October 2016 - graph-tool - archives.skewed.de

Images in vertices
by Nils Hachmeister 15 Nov '16

15 Nov '16

Hello, I'm using graph_tool in a scenario, in which the meaning of a vertex cannot be easily be explained by a label or a text. To get a meaningful graph I would need to display a image inside the vertices. Has anyone an idea, how could this be achieved? Thanks Soraltan

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random_graph stochastic block model produces unreasonably interconnected blocks
by G. B. 04 Nov '16

04 Nov '16

I'm currently building two-type random graphs of 100 vertices using the traditional_blockmodel feature of the random_graph/random_rewire functions. The degree_sampler I'm using is just lambda: poisson(5), which means that my graphs have about 250 edges. My blocks contain 15 vertices and 85 vertices respectively. When I tune the correlation function in the following way: def corr(a,b): if a==b: return 20 else: return 1 I would expect, based on the documentation, that the following is approximately true: 250 edges = (15*85)*(1*p_baseline) + (15 choose 2)*(20*p_baseline)+(85 choose 2)*(20*p_baseline). Solving this equation gives an approximate value of p_baseline = .0033, given the degree_sampler I started with. If p_baseline = .0033, then p_acrossblocks = .0033*1 = .0033 as well. Since there are 85*15=1275 possible edges across the two blocks, I would expect an average of .0033*1275=4.2 edges across the blocks in the entire network. Despite this, I am continually seeing the minority block being, on average, highly centralized in the overall network, with many more edges reaching from it to the other block than would be predicted. What has gone wrong here? Have I misunderstood the vertex_corr feature? Any help would be greatly appreciated. -- 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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Building graph-tool on CentOS 7
by Smith, Steven - 1004 - MITLL 28 Oct '16

28 Oct '16

The graph-tool make command on CentOS 7 fails at this point: $ cd graph-tool-2.2.35 $ ./configure --with-sparsehash-prefix=google $ make make all-recursive make[1]: Entering directory `/home/user/Downloads/graph-tool-2.2.35' Making all in src … make[4]: Entering directory `/home/user/Downloads/graph-tool-2.2.35/src/graph/topology' CXX graph_subgraph_isomorphism.lo graph_subgraph_isomorphism.cc: In instantiation of 'void get_subgraphs::operator()(const Graph1&, const Graph2*, VertexLabel, boost::any, EdgeLabel, boost::any, std::vector<VertexMap>&, size_t, bool, bool) const [with Graph1 = boost::adj_list<long unsigned int>; Graph2 = boost::adj_list<long unsigned int>; VertexLabel = boost::unchecked_vector_property_map<int, boost::typed_identity_property_map<long unsigned int> >; EdgeLabel = boost::unchecked_vector_property_map<int, boost::adj_edge_index_property_map<long unsigned int> >; VertexMap = boost::checked_vector_property_map<int, boost::typed_identity_property_map<long unsigned int> >; size_t = long unsigned int]': /usr/include/c++/4.8.2/functional:1305:50: required from '_Result std::_Bind<_Functor(_Bound_args ...)>::__call_c(std::tuple<_Args2 ...>&&, std::_Index_tuple<_Indexes ...>) const [with _Result = void; _Args = {boost::adj_list<long unsigned int>&, boost::adj_list<long unsigned int>*&, boost::unchecked_vector_property_map<int, boost::typed_identity_property_map<long unsigned int> >&, boost::unchecked_vector_property_map<int, boost::adj_edge_index_property_map<long unsigned int> >&}; long unsigned int ..._Indexes = {0ul, 1ul, 2ul, 3ul, 4ul, 5ul, 6ul, 7ul, 8ul, 9ul}; _Functor = get_subgraphs; _Bound_args = {std::_Placeholder<1>, std::_Placeholder<2>, std::_Placeholder<3>, boost::any, std::_Placeholder<4>, boost::any, std::reference_wrapper<std::vector<boost::checked_vector_property_map<int, boost::typed_identity_property_map<long unsigned int> >, std::allocator<boost::checked_vector_property_map<int, boost::typed_identity_property_map<long unsigned int> > > > >, long unsigned int, bool, bool}]’ … _descriptor>, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_:: na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_:: na, mpl_::na, mpl_::na, mpl_::na>}]' graph_subgraph_isomorphism.cc:178:56: required from here graph_subgraph_isomorphism.cc:108:114: error: 'vf2_subgraph_mono' was not declared in this scope vertices_equivalent(make_property_map_equivalent(vertex_label1, vertex_label2))); ^ … , graph_tool::ConstantPropertyMap<bool, boost::adj_list<long unsigned int>::edge_descriptor>, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na, mpl_::na>}]' graph_subgraph_isomorphism.cc:178:56: required from here graph_subgraph_isomorphism.cc:108:114: error: 'vf2_subgraph_mono' was not declared in this scope Any help fixing this would be greatly appreciated. I’m building graph-tool from the latest source, graph-tool-2.2.35.tar.bz2. CGAL is built successfully from source (there aren’t any cgal-devel packages yet in the .el7 repos), and because the .el 7 sparsehash-devel package puts its libraries in /usr/include/google, the specific ./configure command for CentOS 7 above is necessary. This runs successfully, and every compile up to graph_subgraph_isomorphism is successful.

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clique-finding algorithm
by Reckoner 27 Oct '16

27 Oct '16

Hi, Are there any maximal clique-finding algorithms implemented in graph tool? For example, https://networkx.readthedocs.io/en/stable/reference/generated/networkx.algo… Thanks!

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graph-tool on Windows Subsystem for Linux
by P-M 23 Oct '16

23 Oct '16

I am currently trying to install graph-tool on Windows Subsystem for Linux. Trying to install this I get the following error message: sudo add-apt-repository ppa:ubuntu-toolchain-r/test Cannot add PPA: 'ppa:ubuntu-toolchain-r/test'. Please check that the PPA name or format is correct. Is this expected behaviour or am I doing something wrong? WSL is only in beta so it is very possible graph-tool simply wouldn't be expected to work but I thought I'd check. Cheers, Philipp -- 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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Local Clustering Coefficient for k<=1
by P-M 23 Oct '16

23 Oct '16

How does graph-tool deal with vertices having a degree of 1 (or 0) when calculating the local clustering coefficient graph_tool.clustering.local_clustering? Given the definition used this value would be undefined for k<=1. -- 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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avg_neighbour_corr vs avg_combined_corr
by P-M 19 Oct '16

19 Oct '16

I was wondering, what is the precise difference between avg_combined_corr and avg_neighbour_corr? As far as I understand avg_neighbour_corr could for example tell me what the average degree of the vertices neighbouring a vertex of a given degree are. What in this context would avg_combined_corr tell me though? -- 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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Boost.Python.ArgumentError: Python argument types Error
by reckoner 18 Oct '16

18 Oct '16

I'm trying to build graph-tool on Ubuntu 16 using anaconda Python and I did managed to get it compiled, but I get the following error on import. return libcore.openmp_set_schedule(schedule, chunk) Boost.Python.ArgumentError: Python argument types in graph_tool.libgraph_tool_core.openmp_set_schedule(str, int) did not match C++ signature: openmp_set_schedule(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, int) Help. Thanks in advance. -- 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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How to efficiently work with large graphs up to a maximum search distance?
by Gareth Simons 14 Oct '16

14 Oct '16

I am working with large weighted undirected graphs and need to calculate a form of betweenness and closeness up to a certain maximum distance. What is the most efficient way to go about this with graph-tool? I basically need all-pairs shortest paths up to a certain maximum distance, after which I can use the property arrays to deduce the information I need. For example: - Using the provided betweenness and closeness methods will search all pairs of nodes, whereas I only need to search up to a certain distance. - Topology.shortest_distance() lets me search to a maximum distance, but only if source is not set to None. So what I am currently trying is to iterate all nodes as source ‘i’. For each ‘i’, the remaining ‘j-vertices’ are provided to the target parameter as an iterable. To avoid duplication, I pop each ‘i’ from ‘j-vertices’ as the loop progresses, so that if it has already searched from ‘i’ to ‘j’ it doesn’t later also search from ‘j’ to ‘i’. For each ‘i’ source the method therefore returns the distances to all ‘j’ as well as the predecessor map. I then use the predecessor map to generate the shortest path for each ‘i’-‘j’ pair by using the topology.shortest_path() method (with predecessor map provided so that it doesn’t recalculate the shortest paths.) There is quite a bit of looping going on and I’m wondering if there is a simpler way to calculate all-pairs shortest paths to a maximum distance while minimising duplication of shortest path searches? Thanks, Gareth

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Getting out degree for each of the nodes of a BlockState
by isukritgupta 14 Oct '16

14 Oct '16

Hi Tiago, I wanted to create a probability distribution function for the inferred network calculated by SBM (using function 'minimise_blockmodel_dl') from the original network. The object in consideration in this case is the 'BlockState' object. I couldn't find a way to do this, since there is not function to calculate the out degree of a node in the BlockState object. Can you suggest how I can achieve this? Thanks, Sukrit -- 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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