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说实话，这个我们普通人的思路就排不上用场了。但是数学家证明了一件事情，只要我们使用启发式函数来估计值，并且这些值能够一定小于当前点到终点的路径的长度，这样就一定能找到最优路径。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"这种能找到最优路径的启发式寻路，在计算机里面我们叫它做 “","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"A*","attrs":{}}],"attrs":{}},{"type":"text","text":"”。这里面的 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"A","attrs":{}}],"attrs":{}},{"type":"text","text":" 代表着一种不一定能找到最优路径的启发式寻路。所以 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"A*","attrs":{}}],"attrs":{}},{"type":"text","text":" 就是 A 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函数）","attrs":{}}]}],"attrs":{}},{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":3,"align":null,"origin":null},"content":[{"type":"text","text":"在我们通过这个类获取值的时候给我们数据里面的最小值","attrs":{}}]}],"attrs":{}},{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":4,"align":null,"origin":null},"content":[{"type":"text","text":"在我们插入数据的时候不需要排序，只是单纯的保存","attrs":{}}]}],"attrs":{}},{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":5,"align":null,"origin":null},"content":[{"type":"text","text":"每次去除数据的时候，可以把输出的数据在类的数据里面删除掉","attrs":{}}]}],"attrs":{}},{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":6,"align":null,"origin":null},"content":[{"type":"text","text":"这样我们就可以一直在里面获取数据，知道没有数据为止","attrs":{}}]}],"attrs":{}},{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":7,"align":null,"origin":null},"content":[{"type":"text","text":"最后加入一个可以获取当前数据的长度（这个在我们的寻路算法中需要用到）","attrs":{}}]}],"attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"这里我们用一个非常 “土鳖” 的数组来实现这个 Sorted 类，但是在计算机当中，我们还有很多其他方式可以实现这一种类。比如说 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"winner tree","attrs":{}}],"attrs":{}},{"type":"text","text":"，","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"堆 (heap)","attrs":{}}],"attrs":{}},{"type":"text","text":"，","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"排序二叉树","attrs":{}}],"attrs":{}},{"type":"text","text":" 等很多的不同思路来实现有序的数据结构。","attrs":{}}]}],"attrs":{}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"好废话少说，我们来看看怎么实现这个数据结构：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"codeblock","attrs":{"lang":"javascript"},"content":[{"type":"text","text":"/** 排序数据类 */\nclass Sorted {\n constructor(data, compare) {\n this.data = data.slice();\n this.compare = compare || ((a, b) => a - b);\n }\n take() {\n // 考虑到 null 也是可以参与比较的，所以这里返回 null 是不合适的\n if (!this.data.length) return;\n // 记录最小的值\n // 默认第一个位置为最小值\n let min = this.data[0];\n // 记录最小值的位置\n let minIndex = 0;\n\n // 开始比较数组里面的所有值，找到更小的值，就记录为 min\n // 同时记录最小值，和最小值的位置\n for (let i = 1; i < this.data.length; i++) {\n if (this.compare(this.data[i], min) < 0) {\n min = this.data[i];\n minIndex = i;\n }\n }\n\n // 现在我们要把最小值拿出去了，所以要在我们当前的数据中移除\n // 这里我们不考虑使用 splice，因为 splice 移除会涉及数组内的元素都要往前挪动\n // 这样 splice 就会有一个 O(N) 的时间复杂度\n // 这里我们用一个小技巧，把数组里面最后一位的值挪动到当前发现最小值的位置\n // 最后使用 pop 把最后一位数据移除\n this.data[minIndex] = this.data[this.data.length - 1];\n this.data.pop();\n // 最后把最小值输出\n return min;\n }\n give(value) {\n this.data.push(value);\n }\n get length() {\n return this.data.length;\n }\n}","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"有了这个 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"Sorted","attrs":{}}],"attrs":{}},{"type":"text","text":" 的数据结构之后，我们就可以用来解决我们的寻路问题，让我们可以找到最佳的路径了。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"加入这个最佳路径的逻辑，我们需要改到一下几个点：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"numberedlist","attrs":{"start":"1","normalizeStart":1},"content":[{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":1,"align":null,"origin":null},"content":[{"type":"text","text":"首先改写我们的存储数据的 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"queue","attrs":{}}],"attrs":{}},{"type":"text","text":"，使用我们 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"Sorted","attrs":{}}],"attrs":{}},{"type":"text","text":" 的排序数据结构","attrs":{}}]}],"attrs":{}},{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":2,"align":null,"origin":null},"content":[{"type":"text","text":"编写一个 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"distance()","attrs":{}}],"attrs":{}},{"type":"text","text":" 函数来运算任何一个格子与终点格子的直线距离","attrs":{}}]}],"attrs":{}},{"type":"listitem","content":[{"type":"paragraph","attrs":{"indent":0,"number":3,"align":null,"origin":null},"content":[{"type":"text","text":"把所有入队列和出队列的调用改为使用 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"Sorted","attrs":{}}],"attrs":{}},{"type":"text","text":" 类里面的 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"take","attrs":{}}],"attrs":{}},{"type":"text","text":" 取值 和 ","attrs":{}},{"type":"codeinline","content":[{"type":"text","text":"give","attrs":{}}],"attrs":{}},{"type":"text","text":" 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