Pauline - Fire #1
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CheezItMan
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May 20, 2021
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| # Time Complexity - O(v + e) Using BFS, the function checks each vertex through the queue once, and all edges | ||
| # associated with that queue once or twice at most. Checking for non biparition-able graphs via edges beforehand | ||
| # and only adding to the queue any edges with vertices that haven't been visited as a vertex prevents | ||
| # repeat vertices from being visited. | ||
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| # Space Complexity - O(v) - A hash, and set, and a queue are created where the max number of elements added will never exceed | ||
| # the number of vertices (v) in the graph. group_hash will always have two keys between which the vertices are divided into based on | ||
| # edges, to_visit is a set of all vertices to delete from (in O(1) time), while bfs at worst will have all vertices in the Queue, | ||
| # as the function doesn't add any edges that have already been visited. to_visit mostly exists to track any vertices | ||
| # in a graph that aren't reached by a group of other vertices in the graph, which group_hash and bfs_q can't account for. | ||
| def possible_bipartition(dislikes) |
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Nice implementation of Breadth-first-search. Well done!
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| # set current group for leading vertex | ||
| v_group = 1 | ||
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| # set current group for edges | ||
| e_group = 2 |
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This works to label the groups, I just used the symbols :red, and :green to label the groups.
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Will update with any improvements as I revisit. Thank you!!