ioftools / networkxMiCe / networkxmaster / networkx / algorithms / traversal / edgedfs.py @ 5cef0f13
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"""


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===========================

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Depth First Search on Edges

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===========================

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Algorithms for a depthfirst traversal of edges in a graph.

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"""

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import networkx as nx 
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FORWARD = 'forward'

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REVERSE = 'reverse'

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__all__ = ['edge_dfs']

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def edge_dfs(G, source=None, orientation=None): 
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"""A directed, depthfirstsearch of edges in `G`, beginning at `source`.

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Yield the edges of G in a depthfirstsearch order continuing until

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all edges are generated.

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Parameters

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G : graph

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A directed/undirected graph/multigraph.

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source : node, list of nodes

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The node from which the traversal begins. If None, then a source

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is chosen arbitrarily and repeatedly until all edges from each node in

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the graph are searched.

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orientation : None  'original'  'reverse'  'ignore' (default: None)

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For directed graphs and directed multigraphs, edge traversals need not

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respect the original orientation of the edges.

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When set to 'reverse' every edge is traversed in the reverse direction.

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When set to 'ignore', every edge is treated as undirected.

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When set to 'original', every edge is treated as directed.

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In all three cases, the yielded edge tuples add a last entry to

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indicate the direction in which that edge was traversed.

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If orientation is None, the yielded edge has no direction indicated.

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The direction is respected, but not reported.

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Yields

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edge : directed edge

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A directed edge indicating the path taken by the depthfirst traversal.

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For graphs, `edge` is of the form `(u, v)` where `u` and `v`

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are the tail and head of the edge as determined by the traversal.

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For multigraphs, `edge` is of the form `(u, v, key)`, where `key` is

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the key of the edge. When the graph is directed, then `u` and `v`

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are always in the order of the actual directed edge.

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If orientation is not None then the edge tuple is extended to include

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the direction of traversal ('forward' or 'reverse') on that edge.

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Examples

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>>> import networkx as nx

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>>> nodes = [0, 1, 2, 3]

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>>> edges = [(0, 1), (1, 0), (1, 0), (2, 1), (3, 1)]

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>>> list(nx.edge_dfs(nx.Graph(edges), nodes))

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[(0, 1), (1, 2), (1, 3)]

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>>> list(nx.edge_dfs(nx.DiGraph(edges), nodes))

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[(0, 1), (1, 0), (2, 1), (3, 1)]

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>>> list(nx.edge_dfs(nx.MultiGraph(edges), nodes))

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[(0, 1, 0), (1, 0, 1), (0, 1, 2), (1, 2, 0), (1, 3, 0)]

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>>> list(nx.edge_dfs(nx.MultiDiGraph(edges), nodes))

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[(0, 1, 0), (1, 0, 0), (1, 0, 1), (2, 1, 0), (3, 1, 0)]

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>>> list(nx.edge_dfs(nx.DiGraph(edges), nodes, orientation='ignore'))

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[(0, 1, 'forward'), (1, 0, 'forward'), (2, 1, 'reverse'), (3, 1, 'reverse')]

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>>> list(nx.edge_dfs(nx.MultiDiGraph(edges), nodes, orientation='ignore'))

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[(0, 1, 0, 'forward'), (1, 0, 0, 'forward'), (1, 0, 1, 'reverse'), (2, 1, 0, 'reverse'), (3, 1, 0, 'reverse')]

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Notes

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The goal of this function is to visit edges. It differs from the more

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familiar depthfirst traversal of nodes, as provided by

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:func:`networkx.algorithms.traversal.depth_first_search.dfs_edges`, in

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that it does not stop once every node has been visited. In a directed graph

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with edges [(0, 1), (1, 2), (2, 1)], the edge (2, 1) would not be visited

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if not for the functionality provided by this function.

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See Also

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dfs_edges

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"""

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nodes = list(G.nbunch_iter(source))

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if not nodes: 
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return

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directed = G.is_directed() 
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kwds = {'data': False} 
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if G.is_multigraph() is True: 
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kwds['keys'] = True 
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# set up edge lookup

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if orientation is None: 
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def edges_from(node): 
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return iter(G.edges(node, **kwds)) 
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elif not directed or orientation == 'original': 
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def edges_from(node): 
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for e in G.edges(node, **kwds): 
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yield e + (FORWARD,)

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elif orientation == 'reverse': 
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def edges_from(node): 
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for e in G.in_edges(node, **kwds): 
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yield e + (REVERSE,)

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elif orientation == 'ignore': 
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def edges_from(node): 
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for e in G.edges(node, **kwds): 
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yield e + (FORWARD,)

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for e in G.in_edges(node, **kwds): 
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yield e + (REVERSE,)

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else:

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raise nx.NetworkXError("invalid orientation argument.") 
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# set up formation of edge_id to easily look up if edge already returned

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if directed:

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def edge_id(edge): 
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# remove direction indicator

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return edge[:1] if orientation is not None else edge 
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else:

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def edge_id(edge): 
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# single id for undirected requires frozenset on nodes

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return (frozenset(edge[:2]),) + edge[2:] 
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# Basic setup

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check_reverse = directed and orientation in ('reverse', 'ignore') 
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visited_edges = set()

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visited_nodes = set()

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edges = {} 
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# start DFS

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for start_node in nodes: 
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stack = [start_node] 
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while stack:

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current_node = stack[1]

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if current_node not in visited_nodes: 
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edges[current_node] = edges_from(current_node) 
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visited_nodes.add(current_node) 
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try:

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edge = next(edges[current_node])

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except StopIteration: 
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# No more edges from the current node.

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stack.pop() 
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else:

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edgeid = edge_id(edge) 
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if edgeid not in visited_edges: 
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visited_edges.add(edgeid) 
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# Mark the traversed "to" node as tobeexplored.

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if check_reverse and edge[1] == REVERSE: 
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stack.append(edge[0])

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else:

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stack.append(edge[1])

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yield edge
