graph-tool July 2018

graph-tool@skewed.de

14 participants
19 discussions

How to control the orientation of the graph topology
by Xun Xiao 26 Feb '22

26 Feb '22

Hi Tiago, sometimes, when delete the graph and create a new one, then plot it, the plotted graph is shown upside down (in terms of the node text). So how could we control the orientation of the graph? Or which parameter we should use to always make node text shown in a correct orientation. Thanks a lot. -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com… Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.

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Upside down labels
by charlie 26 Feb '22

26 Feb '22

Hi, I'm suffering from the same issue mentioned in this post: https://git.skewed.de/count0/graph-tool/issues/174 Namely, I'm trying to draw a graph that includes a lot of self-looping edges, and my labels are being printed upside down. If I remove the self-loops the labels are shown the right way up. Is there a fix for it? Thanks, Charlie -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com… Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.

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What formula is used for std in vertex_average and edge_average?
by VaSa 16 Jul '20

16 Jul '20

I am curious what is being used to calculate the standard deviation of the average in gt.vertex_average and gt.edge_average >>> t2=gt.Graph() >>> t2.add_vertex(2) >>> t2.add_edge(t2.vertex(0), t2.vertex(1)) >>> gt.vertex_average(t2, "in") (0.5, 0.35355339059327373) Now, shouldn't std be σ(n)=sqrt(((0-0.5)^2+(1-0.5)^2)/2)=0.5 ? also q(n-1)=sqrt((0.5^2+0.5^2)/(2-1))~=0.70710 0.3535 is sqrt(2)/4 which happens to be σ(n-1)/2, so it seems there is some relation to that. A little bigger graph. >>> t3=gt.Graph() >>> t3.add_vertex(5) >>> t3.add_edge(t3.vertex(0), t3.vertex(1)) >>> gt.vertex_average(t3, "in") (0.2, 0.17888543819998318) Now, we should have 0,1,0,0,0 series for vertex incoming degree. So Windows calc gives σ(n)=0.4 and σ(n-1)~=0.44721, so where does 0.1788854 come from ? Reason, I am asking because, I have a large graph, where the average looks quite alright but the std makes no sense, as going by the histogram, degree values are quite a bit more distributed than the std would indicate. -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com… Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.

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assigning vertex properties when adding edges
by m jadidi 04 Mar '20

04 Mar '20

Hi, I was wondering if there is any way to assign vertex properties while adding edges to the graph. for example using "add_edge_list" I can assign edge properties but later I have to iterate through all vertices again to assign their properties. I know this is not a problem when the vertex property is of the type "int" or "float" because then one can use "vprop.a = values", but in case of "string" and "object" this method doesn't work What would be the best/fastest way to handle this situation. I guess it would be very helpful to extend the "add_edge_list" function to accept vertex property in some way. cheers, -- Mohsen

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Nested Block State hierarchy level after mcmc_equilibrate
by ilyco 16 Jan '20

16 Jan '20

I ran mcmc_equilibrate on a nested block state model in a weighted graph. As per instructions, I copied the initially computed state in another object with increased hierarchy depth to 10. However, this fixed the depth to 10. Everything computed afterwards has depth 10 even if is clear that after 3 or 4 levels the nodes converge to one. There are many empty branches and when I try to plot it with empty_branches = False, I get an error stating it is not a tree. RuntimeError: Invalid hierarchical tree: No path from source to target. Did anybody perform any similar analyses? The hierarchy after mcmc_equilibrate: <NestedBlockState object, with base <BlockState object with 24 blocks (24 nonempty), degree-corrected, with 1 edge covariate, for graph <Graph object, undirected, with 230 vertices and 11230 edges, edges filtered by (<PropertyMap object with key type 'Edge' and value type 'bool', for Graph 0x7fc3a89f1210, at 0x7fc3a64911d0>, False), vertices filtered by (<PropertyMap object with key type 'Vertex' and value type 'bool', for Graph 0x7fc3a89f1210, at 0x7fc3a64912d0>, False) at 0x7fc3a89f1210>, at 0x7fc3a6491950>, and 10 levels of sizes [(230, 24), (24, 5), (5, 1), (1, 1), (1, 1), (1, 1), (1, 1), (1, 1), (1, 1), (1, 1)] at 0x7fc3a6491590> -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

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Problem with add_edge_list(eprop=x)
by JHickey 04 Oct '18

04 Oct '18

I'd like to use the "add_edge_list" function to add edges to my graph, and simultaneously assign a value for an edge property map for each of the added edges. When I try the following example (with no edge property map information) works fine: elist1 = np.array([[0,1], [1, 2]]) #edge list with no value for edge property map data (only the source and target for the edges) g = gt.Graph() my_eprop = g.new_edge_property('bool') g.add_edge_list(elist) But with the following example, I get the error below: elist2 = np.array([[0,1, 1], [1, 2, 0]]) #edge list with edge property map value in 3rd column g = gt.Graph() my_eprop = g.new_edge_property('bool') g.add_edge_list(elist2, eprops=my_eprop) Error: --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-48-6a949ea52c9b> in <module>() ----> 1 g.add_edge_list(elist2, eprops=my_eprop) /usr/lib/python2.7/dist-packages/graph_tool/__init__.pyc in add_edge_list(self, edge_list, hashed, string_vals, eprops) 1969 eprops = () 1970 else: -> 1971 convert = [_converter(x.value_type()) for x in eprops] 1972 eprops = [_prop("e", self, x) for x in eprops] 1973 if not isinstance(edge_list, numpy.ndarray): /usr/lib/python2.7/dist-packages/graph_tool/__init__.pyc in __getitem__(self, k) 534 kt = "Graph" 535 raise ValueError("invalid key '%s' of type '%s', wanted type: %s" --> 536 % (str(k), str(type(k)), kt) ) 537 538 def __setitem__(self, k, v): ValueError: invalid key '0' of type '<type 'int'>', wanted type: Edge --------------------------------------------------------------------------- Please help! -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com… Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.

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Viewing the gt.collection.data as a pandas Dataframe
by Rachit Saluja 06 Aug '18

06 Aug '18

Hello, I have recently started working with graph-tool, and was wondering if we can try to view any of the data provided in the repo as a pandas Dataframe? This would be helpful, because I would like to analyze a few things with a custom dataset. For example, gt.collection.data["celegansneural"], can it be displayed as a dataframe? Or any other way? I would like to see the all the content in it. Warm regards, Rachit Saluja

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clabel usage for partial constraints
by Anatol Wegner 06 Aug '18

06 Aug '18

Hi, I have a question regarding the implementing partial constraints during blockmodel minimization. By partial constraints I mean that I have a group of vertices V1 that are pre-labeled into k clusters i.e. vertices from V1 that are in different clusters should not mix. Then there is a second set of vertices V2 that should be able to mix freely with vertices from both V1 and V2. I have tried defining a corresponding vertex property and passing it to clabel argument but have always ended up with partitions in which V1 and V2 don't mix in the final state. Best regards, Anatol

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Nested Block Model Confusion
by ashutosh 27 Jul '18

27 Jul '18

Sir, I have three doubts to clarify which I list here 1.) I am trying to use the following function for my graph: *class graph_tool.inference.nested_blockmodel.NestedBlockState(g, bs, base_type=<class 'graph_tool.inference.blockmodel.BlockState'>, state_args={}, hstate_args={}, hentropy_args={}, sampling=False, **kwargs)* I am not able to understand what do I need to provide for *'bs'* values in the arguments. The tutorial mentions that it is a *Property Map Hierarchical node partition*. What I understand it is asking for a prior hierarchical information about the nodes which can be done using hierarchical clustering. If this is the case then how does hierarchical partition help me ? because it is mentioned in the tutorial that to overcome the limit of BlockState function to identify smaller communities in very large graph this function was implemented. My graph is very large and I didn't keep any hierarchical information along with it. If not then what do I need to pass to the argument 'bs' in this function ? 2.) Suppose I have a network myG with N nodes and E edges , undirected and no value specifically assigned in the edge, vertex or graph property map. I want to do the nested block model partition with mcmc equilibrate to get the best partition. Then are these steps to do so correct. a) Import graph_tool.inference and graph_tool.all b) define your graph myG as *"NestedBlockState"* c) minimize your NestedBlockState using the *minimize_nested_blockmodel_dl(myG)* function d) run mcmc_equilibrate function on minimized nested block state to find the best partitions in n iterations. 3.) While using LayeredBlockState function, you mentioned in one of your mailing list reply, one should collapse the graph as a single graph with multiple edges. What I understood by trying some random code is that i can add multiple edges between two nodes but pass a different property map for each edge defining the corresponding layer. Finally use this Property Map in LayeredBlockState function by passing it to 'ec' parameter. Am I right on this ? 4.) Which draw/plot function should be used to plot very large graphs. My graph has 6500 nodes and 95000 edges. The calling of function draw() gives memory error (for SVG format), PDF format fails to load for a very long time and PNG format is of very low resolution. GraphViz doesn't work due to error related to libv which I saw is a bug in the mailing list due to the libv library. -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

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Precompiled Binary (Arch Linux)
by dartheian 26 Jul '18

26 Jul '18

Hi everyone, I am not sure if I have to post this discussion here or on Arch Linux's forums, so sorry if this is not the right place. As far as I understood, this library is written in C++ and wrapped with Python. So it is similar to other high-performance libraries (like Numpy) in such sense. Other libraries, like Numpy itself, are available trough precompiled packages for almost every main distribution (including Arch). Currently precompiled (I think) graph-tool packages are available just for Debian and Ubuntu, while Arch has only an AUR package which "unfortunately" require compilation. I think this library is awesome and should have a precompiled Arch package to make it immediate to install on such systems, so that way, for example, we can just treat it like a normal package dependency to other packages simplifing developement and distribution of other software who require graph-tool and ask less expert users just to type a bunch of simple commands to install the package instead of compile it. Is it possible to do such a thing? If yes, do you plan to do it? Should I ask on Arch forums instead? I understand C++ makes thigs difficult for portability, but the majority of linux libraries are written in C and have a precompiled package on major distributions. But, as i sayed, graph-tool it is similar (I think) to a lot of neat C++/Python libraries which have an Arch precompiled package. Does create an Arch package ask too much effort for graph-tool developers in order maintain the software? Please, tell me if I am wrong on something and thanks in advance for your reply. One of the coolest libraries I ever seen! Even the documentation is awesome (love the fact thath you specify types even in a weak-typed language, the notes on complexity of the algorithms...) and today is a rare thing :) --Daniele -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

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graph-tool July 2018