February 2017 - graph-tool - archives.skewed.de

Debian package and boost at compile-time
by Alcolo Alcolo 12 Mar '17

12 Mar '17

Hi, I have installed the package python3-graph-tool and when I use graph_tool.search.dfs_iterator I got the error: Traceback (most recent call last): File "/home/steph/bin/superGraph.py", line 160, in <module> gg.create_revdep(gg.getPackage('umda')) File "/home/steph/bin/superGraph.py", line 88, in create_revdep for e in bfs_iterator(self.graph, node): File "/usr/lib/python3/dist-packages/graph_tool/search/__init__.py", line 345, in bfs_iterator return libgraph_tool_search.bfs_search_generator(g._Graph__graph, int(source)) RuntimeError: This functionality is not available because boost::coroutine was not found at compile-time Ubuntu: 14.04 python3-graph-tool version 2.12-1 (from deb http://downloads.skewed.de/apt/trusty trusty universe) There is a way to install python3-graph-tool binaries compiled with boost ? Of course I can compile myself graph-tool, but it is not my goal.

6 26

apt-get fail to download index files
by Andy Maloney 10 Mar '17

10 Mar '17

I am trying to install graph-tool on a Trusty Ubuntu virtualbox being hosted on a Mac. I've added the requisite lines deb http://downloads.skewed.de/apt/trusty trusty main deb-src http://downloads.skewed.de/apt/trusty trusty main to my /etc/apt/sources.list, but when I run a sudo apt-get update, I get the following errors: W: Failed to fetch http://downloads.skewed.de/apt/trusty/dists/trusty/Release Unable to find expected entry 'main/source/Sources' in Release file (Wrong sources.list entry or malformed file) E: Some index files failed to download. They have been ignored, or old ones used instead. I have the main, universe, and multiverse repositories available. If any one has come across this problem before, please let me know how to fix it. Thanks. Andy_

4 4

Boost.Python.ArgumentError: Python argument types did not match C++ signature
by P-M 03 Mar '17

03 Mar '17

I have been trying to compile the recent git version of graph-tool against my anaconda python. I do this using sudo ./configure CXX="g++-5" CXXFLAGS="-std=gnu++14 -Wno-unused-local-typedefs" PYTHON="/home/pmj27/anaconda2/bin/python2.7" CAIROMM_LIBS="-L/home/pmj27/anaconda2/include/cairomm-1.0/cairomm" --enable-openmp (if I skip the sudo it won't pick up boost for reasons not quite known to me). I then run "sudo make -j20" followed by "make install". When opening python and importing the module I however get the error message Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/__init__.py", line 3323, in <module> openmp_set_schedule("static", 0) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/__init__.py", line 3320, in openmp_set_schedule 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) My first thought was that graph-tool must be linking against an incorrect version of boost. So, following the advice from other posts, I ran ldd /home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/libgraph_tool_core.so . This returns: linux-vdso.so.1 => (0x00007fffc93ce000) libpython2.7.so.1.0 => /home/pmj27/anaconda2/lib/libpython2.7.so.1.0 (0x00007fbcd05ec000) libboost_iostreams.so.1.63.0 => /home/pmj27/anaconda2/lib/libboost_iostreams.so.1.63.0 (0x00007fbcd03c4000) libboost_python.so.1.63.0 => /home/pmj27/anaconda2/lib/libboost_python.so.1.63.0 (0x00007fbcd0175000) libboost_regex.so.1.63.0 => /home/pmj27/anaconda2/lib/libboost_regex.so.1.63.0 (0x00007fbccfe5a000) libboost_coroutine.so.1.63.0 => /home/pmj27/anaconda2/lib/libboost_coroutine.so.1.63.0 (0x00007fbccfc50000) libexpat.so.1 => /home/pmj27/anaconda2/lib/libexpat.so.1 (0x00007fbccfa27000) libstdc++.so.6 => /home/pmj27/anaconda2/lib/libstdc++.so.6 (0x00007fbccf66b000) libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007fbccf33c000) libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007fbccef72000) libgcc_s.so.1 => /home/pmj27/anaconda2/lib/libgcc_s.so.1 (0x00007fbcced5b000) libgomp.so.1 => /home/pmj27/anaconda2/lib/libgomp.so.1 (0x00007fbcceb38000) libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007fbcce91a000) libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007fbcce716000) libutil.so.1 => /lib/x86_64-linux-gnu/libutil.so.1 (0x00007fbcce513000) libz.so.1 => /home/pmj27/anaconda2/lib/./libz.so.1 (0x00007fbcce2fc000) librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007fbcce0f4000) libicudata.so.56 => /home/pmj27/anaconda2/lib/./libicudata.so.56 (0x00007fbccc711000) libicui18n.so.56 => /home/pmj27/anaconda2/lib/./libicui18n.so.56 (0x00007fbccc214000) libicuuc.so.56 => /home/pmj27/anaconda2/lib/./libicuuc.so.56 (0x00007fbccbe2f000) libboost_context.so.1.63.0 => /home/pmj27/anaconda2/lib/./libboost_context.so.1.63.0 (0x00007fbccbc26000) libboost_thread.so.1.63.0 => /home/pmj27/anaconda2/lib/./libboost_thread.so.1.63.0 (0x00007fbccba04000) libboost_chrono.so.1.63.0 => /home/pmj27/anaconda2/lib/./libboost_chrono.so.1.63.0 (0x00007fbccb7fd000) libboost_system.so.1.63.0 => /home/pmj27/anaconda2/lib/./libboost_system.so.1.63.0 (0x00007fbccb5fa000) /lib64/ld-linux-x86-64.so.2 (0x000055cf9c8bc000) As far as I can tell all boost libraries are based on the anaconda boost libraries. Does anybody have any ideas what might be going wrong? Best, 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.

3 30

Inference - Aborted (core dumped)
by P-M 27 Feb '17

27 Feb '17

Hello Tiago, I have been running a piece of code to give me some idea how long it takes me to calculate edge likelihoods as I add vertices and edges to my network. This works for a while and then it all crashes with a rather nasty looking error message. The code is very similar to what I have posted here <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> so I won't paste it here again in the interest of brevity, though the entire script can be found here ( edge_prediction_stats.py <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> ). When my script gets to a certain point in the loop it crashes with a long error message. (I have observed this when the code reaches the filtered network corresponding to pub_year=1870 and pub_year=1880). I presume this appears to happen when evaluating `state = gt.minimize_nested_blockmodel_dl(g, deg_corr=True)` as far as I can tell by the screen output. The error message that I then get is posted below. Is this caused by an issue in graph-tool? I am running Ubuntu 16.04, running gcc -v returns gcc version 4.8.5 (GCC) though GCC 5.4.0-6ubuntu1~16.04.4 is also installed and my graph-tool version is 2.20dev (commit 01432d60, Sun Jan 15 19:54:52 2017 +0000). *** Error in `python': double free or corruption (out): 0x00000000033db2c0 *** ======= Backtrace: ========= /lib/x86_64-linux-gnu/libc.so.6(+0x777e5)[0x7ff250de37e5] /lib/x86_64-linux-gnu/libc.so.6(+0x7fe0a)[0x7ff250debe0a] /lib/x86_64-linux-gnu/libc.so.6(cfree+0x4c)[0x7ff250def98c] /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/libgraph_tool_core.so(+0x1bf83b1)[0x7ff2405333b1] /usr/lib/x86_64-linux-gnu/libboost_python-py27.so.1.58.0(+0x2547c)[0x7ff23e4eb47c] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0xae435)[0x7ff251b10435] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0x8ecab)[0x7ff251af0cab] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0xae4f1)[0x7ff251b104f1] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0x8ecab)[0x7ff251af0cab] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0xae4f1)[0x7ff251b104f1] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0x7f08f)[0x7ff251ae108f] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0x8ecab)[0x7ff251af0cab] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0xae4f1)[0x7ff251b104f1] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(+0x8cbe7)[0x7ff251aeebe7] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(PyDict_SetItem+0x8c)[0x7ff251af203c] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x6ae0)[0x7ff251b5d010] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x89e)[0x7ff251b5fa2e] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCode+0x32)[0x7ff251b5fb42] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(PyRun_FileExFlags+0xb0)[0x7ff251b80050] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(PyRun_SimpleFileExFlags+0xef)[0x7ff251b8022f] /home/pmj27/anaconda/bin/../lib/libpython2.7.so.1.0(Py_Main+0xca4)[0x7ff251b95b74] /lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf0)[0x7ff250d8c830] python[0x400649] ======= Memory map: ======== 00400000-00401000 r-xp 00000000 08:11 87037196 /home/pmj27/anaconda/bin/python2.7 00600000-00601000 rw-p 00000000 08:11 87037196 /home/pmj27/anaconda/bin/python2.7 00f8f000-3110f000 rw-p 00000000 00:00 0 [heap] 7ff174000000-7ff174021000 rw-p 00000000 00:00 0 7ff174021000-7ff178000000 ---p 00000000 00:00 0 7ff17bbe7000-7ff184000000 rw-p 00000000 00:00 0 7ff184000000-7ff184021000 rw-p 00000000 00:00 0 7ff184021000-7ff188000000 ---p 00000000 00:00 0 7ff188000000-7ff188021000 rw-p 00000000 00:00 0 7ff188021000-7ff18c000000 ---p 00000000 00:00 0 7ff18c000000-7ff18c021000 rw-p 00000000 00:00 0 7ff18c021000-7ff190000000 ---p 00000000 00:00 0 7ff190000000-7ff190021000 rw-p 00000000 00:00 0 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/home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/util/libgraph_tool_util.so 7ff226817000-7ff226a16000 ---p 000eb000 08:11 115217209 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/util/libgraph_tool_util.so 7ff226a16000-7ff226a1a000 r--p 000ea000 08:11 115217209 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/util/libgraph_tool_util.so 7ff226a1a000-7ff226a1b000 rw-p 000ee000 08:11 115217209 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/util/libgraph_tool_util.so 7ff226a1b000-7ff2276bc000 r-xp 00000000 08:11 114962515 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/search/libgraph_tool_search.so 7ff2276bc000-7ff2278bb000 ---p 00ca1000 08:11 114962515 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/search/libgraph_tool_search.so 7ff2278bb000-7ff2278cc000 r--p 00ca0000 08:11 114962515 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/search/libgraph_tool_search.so 7ff2278cc000-7ff2278d3000 rw-p 00cb1000 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7ff2349b9000-7ff234bb9000 ---p 00714000 08:11 88477126 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/flow/libgraph_tool_flow.so 7ff234bb9000-7ff234bbb000 r--p 00714000 08:11 88477126 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/flow/libgraph_tool_flow.so 7ff234bbb000-7ff234bbe000 rw-p 00716000 08:11 88477126 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/flow/libgraph_tool_flow.so 7ff234bbe000-7ff234d7b000 r-xp 00000000 08:11 115086279 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/stats/libgraph_tool_stats.so 7ff234d7b000-7ff234f7a000 ---p 001bd000 08:11 115086279 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/stats/libgraph_tool_stats.so 7ff234f7a000-7ff234f7d000 r--p 001bc000 08:11 115086279 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/stats/libgraph_tool_stats.so 7ff234f7d000-7ff234f7f000 rw-p 001bf000 08:11 115086279 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/stats/libgraph_tool_stats.so 7ff234f7f000-7ff2388d3000 r-xp 00000000 08:11 115086288 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/topology/libgraph_tool_topology.so 7ff2388d3000-7ff238ad2000 ---p 03954000 08:11 115086288 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/topology/libgraph_tool_topology.so 7ff238ad2000-7ff238ada000 r--p 03953000 08:11 115086288 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/topology/libgraph_tool_topology.so 7ff238ada000-7ff238b05000 rw-p 0395b000 08:11 115086288 /home/pmj27/anaconda/lib/python2.7/site-packages/graph_tool/topology/libgraph_tool_topology.so 7ff238b05000-7ff238b06000 rw-p 00000000 00:00 0 Aborted (core dumped) -- 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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Some clarifications regarding directness
by bloodymeli 23 Feb '17

23 Feb '17

Hi, Consider the following GraphML file (attached). According to the GraphML file, it represents an undirected graph. Therefore, I would expect that as I set it to directed graph: gtGraph=gt.load_graph("yeast.graphml") gtGraph.set_directed(1) I would obtain two directed edges for every undirected edge. In particular, the in degree of every node should be equal to the out degree. However, this is not the case, for example: v=gtGraph.vertex(1834) v.in_degree() Out[3]: 5 v.out_degree() Out[4]: 2 I'm a bit puzzled. A) Is the source file corrupted? B) When I set the directedness flag to 1, am I guaranteed that every undirected edge would be converted to two directed edges? If not, how can I perform this operation (A = A + A', assuming the adjacency matrix is triangular) or validate it? yeast.graphml <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> -- 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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Questions about output of "history" of graph_tool.inference.mcmc_equilibrate
by P-M 21 Feb '17

21 Feb '17

I have just run the following snippet of code: mcmc_args=dict(parallel = True,niter=10) history = gt.mcmc_equilibrate(state, wait=1000, history=True,mcmc_args=mcmc_args) with open('history1.pkl','wb') as his1_pkl: pickle.dump(history,his1_pkl,-1) According to the manual history is a "list of tuples of the form (iteration, entropy)". When unpickling it however I get a list of length 2000. Each element in the list is another list of length two containing `nan` as first entry and then a single-digit integer as second entry. A couple of questions: 1) I would expect a tuple, not a list for each entry in the list. Is the manual wrong or is the code wrong? Or did I do something wrong? 2) Why am I receiving `nan` rather than a value for "iteration" as first entry of my list? 3) Is there a particular reason why the length of the list is precisely 2000 in this case? (Obviously there is, I just haven't quite figured it out yet.) Best, 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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mcmc_equilibrate - Segmentation fault (core dumped)
by P-M 21 Feb '17

21 Feb '17

I am trying to run the following snippet of code: import graph_tool.all as gt import timeit, os import cPickle as pickle import numpy as np g = gt.load_graph('graph_no_multi_reac_type.gt') gt.remove_parallel_edges(g) print 'minimising state' start = timeit.default_timer() state = gt.minimize_nested_blockmodel_dl(g, deg_corr=True,verbose=False) duration = timeit.default_timer()-start print 'duration: ', duration state = state.copy(sampling=True) with open('state_n_dc.pkl','wb') as state_pkl: pickle.dump(state,state_pkl,-1) print 'equilibrating Markov chain' start = timeit.default_timer() mcmc_args = {} mcmc_args=dict(parallel = True,niter=10) history = gt.mcmc_equilibrate(state, wait=1000, history=True,mcmc_args=mcmc_args) duration = timeit.default_timer()-start print 'duration: ', duration with open('history1.pkl','wb') as his1_pkl: pickle.dump(history,his1_pkl,-1) On the attached graph ( graph_no_multi_reac_type.gt <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> ). I, however, get an error message stating "Segmentation fault (core dumped)". To be precise my screen output is: minimising state duration: 991.349531889 equilibrating Markov chain Segmentation fault (core dumped) So the error seems to arise during `history = gt.mcmc_equilibrate(state, wait=1000, history=True,mcmc_args=mcmc_args)`. Why might that be? I have observed the issue both with `2.20dev (commit 01432d60, Sun Jan 15 19:54:52 2017 +0000)` and `2.20 (commit f6ef9990, Fri Jan 27 16:40:08 2017 +0000)`. Best, 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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Two ways of calculating the degree sequence
by gogurt 20 Feb '17

20 Feb '17

So I'm trying to calculate the degree sequence of G, an undirected, connected simple graph. As far as I see it, there are two ways to do this. Iterate over all the vertices, or sum the rows of the adjacency matrix. So: def degree_sequence1(G): degs = [] for v in G.vertices(): degs.append(v.out_degree() + v.in_degree()) degs.sort() return degs def degree_sequence2(G): mat = gt.adjacency(G) degs = np.squeeze(np.asarray(mat.sum(axis=0))) degs.sort() return degs The first way definitely works. But when I try to use the second method, I find that even if I run this code on a connected network I get zeroes in my degree sequence. Which shouldn't be possible if the graph is connected. So I know that I'm understanding something wrong here. Can somebody point out where I went wrong here? Thanks! -- 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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[Centrality Measures]
by Thais GOMES ALMEIDA 20 Feb '17

20 Feb '17

Hi Tiago, I'm working with some centrality measures provide by graph_tool and I have some questions: *Does the 'trust_map' parameter of the eigentrust centrality function refer to the edges' weight?* In the example present in the docs, it was used the edges' weight as value to 'trust_map', but in the parameters' description was said that this parameter refers to 'Edge property map with the values of trust associated with each edge. The values must lie in the range [0,1]." *Why are my values of authority and hub centrality equal?* I'm getting the same values for authority and hub centrality. ex: v_id hub authority 1, 0.401326450573, 0.401326450573 2, 0.614525497348, 0.614525497348 ... *Code:g.vp.authority = g.new_vertex_property("double")g.vp.hub = g.new_vertex_property("double")eig, g.vp.authority, g.vp.hub = graph_tool.centrality.hits(g, weight = g.ep.edge_weight)* Thais Almeida.

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dfs_search question
by Tom 17 Feb '17

17 Feb '17

Hi, I trying to use dfs_search, and after digging through the sources, it appears that only dfs_search accepting a start vertex is exposed by the library. However, the BGL also has an overload for depth_first_search which doesn't need a vertex and traverses *all* vertices. (In addition to the two overloads, there is also a separate interface depth_first_visit(), which does exactly what "dfs_search" does.) Any chance of exposing the versions of [db]fs_search which don't need a start vertex, please? Many thanks, Tom -- 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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