graph-tool April 2017

graph-tool@skewed.de

10 participants
18 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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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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FW: Graphtool: Finding the paths that the maximum flow algorithm produces
by Hobé Alex 25 Jun '18

25 Jun '18

Hi Tiago and everyone else on the list Thank you for your swift reply. The attached png is one example of a max flow calculation result. The flow is limited in four places in this graph. I would like to extract the order of the edges in the four paths I drew. The shortest path solution you described corresponds to path 3 in the drawing. all_shortest_paths gives my path 3 and another completely different path before crashing with a memoryError. Looking forward to hearing from you. Best, Alex ________________________________________ From: Tiago de Paula Peixoto [tiago(a)skewed.de] Sent: Thursday, March 09, 2017 18:43 To: Hobé Alex Subject: Re: Graphtool: Finding the paths that the maximum flow algorithm produces Hi Hobé, I'm not sure I understand what you want. Any path containing edges with positive flow is a "flow path". There are many of them. Which one do you want? If you just want _some_ path, just filter out the edges with zero flow and get the shortest path. But there are many other ways to proceed... Best, Tiago PS. There is a mailing list of the graph-tool project, where questions like this can be posted. It is better to use the list than to ask me directly, since it builds a repository of questions others can consult, and other people can help you as well. On 09.03.2017 17:04, Hobé Alex wrote: > Dear Mr. de Paula Peixoto > > I am using the python graphtool for my master thesis and am enjoying the > beautiful pictures it produces. > When computing the maximum flow I would like to use other edge properties > along the computed path for further calculations. > I am therefore looking for a way to find an array, which contains the edges > along a flow path, similar to the shortest_path result. > I looked through all the pages of the online tutorial, learnt a couple of > new tricks, but haven't found a way to solve this. > > I would be very thankful for any assistance you would be able to provide and > I look forward to hearing from you. > Best wishes, > > Alex Hobé -- Tiago de Paula Peixoto <tiago(a)skewed.de>

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from graph_tool.all import * gives ImportError
by vineesh vs 21 Jun '18

21 Jun '18

I tried the following command in Python and ipython prompt (2.7 version) --------------------------------------------------------------------------- In [1]: from graph_tool.all import * --------------------------------------------------------------------------- Its giving the following error. How can we solve it? --------------------------------------------------------------------------- ImportError Traceback (most recent call last) <ipython-input-1-100bbe2bc9d9> in <module>() ----> 1 from graph_tool.all import * /usr/lib/python2.7/dist-packages/graph_tool/__init__.py in <module>() 103 104 from .dl_import import * --> 105 dl_import("from . import libgraph_tool_core as libcore") 106 __version__ = libcore.mod_info().version 107 /usr/lib/python2.7/dist-packages/graph_tool/dl_import.pyc in dl_import(import_expr) 55 56 try: ---> 57 exec(import_expr, local_dict, global_dict) 58 finally: 59 sys.setdlopenflags(orig_dlopen_flags) # reset it to normal case to <string> in <module>() ImportError: /usr/lib/python2.7/dist-packages/graph_tool/libgraph_tool_core.so: undefined symbol: _ZN5boost9iostreams4zlib6finishE --------------------------------------------------------------------------- Thanks

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get 500 error when I try to pull graph tool from git repo
by Reckoner 18 Jul '17

18 Jul '17

am I the only one getting this error? Thanks!

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Invalid vertex index error in get_edges_prob using filtered graph
by P-M 26 May '17

26 May '17

Hello, I am running a script to calculate the likelihoods of certain edges being missing edges on a filtered graph (I filter out some edges to see whether the filtered edges are more likely to be missing than a bunch of other, random edges that I also calculate the likelihood for). When running this I however get an error telling me the following: Traceback (most recent call last): File "edge_prediction_stats_ex_+_rand_es.py", line 122, in <module> callback=collect_edge_probs,history=True) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/mcmc.py", line 155, in mcmc_equilibrate extra = callback(state) File "edge_prediction_stats_ex_+_rand_es.py", line 15, in collect_edge_probs p = s.get_edges_prob([chosen_test_edges[i]], entropy_args=dict(partition_dl=False)) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/nested_blockmodel.py", line 345, in get_edges_prob L += lstate.get_edges_prob(missing, spurious, entropy_args=eargs) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/blockmodel.py", line 1147, in get_edges_prob pos[u] = self.b[u] File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/__init__.py", line 446, in __getitem__ k = self.__key_convert(k) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/__init__.py", line 424, in __key_convert key = self.__g().vertex(key) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/__init__.py", line 1760, in vertex raise ValueError("Invalid vertex index: %d" % int(i)) ValueError: Invalid vertex index: 2 I have told python to return the vertex IDs of the edge that is raising the error and have checked manually in the filtered graph whether these vertex IDs are valid IDs and they are. Can anybody reproduce this error? Tiago, is this in any way related to the errors I have been observing with filtered graphs in the past? I am running version 2.23dev (commit 87abb56d, Wed Apr 5 15:21:41 2017 +0100) which I think should be the latest version on Ubuntu 16.04 and have compiled it with GCC 5.4.0. Here is the network used ( graph_no_multi_clean.zip <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> ) and here is the script used ( edge_prediction_stats_ex_+_rand_es.py <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com…> ) to produce the error. -- 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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Generating planar graph of amino acids based
by Matyas, Csongor 02 May '17

02 May '17

Hi everyone I'm trying to generate a planar graph of amino acids, based on their properties, something like this: http://www.russelllab.org/aas/other_images/lb3.gif I want them to be something like this (I know there is a solution already, but this is just an example at the moment, if I can't solve this problem, I can't move forward). Some amino acids should be close to each other, because they are in the same group. The problem is, that they can belong to multiple groups, so just grouping doesn't work. I've seen the fruchterman_reingold_layout and it's two parameters: *a* : float (optional, default:) Attracting force between adjacent vertices. *r* : float (optional, default: 1.0) Repulsive force between vertices. The problem is, that I think I would need the opposite. Repulsive force between the connected vertices, and attractive force between the vertices in general. The question is, can I do that somehow? Or is there another way? This is something I've done to play with until now, attached Thank you Csongor

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graph-tool April 2017