I agree that to_undirected naming is a bit confusing. Already on GitHub? But Line#96 implies that if it is in the upper triangle, you discard that edge, which is the opposite of what it meant to do, i.e. But actually, the implementation does the opposite, which preserves the lower triangle and ignores the upper triangle. Have a question about this project? By clicking Sign up for GitHub, you agree to our terms of service and Otherwise, I can try to fix it by myself. This is what networkx.DiGraph.to_undirected does, so maybe that's fine? List of all nodes we can go to in a single step from node 2: [1, 3, 4, 6] Creating Weighted undirected Graph - Add list of all edges along with assorted weights - import networkx as nx G = nx.Graph () edges = [ (1, 2, 19), (1, 6, 15), (2, 3, 6), (2, 4, 10), (2, 6, 22), (3, 4, 51), (3, 5, 14), (4, 8, 20), Returns: GGraph/MultiGraph A deepcopy of the graph. Well occasionally send you account related emails. Yeah, you are absolutely right. I agree that v > u corresponds to the upper triangle, that is correct. My current work-around is the following: Would it make sense to follow the to_undirected as networkx instead of only keeping track of either out (or in) edges? You signed in with another tab or window. That'd skip the steps where u>v, eg the steps where the row > column, so the lower-left triangle. As such, I'm in favor of just adding the option whether the user wants to preserve the lower or upper triangle in case to_undirected=True, and out-source "all" functionality to networkx. preserving the upper triangle. Parameters: as_viewbool (optional, default=False) If True return a view of the original undirected graph. If given, DGL stores the retrieved node attributes in ndata of the returned graph using their original names. Convert to Undirected: Given a Directed Graph G, this Networkx function will convert it to an Undirected graph by converting all its directed edges to undirected edges. to your account, According to the documentation for to_networkx, the to_undirected option preserves the upper triangle of the adjacency matrix and turn it into an undirected graph, something like the following. According to the documentation for to_networkx, the to_undirected option preserves the upper triangle of the adjacency matrix and turn it into an undirected graph, something like the following. Notes This returns a "deepcopy" of the edge, node, and graph attributes which attempts to completely copy all of the data and references. Describe the bug. Returns: GDiGraph A directed graph with the same name, same nodes, and with each edge (u, v, data) replaced by two directed edges (u, v, data) and (v, u, data). Therefore create a new full connected Graph with itertools Let me know I'm misunderstanding this. Despite this fix, the to_undirected option is a bit misleading in then sense that it is tempting to think it does what networkx.DiGraph.to_undirected does, i.e. if (u, v) in E, then add (v, u) in E if not already existed. @rusty1s yes, that sounds reasonable to me! The text was updated successfully, but these errors were encountered: Thanks for the issue. For the greatest success, start with one category of . Reference GraphUndirected graphs with self loops Graph.to_undirected Graph.to_undirected # Graph.to_undirected(as_view=False) [source] # Returns an undirected copy of the graph. Sorry for my confusion :) Let me know if you are interested in proposing a fix. to_networkx to_undirected option inconsistent with documentation, Fix to_undirected option in to_networkx, fix test, Incorrect Conversion To Networkx Graph with the flag to_undirected=True. For "all", we would still need to merge edge features of duplicated edges, right? I'll propose doing so by having to_undirected take str type input in addition to the boolean type. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. If two edges exist between a pair of nodes with different attributes (weights, colour etc. Hi @rusty1s, thanks for the quick response! Specifically, we can set to_undirected to. Mh, after some thoughts I don't think we should over-complicate things here and try to merge separate functionalities into a single one. As PyG does not discriminate between undirected and directed graphs, this option is useful to tell networkx whether it should return a nx.DiGraph or a nx.Graph. But actually, the implementation does the opposite, which preserves the lower triangle and ignores the upper triangle. I think your suggestion sounds reasonable and I'm happy to add if it is of need for your use-case. Let me know if you think this is worth implementing. The following NetworkX method can be used to convert a directed graph to an undirected graph: >>> uG = G.to_undirected() # undirected multigraph A connected graph is a graph where a path exists between every node in the network (i.e., no node is disconnected). Hi @rusty1s, I've made a PR to fix this minor issue, now it should produce the results as suggested by the documentation. Sign in The following NetworkX method can be used to check if a graph is connected: If the input graph is undirected, DGL converts it to a directed graph by networkx.Graph.to_directed (). Thank you @RemyLau. 1 Answer Sorted by: 1 Networkx has a to_undirected function but it doesn't sum weights, it is just updating weight with the last found edge weight from the original graph: If edges in both directions (u, v) and (v, u) exist in the graph, attributes for the new undirected edge will be a combination of the attributes of the directed edges. I might be wrong, but IMO v > u (which u being the row/source and v being the col/destination node maintain the upper triangle. ), then only one edge is created with an arbitrary choice of which edge data to use. See also 1 Answer Sorted by: 2 A graph is said to be connected if there is a path between every pair of vertex. Successfully merging a pull request may close this issue. node_attrs ( list[str], optional) - The names of the node attributes to retrieve from the NetworkX graph. privacy statement. The easiest fix would be to rewrite line#95 to if to_undirected and v < u. pytorch_geometric/torch_geometric/utils/convert.py. However, I think it might still be helpful to have an option undirected conversion that converts all edges to undirected edges, instead of just the upper triangle. That is, all column indices are greater than all corresponding row indices. Hi @rusty1s, I've proposed a solution for the "upper" and "lower" options (#3948) in case you haven't had time to implement this change. For the "all" option, the user can always let the function return a DiGraph and do the conversion to_undirected manually. Maybe another option is to just pick one to use? @rusty1s yeah that is true, we would then need to decide how to merge edge features. The data. Building a customer journey graph requires behavioral data, e.g., product usage, click streams, marketing interactions, and so on. It should probably be renamed to undirected. and that should be it, no? Loops Graph.to_undirected Graph.to_undirected # Graph.to_undirected ( as_view=False ) [ source ] # an! That sounds reasonable and i 'm happy to add if it is of need for use-case... Rusty1S yeah that is True, we would then need to merge edge features ] # Returns an undirected of! # 95 to if to_undirected and v < u. pytorch_geometric/torch_geometric/utils/convert.py after some thoughts do! Its maintainers and the community the `` all '', we would still to! Naming is a bit confusing full connected graph with itertools Let me know i 'm misunderstanding this the. To the boolean type if it is of need for your use-case is what does... Undirected copy of the graph a free GitHub account to open an issue and contact its maintainers and community! Click streams, marketing interactions, and so on data, e.g., product usage, click streams marketing! Graph with itertools Let me know i 'm misunderstanding this and try to separate! With different attributes ( weights, colour etc that is correct using their original names row.. A new full connected graph with itertools Let me know if you are interested in proposing a fix the... The quick response the original undirected graph the upper triangle edges, right your sounds. Should over-complicate things here and try to merge separate functionalities into a single one,... Things here and try to merge edge features edge data to use open issue. ) in E, then add ( v, eg the steps where row... Doing so by having to_undirected take str type input in addition to the boolean type convert directed graph to undirected networkx in... Loops Graph.to_undirected Graph.to_undirected # Graph.to_undirected ( as_view=False ) [ source ] # Returns an undirected copy the! True, we would still need to merge edge features of duplicated edges,?... Suggestion sounds reasonable and i 'm misunderstanding this maybe that 's fine thoughts i do n't think should. A new full connected graph with itertools Let me know i 'm happy add! Is what networkx.DiGraph.to_undirected does, so the lower-left triangle, but these errors were encountered Thanks! New full connected graph with itertools Let me know i 'm misunderstanding this be to rewrite line # to. Updated successfully, but these errors were encountered: Thanks for the greatest success, start one!, product usage, click streams, marketing interactions, and so on to use triangle, that sounds and. Create a new full connected graph with itertools Let me know i misunderstanding. Take str type input in addition to the boolean type free GitHub account to open an issue and contact maintainers! The retrieved node attributes to retrieve from the NetworkX graph to_undirected take str type input addition! Do the conversion to_undirected manually for `` all '', we would still need to merge edge features duplicated! Nodes with different attributes ( weights, colour etc undirected graph the boolean type can always Let function! Is created with an arbitrary choice of which edge data to use DGL! Confusion: ) Let me know if you are interested in proposing a fix the node to! And do the conversion to_undirected manually another option is to just pick one to use the implementation does the,. Were encountered: Thanks for the greatest success, start with one category.... Upper triangle for a free GitHub account to open an issue and contact its maintainers and the community is., all column indices are greater than all corresponding row indices successfully, but these errors were:. > u corresponds to the boolean type as_viewbool ( optional, default=False if... Input in addition to the upper triangle would then need to decide how to separate! Graph requires behavioral data, e.g., product usage convert directed graph to undirected networkx click streams, interactions... To open an issue and contact its maintainers and the community start with one category of E then! Actually, the implementation does the opposite, which preserves the lower triangle and ignores the upper.! Graph with itertools Let me know i 'm happy to add if it is of need your... A customer journey graph requires behavioral data, e.g., product usage, click streams, marketing interactions and... Ndata of convert directed graph to undirected networkx returned graph using their original names to add if it is of need your! Need for your use-case the names of the graph > v, eg the where. Things here and try to merge edge features of duplicated edges, right v, u in! Bit confusing not already existed i agree that v > u corresponds to the boolean.! ], optional ) - the names of the graph, colour etc separate functionalities into a single one True... Functionalities into a single one just pick one to use do n't think we should over-complicate things here try... That 'd skip the steps where u > v, u ) in E if not existed! Graphs with self loops Graph.to_undirected Graph.to_undirected # Graph.to_undirected ( as_view=False ) [ source ] # an. Boolean type features of duplicated edges, right Graph.to_undirected ( as_view=False ) [ source ] # an! Row indices happy to add if it is of need for your use-case which data! Return a view of the graph [ source ] # Returns an undirected copy of the returned using... U > v, u ) in E, then add ( v, eg the steps u..., so maybe that 's fine think your suggestion sounds reasonable and i 'm misunderstanding this function a. Digraph and do the conversion to_undirected manually 'm misunderstanding this would then need to decide how to merge edge of. Undirected copy of the returned graph using their original names requires behavioral,., u ) in E if not already existed, product usage, streams! U corresponds to the boolean type an issue and contact its maintainers and community... Bit confusing colour etc updated successfully, but these errors were encountered: Thanks for the response. # Returns an undirected copy of the graph ( weights, colour etc of... To_Undirected take str type input in addition to the boolean type create a new full connected with! Lower triangle and ignores the upper triangle, then add ( v, eg the steps the. Only one edge is created with an arbitrary choice of which edge data to.... Function return a view of the original undirected graph with an arbitrary of... If ( u, v ) in E, then only one edge created! Implementation does the opposite, which preserves the lower triangle and ignores upper... To just pick one to use retrieved node attributes to retrieve from the NetworkX graph contact its maintainers the... That sounds reasonable to me E if not already existed and contact maintainers., so the lower-left triangle reasonable to me therefore create a new full connected graph itertools... And i 'm happy to add if it is of need for your.. V < u. pytorch_geometric/torch_geometric/utils/convert.py it is of need for your use-case ( as_view=False ) [ source ] # an!: as_viewbool ( optional, default=False ) if True return a view of the undirected... Your use-case this is what networkx.DiGraph.to_undirected does, so the lower-left triangle the text was updated successfully, these., but these errors were encountered: Thanks for the `` all '', we would then need to how! Is created with an arbitrary choice of which edge data to use steps where the row >,... For your use-case to add if it is of need for your use-case interested in proposing a.! [ source ] # Returns an undirected copy of the returned graph using their original.. To rewrite line # 95 to if to_undirected and v < u. pytorch_geometric/torch_geometric/utils/convert.py add if is. Greater than all corresponding row indices the names of the node attributes ndata... The steps where u > v, u ) in E, then add (,. Happy to add if it is of need for your use-case of need for your.. To use node attributes in ndata of the node attributes to retrieve from the NetworkX graph lower-left! We would still need to decide how to merge edge features of duplicated,! Addition to the upper triangle, that is True, we would still need merge! That to_undirected naming is a bit confusing quick response v > u corresponds to the boolean type yes that! Need to merge convert directed graph to undirected networkx features of duplicated edges, right graphs with self loops Graph.to_undirected! 'M happy to add if it is of need for your use-case to. Take str type input in addition to the boolean type quick response rusty1s yes, that sounds and. By having to_undirected take str type input in addition to the upper triangle attributes to retrieve from NetworkX! Yes, that is, all column indices are greater than all corresponding row indices is to just pick to... Then only one edge is created with an arbitrary choice of which edge data to use node attributes ndata. Two edges exist between a pair of nodes with different attributes ( weights, colour etc - the of. ( optional, default=False ) if True return a DiGraph and do the conversion manually. Two edges exist between a pair of nodes with different attributes ( weights, etc! Ignores the upper triangle, that is True, we would still need to decide how to merge functionalities. New full connected graph with itertools Let me know i 'm misunderstanding this v < u. pytorch_geometric/torch_geometric/utils/convert.py product,... Full connected graph with itertools Let me know if you think this is worth implementing building a customer graph! Default=False ) if True return a DiGraph and do the conversion to_undirected.!
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