graph-tool June 2020

graph-tool@skewed.de

14 participants
22 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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random graph
by JM 01 Sep '21

01 Sep '21

Dear Tiago, I have a directed graph of about half a million nodes and approximately a million edges following scale free behaviour and a power law degree distribution. To test some of my hypothesis, I would like to generate random smaller graphs (about 50 up to 200 nodes) representative of the big one. When I used a sample function that samples straight away from the real distribution of the big network, I have following problems: - I generate unconnected nodes with both 0 in AND out degree. - I generate small sub parts of a few nodes that are not connected to the main graph. - If only sampling from nodes with at least 1 degree, the generated graph is coherent, but not representative anymore as I need a big portion of nodes with either only one in or one out degree. Here is the part of my script I used for that, where samples are drawn from dictionaries of the degrees: def sample_in(): a=np.random.randint(num) k_in = in_degrees[a] return k_in def sample_out(): if sample_in()==0: b=np.random.randint(num_out) k_out=out_zero_zeros.values()[b] return k_out else: b=np.random.randint(num) k_out=out_degrees[b] return k_out N=200 g=gt.random_graph(N, lambda:(sample_in(), sample_out()), model="constrained-configuration", directed=True) I also tried sampling from a list of tuples as you have mentioned before in the forum, but I didn't receive any results, as the tuples randomly drawn from my list might not be combinable. degs=[(7,1),(4,3),(5,6),(2,4),(6,8),(2,0),(3,5),(0,3),(2,7),(2,1)] g = gt.random_graph(4, lambda i: degs[i], directed=True) - Is there any option I could active that would help me in those cases I described above? - Is there a better way how to create representative small networks? Any help on that issue will be much appreciated. Best wishes, Jana -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

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get_hierarchy_control_points return values
by Davide Cittaro 20 Apr '21

20 Apr '21

Hi again, I'm writing a small package that builds on graph-tool, but not on its graphics capabilities (also because I have to represent other things rather than the graph itself). Still I could use some of the functions "under the hood" for my purposes. I have a question about gt.draw.get_hierarchy_control_points(): the function returns the Bézier spline control points for edges in a given graph, but I'm having difficulties in understanding how this information is encoded. For a single edge in graph, I have dozens of values as control points (half dozens + 2), hence I suspect all splines going from node A to the root of a hierarchy and back to node B are encoded there, and control points should be taken 6 by 6 (3x2 by 3x2 coordinates?). How (x,y) for control points are encoded then: (x, x, x, y, y, y) or (x, y, x, y, x, y)? What are the 2 additiona values I have for each vector? Also, are values absolute or relative to one node in particular (A, B or root...)? Thanks d

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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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Freeze using SIRState
by Ronaldo Alves 30 Jun '20

30 Jun '20

Hi everyone, I am conducting tests where I perform several parallel tests of the SIR model (they are not using n iterations because I need to find out when the model stabilizes, where si (t) = 0). Parallel execution has been carried out with the multiprocessing library. In larger networks (2000 nodes), when performing the procedure of removing parallel edges (the graphs are converted to undirected), the execution freeze. Can you imagine the reason for this behavior? If I don't execute the remove_parallel_edges function, everything happens normally ... Execution hangs when iterate_sync will be performed. A serial run works normally (without multiprocessing). Would anyone have a tip? Best regards, Ronaldo Alves

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Unable to install on ubuntu 16.04 LTS
by dexterd 30 Jun '20

30 Jun '20

Hi, I followed the instructions in the official website (https://git.skewed.de/count0/graph-tool/-/wikis/installation-instructions#d…) to install graph-tool on ubuntu 16.04 LTS. I set DISTRIBUTION to xenial (corresponding to ubuntu 16.04 LTS). Then I downloaded the public key as instructed. However, when I ran apt-get update, it reported the error: "The repository 'https://downloads.skewed.de/apt xenial Release' does not have a Release file". The following line would not work, neither. I wonder which DISTRIBUTION should I set? I tried the ones listed in the website but failed when executing the "apt-get install python3-graph-tool"... Thank you very much for your time and I look forward to you reply. -- Sent from: https://nabble.skewed.de/

2 2

Doubt about SIR model
by Ronaldo Alves 24 Jun '20

24 Jun '20

Dear graph-tool community, I have a little doubt off the topic. I've been checking out the SIR model. In the mathematical expression what is the meaning of the variable ri? Was it the likelihood of spontaneous infection of the node? I checked the references, but I still couldn't understand. Can you help me? Best regards, Ronaldo Alves

2 2

Could not link against boost iostream
by hadars 23 Jun '20

23 Jun '20

Hi, while trying to compile manually graph-tool on ubunto 20.04 by running ./configure, I'm getting this error message: configure: error: Could not link against boost _iostreams when checking the config.log file, it says: /usr/bin/ld: cannot find -lboost_iostreams How can I solve this? Thanks! -- Sent from: https://nabble.skewed.de/

2 1

fail to build for GCC 8.3.0
by slitvinov 22 Jun '20

22 Jun '20

graph-tools fail to build with g++ (GCC) 8.3.0 20190222 with the following error message: In file included from blockmodel/graph_blockmodel_mcmc.cc:26: blockmodel/../loops/mcmc_loop.hh: In lambda function: blockmodel/../loops/mcmc_loop.hh:84:42: error: lambda capture of 'single_step' is not a constant expression if constexpr (single_step) ^ make[3]: *** [Makefile:1047: blockmodel/graph_blockmodel_mcmc.lo] Error 1 make[3]: Leaving directory '/users/lisergey/ClearMap2/graph-tool/src/graph/inference' make[2]: *** [Makefile:810: install-recursive] Error 1 make[2]: Leaving directory '/users/lisergey/ClearMap2/graph-tool/src/graph' make[1]: *** [Makefile:422: install-recursive] Error 1 make[1]: Leaving directory '/users/lisergey/ClearMap2/graph-tool/src' make: *** [Makefile:599: install-recursive] Error 1 -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

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graph-tool June 2020