Infinity 。这为从起始节点无法访问节点的情况提供了参考。接下来,您将要从开始节点转到其邻居。这些邻居是一个边缘,此时你应该添加一个距离单位到你要跟踪的距离。最后,有助于实现广度优先搜索算法的重要数据结构是队列。这是一个数组,您可以在其中添加元素到一端并从另一端删除元素。这也称为FIFO或先进先出数据结构。 bfs() ,它将邻接矩阵图(二维数组)和节点标签根作为参数。节点标签只是0到n - 1之间节点的整数值,其中n是图中节点的总数。您的函数将输出JavaScript对象键值对与节点及其与根的距离。如果无法到达节点,则其距离应为Infinity 。 [[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0]] ,起始节点为1应该返回{0: 1, 1: 0, 2: 1, 3: 2}'
testString: 'assert((function() { var graph = [[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0]]; var results = bfs(graph, 1); return isEquivalent(results, {0: 1, 1: 0, 2: 1, 3: 2})})(), "The input graph [[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0]] with a start node of 1 should return {0: 1, 1: 0, 2: 1, 3: 2}");'
- text: '输入图[[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 0]] ,起始节点为1应该返回{0: 1, 1: 0, 2: 1, 3: Infinity}'
testString: 'assert((function() { var graph = [[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 0]]; var results = bfs(graph, 1); return isEquivalent(results, {0: 1, 1: 0, 2: 1, 3: Infinity})})(), "The input graph [[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 0]] with a start node of 1 should return {0: 1, 1: 0, 2: 1, 3: Infinity}");'
- text: '输入图[[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0]] ,起始节点为0应该返回{0: 0, 1: 1, 2: 2, 3: 3}'
testString: 'assert((function() { var graph = [[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0]]; var results = bfs(graph, 0); return isEquivalent(results, {0: 0, 1: 1, 2: 2, 3: 3})})(), "The input graph [[0, 1, 0, 0], [1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0]] with a start node of 0 should return {0: 0, 1: 1, 2: 2, 3: 3}");'
- text: '起始节点为0的输入图[[0, 1], [1, 0]]应返回{0: 0, 1: 1}'
testString: 'assert((function() { var graph = [[0, 1], [1, 0]]; var results = bfs(graph, 0); return isEquivalent(results, {0: 0, 1: 1})})(), "The input graph [[0, 1], [1, 0]] with a start node of 0 should return {0: 0, 1: 1}");'
```