我的输入是一个列表列表.其中一些共享共同的元素,例如.
My input is a list of lists. Some of them share common elements, eg.
L = [['a','b','c'],['b','d','e'],['k'],['o','p'],['e','f'],['p','a'],['d','g']]我需要合并所有共享一个公共元素的列表,并重复此过程,只要不再有包含相同项目的列表即可.我曾考虑过要使用布尔运算和while循环,但无法提出一个好的解决方案.
I need to merge all lists, that share a common element, and repeat this procedure as long as there are no more lists with the same item. I thought about using boolean operations and a while loop, but couldn't come up with a good solution.
最终结果应该是:
L = [['a','b','c','d','e','f','g','o','p'],['k']]推荐答案
您可以将列表看作是Graph的一种表示法,即['a','b','c']是一个具有3个相互连接的节点的图.您要解决的问题是在此图中找到连接的组件.
You can see your list as a notation for a Graph, ie ['a','b','c'] is a graph with 3 nodes connected to each other. The problem you are trying to solve is finding connected components in this graph.
为此,您可以使用 NetworkX ,它的优点是几乎可以保证是正确的:
You can use NetworkX for this, which has the advantage that it's pretty much guaranteed to be correct:
l = [['a','b','c'],['b','d','e'],['k'],['o','p'],['e','f'],['p','a'],['d','g']] import networkx from networkx.algorithmsponents.connected import connected_components def to_graph(l): G = networkx.Graph() for part in l: # each sublist is a bunch of nodes G.add_nodes_from(part) # it also imlies a number of edges: G.add_edges_from(to_edges(part)) return G def to_edges(l): """ treat `l` as a Graph and returns it's edges to_edges(['a','b','c','d']) -> [(a,b), (b,c),(c,d)] """ it = iter(l) last = next(it) for current in it: yield last, current last = current G = to_graph(l) print connected_components(G) # prints [['a', 'c', 'b', 'e', 'd', 'g', 'f', 'o', 'p'], ['k']]要自己有效地解决此问题,无论如何,您都必须将列表转换为类似图形的内容,因此您最好从一开始就使用networkX.
To solve this efficiently yourself you have to convert the list into something graph-ish anyways, so you might as well use networkX from the start.
更多推荐
合并具有共同元素的列表
发布评论