graph-tool August 2019

graph-tool@skewed.de

10 participants
17 discussions

Getting a property map from a vector property map
by Mikuláš Poul 30 Aug '19

30 Aug '19

Hi! For the project I'm working on I need to calculate distances on a graph from a couple of vertices to all other vertices. The topology.shortest_distance can only do either from all vertices or from a single one, and to save time I'd like this to run in parallel, so I set out to implement this in C++. I took inspiration from graph-tool's implementation of shortest_distance for pair-wise distances in unweighted graphs (running BFS from all vertices in parallel), and managed to modify that to only run from some vertices. However I ran into a problem trying to do the same for weighted graphs. I think the problem I have is that when passing the vector for distances to all vertices it is supposed to be a property map and not a vector, but I cannot figure out how to get a 1d property map from a 2d property map on a C++ level, basically I pass a vector<double> property map to my function but I need to pass a simple double property map to the dijskstra function from boost. Could anyone please help me point to how would I do that? Or is my approach wrong completely? What most confuses me that the same approach works fine for breadth_first_search. The errors I'm getting in compilation: /usr/include/boost/graph/dijkstra_shortest_paths_no_color_map.hpp:43:63: error: no type named ‘value_type’ in ‘struct boost::property_traits<std::vector<double> >’ 43 | typedef typename property_traits<DistanceMap>::value_type Distance; /usr/include/boost/pending/indirect_cmp.hpp:32:78: error: no type named ‘value_type’ in ‘struct boost::property_traits<std::vector<double> >’ 32 | typedef typename boost::property_traits<ReadablePropertyMap>::value_type T; | ^ /usr/include/boost/pending/indirect_cmp.hpp:33:76: error: no type named ‘key_type’ in ‘struct boost::property_traits<std::vector<double> >’ 33 | typedef typename boost::property_traits<ReadablePropertyMap>::key_type K; Thank you, Mikuláš

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Graph views via property maps
by Lietz, Haiko 29 Aug '19

29 Aug '19

Hi all, gt allows creating graph views where vertices and/or edges are filtered out. The principle is described in the documentation: "Vertices or edges which are to be filtered should be marked with a PropertyMap with value type bool, and then set with set_vertex_filter() or set_edge_filter() methods. By default, vertex or edges with value '1' are kept in the graphs, and those with value '0' are filtered out." (https://graph-tool.skewed.de/static/doc/quickstart.html#graph-filtering) Given a layered graph, where layers are coded via an edge property, I want to draw the graphs layer by layer. This is an example graph: from graph_tool.all import * import numpy as np import pandas as pd # data edge_list = pd.DataFrame(np.array([[0, 1, 0], [1, 2, 1], [2, 0, 2]]), columns=['i', 'j', 'layer']) # create graph g = Graph(directed=False) ep_layer = g.new_edge_property('int') g.add_edge_list(edge_list.values, eprops=[ep_layer]) g.edge_properties['layer'] = ep_layer # draw graph with edge colors showing the layers graph_draw(g, edge_color=g.ep.layer) It is possible to draw a single layer (in this example layer 0) in this complicated way: # set layer to be drawn layer = 0 # create graph view ep_filter = g.new_edge_property('bool') for i in range(0, len(edge_list)): e = g.edge(edge_list['i'][i], edge_list['j'][i]) if edge_list['layer'][i] == layer: ep_filter[e] = True else: ep_filter[e] = False g_filter = GraphView(g, efilt=ep_filter) # draw filtered graph graph_draw(g_filter, edge_color=g.ep.layer) If I proceed this way I will also have to create a vertex property map to filter unused vertices and do these steps for all layers I want to draw. But isn't there a more elegant way - preferably handling vertices and edges in the same step? Many thanks and best wishes Haiko

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Vertex position in property map
by Lietz, Haiko 28 Aug '19

28 Aug '19

Hi all, I'm trying to story vertex positions in a property map. Why doesn't it work the way I try? from graph_tool.all import * import numpy as np g = Graph() pos = g.new_vertex_property('object') for i in range(1, 3): v = g.add_vertex() pos[v] = np.array([i, i]) graph_draw(g, pos=pos) Thanks Haiko

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Can I use graph-tool for analyzing temporal network?
by Sara Ansari 23 Aug '19

23 Aug '19

Hello all, I'm going to choose and install a network tool for analyzing a kind of temporal weighted and directed complex network. is graph-tool suitable for it? if no, can any one suggest a right tool for it? Best regards, Sara

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Plotting individual hierarchy of nested SBM
by lenarpooo 15 Aug '19

15 Aug '19

Dear Tiago, Hi! I'm trying to plot the individual hierarchies of a nested SBM, is it possible to inherit the node color and use edge width to represent the number of edges, as in the second image? <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> Thanks! Best wishes, Yingjie -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

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Build error
by skx300 15 Aug '19

15 Aug '19

I am trying to build graph-tool using "make -j8" I have following error, appreciated for any help. /usr/local/include/boost/python/detail/invoke.hpp: In instantiation of ‘PyObject* boost::python::detail::invoke(boost::python::detail::invoke_tag_<false, false>, const RC&, F&, AC0&) [with RC = boost::python::to_python_indirect<const std::type_info&, boost::python::detail::make_reference_holder>; F = const std::type_info& (boost::any::*)() const noexcept; AC0 = boost::python::arg_from_python<boost::any&>; PyObject = _object]’: /usr/local/include/boost/python/detail/caller.hpp:218:46: required from ‘PyObject* boost::python::detail::caller_arity<1>::impl<F, Policies, Sig>::operator()(PyObject*, PyObject*) [with F = const std::type_info& (boost::any::*)() const noexcept; Policies = boost::python::return_value_policy<boost::python::reference_existing_object>; Sig = boost::mpl::vector2<const std::type_info&, boost::any&>; PyObject = _object]’ /usr/local/include/boost/python/object/py_function.hpp:38:33: required from ‘PyObject* boost::python::objects::caller_py_function_impl<Caller>::operator()(PyObject*, PyObject*) [with Caller = boost::python::detail::caller<const std::type_info& (boost::any::*)() const noexcept, boost::python::return_value_policy<boost::python::reference_existing_object>, boost::mpl::vector2<const std::type_info&, boost::any&> >; PyObject = _object]’ graph_bind.cc:588:1: required from here */usr/local/include/boost/python/detail/invoke.hpp:75:16: error: must use ‘.*’ or ‘->*’ to call pointer-to-member function in ‘f (...)’, e.g. ‘(... ->* f) (...)’ return rc(f( BOOST_PP_ENUM_BINARY_PARAMS_Z(1, N, ac, () BOOST_PP_INTERCEPT) ));* ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/include/boost/python/detail/invoke.hpp: In instantiation of ‘PyObject* boost::python::detail::invoke(boost::python::detail::invoke_tag_<false, false>, const RC&, F&, AC0&) [with RC = boost::python::to_python_value<const long unsigned int&>; F = long unsigned int (std::type_info::*)() const noexcept; AC0 = boost::python::arg_from_python<std::type_info&>; PyObject = _object]’: /usr/local/include/boost/python/detail/caller.hpp:218:46: required from ‘PyObject* boost::python::detail::caller_arity<1>::impl<F, Policies, Sig>::operator()(PyObject*, PyObject*) [with F = long unsigned int (std::type_info::*)() const noexcept; Policies = boost::python::default_call_policies; Sig = boost::mpl::vector2<long unsigned int, std::type_info&>; PyObject = _object]’ /usr/local/include/boost/python/object/py_function.hpp:38:33: required from ‘PyObject* boost::python::objects::caller_py_function_impl<Caller>::operator()(PyObject*, PyObject*) [with Caller = boost::python::detail::caller<long unsigned int (std::type_info::*)() const noexcept, boost::python::default_call_policies, boost::mpl::vector2<long unsigned int, std::type_info&> >; PyObject = _object]’ graph_bind.cc:588:1: required from here /usr/local/include/boost/python/detail/invoke.hpp:75:16: error: must use ‘.*’ or ‘->*’ to call pointer-to-member function in ‘f (...)’, e.g. ‘(... ->* f) (...)’ /usr/local/include/boost/python/detail/invoke.hpp: In instantiation of ‘PyObject* boost::python::detail::invoke(boost::python::detail::invoke_tag_<false, false>, const RC&, F&, AC0&) [with RC = boost::python::to_python_value<const char* const&>; F = const char* (std::type_info::*)() const noexcept; AC0 = boost::python::arg_from_python<std::type_info&>; PyObject = _object]’: /usr/local/include/boost/python/detail/caller.hpp:218:46: required from ‘PyObject* boost::python::detail::caller_arity<1>::impl<F, Policies, Sig>::operator()(PyObject*, PyObject*) [with F = const char* (std::type_info::*)() const noexcept; Policies = boost::python::default_call_policies; Sig = boost::mpl::vector2<const char*, std::type_info&>; PyObject = _object]’ /usr/local/include/boost/python/object/py_function.hpp:38:33: required from ‘PyObject* boost::python::objects::caller_py_function_impl<Caller>::operator()(PyObject*, PyObject*) [with Caller = boost::python::detail::caller<const char* (std::type_info::*)() const noexcept, boost::python::default_call_policies, boost::mpl::vector2<const char*, std::type_info&> >; PyObject = _object]’ graph_bind.cc:588:1: required from here /usr/local/include/boost/python/detail/invoke.hpp:75:16: error: must use ‘.*’ or ‘->*’ to call pointer-to-member function in ‘f (...)’, e.g. ‘(... ->* f) (...)’ /usr/local/include/boost/python/detail/invoke.hpp: In instantiation of ‘PyObject* boost::python::detail::invoke(boost::python::detail::invoke_tag_<false, false>, const RC&, F&, AC0&) [with RC = boost::python::to_python_value<const bool&>; F = bool (boost::any::*)() const noexcept; AC0 = boost::python::arg_from_python<boost::any&>; PyObject = _object]’: /usr/local/include/boost/python/detail/caller.hpp:218:46: required from ‘PyObject* boost::python::detail::caller_arity<1>::impl<F, Policies, Sig>::operator()(PyObject*, PyObject*) [with F = bool (boost::any::*)() const noexcept; Policies = boost::python::default_call_policies; Sig = boost::mpl::vector2<bool, boost::any&>; PyObject = _object]’ /usr/local/include/boost/python/object/py_function.hpp:38:33: required from ‘PyObject* boost::python::objects::caller_py_function_impl<Caller>::operator()(PyObject*, PyObject*) [with Caller = boost::python::detail::caller<bool (boost::any::*)() const noexcept, boost::python::default_call_policies, boost::mpl::vector2<bool, boost::any&> >; PyObject = _object]’ graph_bind.cc:588:1: required from here /usr/local/include/boost/python/detail/invoke.hpp:75:16: error: must use ‘.*’ or ‘->*’ to call pointer-to-member function in ‘f (...)’, e.g. ‘(... ->* f) (...)’ make[4]: *** [graph_bind.lo] Error 1 make[4]: *** Waiting for unfinished jobs.... -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

2 1

Finding the ground state
by Terry 06 Aug '19

06 Aug '19

Dear Tiago, Thank you very much for creating and maintaining this awesome package! I really enjoy using it. I have a question regarding finding the NestedBlockState with minimum description length. I currently have a very large bipartite network with approximately 300k edges and 20k nodes, say, g. 1. founding the initial state using an agglomerative heuristic. state = gt.minimize_nested_blockmodel_dl(g, deg_corr=True) 2. equilibrate the Markov chain at beta = 1 bs = state.get_bs() bs += [np.zeros(1)] * (nL - len(bs)) state = state.copy(bs=bs, sampling=True) gt.mcmc_equilibrate(state, wait=1000, epsilon=1e-6, mcmc_args=dict(niter=10)) 3. equilibrate the Markov chain at beta = numpy.inf gt.mcmc_equilibrate(state, wait=1000, epsilon=1e-6, mcmc_args=dict(beta = numpy.inf, niter=10)) 4. founding the state with minimum description length gt.mcmc_equilibrate(state, wait=200, epsilon=1e-6, mcmc_args=dict(beta = numpy.inf, niter=10), callback = finding_minState) where finding_minState is a function that checks whether the state is the minimum MDL found so far. 5. to save the state to pickle files, I use the following to construct a new NestedBlockState minState = gt.NestedBlockState(g, bs = state.get_bs(), state_args = state.state_args) where state_args is some partition prior imposed on the graph. In the above, to speed up the inference, I chose epsilon to be 1e-6 or even 1e-2. I know I can also speed up the program by passing multiflip=True, but since I ran the program on the school server. It currently only have 2.27 available. I run the above code for multiple times to study the computational cost and convergence behavior. For each run, I also calculate the average description length over MCMC sweeps. My question is: Is the above approach correct to find the state with minimum description length? Looking forward to your reply. Best, Terry -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/

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graph-tool August 2019