牌时，要求输出的项目比拥有的项目更多，这是不合理的。");

			var random = new System.Random();

			List<int> arr = Enumerable.Range(0, length).ToList();
			List<int> res = new List<int>();

			for(int i = 0; i < select; ++i)
			{
				int k = random.Next(arr.Count);
				res.Add(arr[k]);
				arr.RemoveAt(k);
			}

			return res;
		}


		/// <summary>
		/// 重复的洗牌
		/// </summary>
		/// <param name="length"></param>
		/// <param name="select"></param>
		/// <param name="repet"></param>
		/// <returns></returns>
		public static List<int> FisherYatesShuffle(int length, int select, int repet)
		{
			if(select > length)
				throw new ArgumentOutOfRangeException("在进行洗牌时，要求输出的项目比拥有的项目更多，这是不合理的。");
#if UNITY_EDITOR
			if(repet > 100)
				Debug.LogError("洗牌的重复次数太高(> 100)，已限制数量");
#endif
			repet = Math.Clamp(repet, 1, 100);

			var random = new System.Random();

			List<int> arr = Enumerable.Range(0, length).ToList();
			List<int> res = new List<int>();

			for(int j = 0; j < repet; j++)
			{
				for(int i = 0; i < length; i++)
				{
					int k = random.Next(arr.Count);
					res.Add(arr[k]);
					arr.RemoveAt(k);
				}
				arr = res.ToList();
				res.Clear();
			}
			return arr;
		}


		/// <summary>
		/// 蓄水池抽样算法，可以在线程安全的情况下完成洗牌。
		/// </summary>
		/// <param name="arr"></param>
		/// <param name="select">需要抽取的样本 M</param>
		/// <param name="reservoir"></param>
		/// <param name="cancellationToken"></param>
		public static void ReservoirSampling(List<int> arr, int select, ConcurrentBag<int> reservoir, CancellationToken cancellationToken)
		{
			/**
			 * int M = 3; // 需要抽样的元素个数
			 * int totalElements = 10; // 输入数据的总元素个数
			 * var arr = new List<int>();
			 * 
			 * for (int i = 1; i <= totalElements; i++)
			 * {
			 *	arr.Add(i);
			 * }
			 * 
			 * ConcurrentBag<int> reservoir = new ConcurrentBag<int>();
			 * Random random = new Random();
			 * 
			 * var cancellationTokenSource = new CancellationTokenSource();
			 * var cancellationToken = cancellationTokenSource.Token;
			 * 
			 * ThreadPool.QueueUserWorkItem(state =>
			 * 	ReservoirSampling(arr, M, reservoir, random, cancellationToken);
			 * , null);
			 * 
			 * // 停止抽样
			 * cancellationTokenSource.Cancel();
			 */
			var random = new System.Random();

			for(int i = select; i < arr.Count; ++i)
			{
				if(cancellationToken.IsCancellationRequested)
					return;

				int k = random.Next(i + 1); // 生成一个随机数 k，范围是 [0, i]
				if(k < select)
				{
					// 如果 k 小于 M，将 arr[k] 添加到抽样结果中
					reservoir.Add(arr[k]);
				}
			}
		}

		#endregion

		#region 应用算法

		/// <summary>
		/// 获取列表中随机顺序的对象
		/// </summary>
		/// <typeparam name="T"></typeparam>
		/// <param name="list"></param>
		/// <param name="count">需要采样的数量</param>
		/// <returns></returns>
		public static IEnumerable<T> GetRandom<T>(this List<T> list, int count = -1)
		{
			var index = FisherYatesShuffle(list.Count, count <= 0 ? list.Count : count);
			for(int i = 0; i < index.Count; i++)
				yield return list[index[i]];
		}

		#endregion


	}
}