|
| 1 | +""" |
| 2 | +Breadth-first-traversal is an algorithm for traversing a tree or |
| 3 | +graph data structure. Starting at the tree root (or some arbitrary node of a |
| 4 | +graph, sometimes referred to as a 'search key'[1]) and explores the neighbor |
| 5 | +nodes at that level first, before moving to the next level. |
| 6 | +""" |
| 7 | + |
| 8 | +from collections import deque |
| 9 | + |
| 10 | + |
| 11 | +def breadth_first_traversal(graph, source): |
| 12 | + """ Performs a breadth-first traversal on a graph |
| 13 | +
|
| 14 | + Args: |
| 15 | + graph (list of list of int): Adjacency matrix representation of graph |
| 16 | + source (int): Index of source vertex to begin search from |
| 17 | +
|
| 18 | + Returns: |
| 19 | + list of dicts describing each vertex in the searched graph |
| 20 | + -> [{distance: _, predecessor: _ }] |
| 21 | + """ |
| 22 | + vertex_info = [] |
| 23 | + for i in range(len(graph)): |
| 24 | + vertex_info.append({"distance": None, "predecessor": None}) |
| 25 | + vertex_info[source]["distance"] = 0 |
| 26 | + |
| 27 | + search_queue = deque() |
| 28 | + search_queue.append(source) |
| 29 | + |
| 30 | + while search_queue: |
| 31 | + u = search_queue.popleft() |
| 32 | + for v in graph[u]: |
| 33 | + if vertex_info[v]["distance"] is None: |
| 34 | + vertex_info[v]["distance"] = vertex_info[u]["distance"] + 1 |
| 35 | + vertex_info[v]["predecessor"] = u |
| 36 | + search_queue.append(v) |
| 37 | + return vertex_info |
| 38 | + |
| 39 | + |
| 40 | +def main(): |
| 41 | + graph_adj_list = [ |
| 42 | + [1], |
| 43 | + [0, 4, 5], |
| 44 | + [3, 4, 5], |
| 45 | + [2, 6], |
| 46 | + [1, 2], |
| 47 | + [1, 2, 6], |
| 48 | + [3, 5], |
| 49 | + [] |
| 50 | + ] |
| 51 | + vertex_info = breadth_first_traversal(graph_adj_list, 3) |
| 52 | + |
| 53 | + for i in range(len(graph_adj_list)): |
| 54 | + print("vertex %s : distance = %s, predecessor = %s" % |
| 55 | + (i, vertex_info[i]["distance"], vertex_info[i]["predecessor"])) |
| 56 | + |
| 57 | + assert(vertex_info[0] == { |
| 58 | + "distance": 4, |
| 59 | + "predecessor": 1 |
| 60 | + }) |
| 61 | + assert(vertex_info[1] == { |
| 62 | + "distance": 3, |
| 63 | + "predecessor": 4 |
| 64 | + }) |
| 65 | + assert(vertex_info[2] == { |
| 66 | + "distance": 1, |
| 67 | + "predecessor": 3 |
| 68 | + }) |
| 69 | + assert(vertex_info[3] == { |
| 70 | + "distance": 0, |
| 71 | + "predecessor": None |
| 72 | + }) |
| 73 | + assert(vertex_info[4] == { |
| 74 | + "distance": 2, |
| 75 | + "predecessor": 2 |
| 76 | + }) |
| 77 | + assert(vertex_info[5] == { |
| 78 | + "distance": 2, |
| 79 | + "predecessor": 2 |
| 80 | + }) |
| 81 | + assert(vertex_info[6] == { |
| 82 | + "distance": 1, |
| 83 | + "predecessor": 3 |
| 84 | + }) |
| 85 | + assert(vertex_info[7] == { |
| 86 | + "distance": None, |
| 87 | + "predecessor": None |
| 88 | + }) |
| 89 | + |
| 90 | + |
| 91 | +if __name__ == '__main__': |
| 92 | + main() |
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