subgraph

I have code to display two subgraphs: graph { rankdir=LR; subgraph cluster01 { label="t=0" a0 [label="A"]; a1 [label="B"]; a2 [label="C"]; a5 [label="E"]; a0 -- a1; a1 -- a2 ; a2 -- a0; }; subgraph cluster02 { label="t=10" b0 [label="A"]; b5 [label="E"]; b1 [label="B"]; b2 [label="C"]; b0 -- b1; b2 -- b5; }; a0--b0 [style=dotted]; a1--b1 [style=dotted]; a2--b2 [style=dotted]; a5--b5 [style=dotted]; } This code displays two subgraphs like this: But I want to have it like this: I hope someone will help me fix the "rankdir" to get it done. The following was achieved by using invisible edges and

In one of the projects I've worked on, the subject of isomorphism versus monomorphism came up . A little background: I'm no expert on graph theory and have no formal training in it. But this topic is very important in chemistry, where chemists expect a particular kind of subgraph matching to take place in the structure search systems they use. If a target graph A has n nodes and m edges, then a chemist would accept subgraph matches in which a query graph B had n nodes and m-1 edges. The only requirement would be that every edge in B should be present in A. For example, a linear chain of 6

I have downloaded a tensorflow GraphDef that implements a VGG16 ConvNet, which I use doing this : Pl['images'] = tf.placeholder(tf.float32, [None, 448, 448, 3], name="images") #batch x width x height x channels with open("tensorflow-vgg16/vgg16.tfmodel", mode='rb') as f: fileContent = f.read() graph_def = tf.GraphDef() graph_def.ParseFromString(fileContent) tf.import_graph_def(graph_def, input_map={"images": Pl['images']}) Besides, I have image features that are homogeneous to the output of the "import/pool5/" . How can I tell my graph that don't want to use his input "images" , but the tensor

I have been dealing with Neo4j through python's Bulbflow and now need a way to save/export subgraphs. I have seen Java and even Ruby approaches for doing this, however a simple Python approach seems to be hiding from me.. So far, I have found two potential paths: Accessing Geoff through py2neo , but there is surprisingly little documentation for extracting a subgraph from a big local neo4j database or from a neo4jserver. Using Networkx : I found networkx can load graphs from many different formats (I am unsure which format neo4j stores their dbs), however I haven't found a way to extract a

I have an unweighted, connected graph. I want to find a connected subgraph that definitely includes a certain set of nodes, and as few extras as possible. How could this be accomplished? Just in case, I'll restate the question using more precise language. Let G(V,E) be an unweighted, undirected, connected graph. Let N be some subset of V. What's the best way to find the smallest connected subgraph G'(V',E') of G(V,E) such that N is a subset of V'? Approximations are fine. I can't think of an efficient algorithm to find the optimal solution, but assuming that your input graph is dense, the

I have a large network stored in Neo4j. Based on a particular root node, I want to extract a subgraph around that node and store it somewhere else. So, what I need is the set of nodes and edges that match my filter criteria. Afaik there is no out-of-the-box solution available. There is a graph matching component available , but it works only for perfect matches. The Neo4j API itself defines only graph traversal which I can use to define which nodes/edges should be visited: Traverser exp = Traversal .description() .breadthFirst() .evaluator(Evaluators.toDepth(2)) .traverse(root); Now, I can add

I have a graph which contains an unknown number of disconnected subgraphs. What's a good algorithm (or Java library) to find them all? I think what you are looking for is generally called a Flood Fill . It is up to you whether you traverse the graph through a BFS or a DFS. Basically you take an unlabeled (AKA uncoloured) node and assign a new label to it. You assign the same label to all nodes adjacent to that one, and so on to all nodes that are reachable from that node. When no more reachable nodes can be labeled, you start over by picking another unlabeled node. Notice that the fact that

Is there a known algorithm or method to find all complete sub-graphs within a graph? I have an undirected, unweighted graph and I need to find all subgraphs within it where each node in the subgraph is connected to each other node in the subgraph. Is there an existing algorithm for this? This is known as the clique problem ; it's hard and is in NP-complete in general, and yes there are many algorithms to do this. If the graph has additional properties (e.g. it's bipartite), then the problem becomes considerably easier and is solvable in polynomial time, but otherwise it's very hard, and is