Re: [igraph] Python-igraph: Possible memory leak in GraphBase.get_all_shortest_paths()
Hi, I have tested it now on a Mac with the following code: #!/usr/bin/env python from psutil import Process from igraph import Graph import gc self = Process() g = Graph.GRG(400, 0.1) for i in xrange(100): sps = g.get_all_shortest_paths(0) del sps gc.collect() mem_info = self.memory_info() print i, mem_info.rss, mem_info.vms The memory usage seems pretty stable to me; these are the results (iteration count, resident set size, virtual memory size): 0 23523328 2532331520 1 24576000 2535403520 2 24584192 2535411712 3 23535616 2534363136 4 24584192 2535411712 5 25657344 2536476672 6 23560192 2534379520 7 23564288 2534379520 8 24788992 2534354944 9 25837568 2535403520 10 23744512 2533306368 11 24698880 259136 12 23773184 259136 13 24817664 2534387712 14 26710016 2535436288 15 23773184 259136 16 24825856 2534387712 17 24825856 2534387712 18 24821760 2534387712 19 23773184 259136 20 24821760 2534387712 So I don't think there's a leak there, at least not on Mac OS X. If you can send me a small, self-contained program, equipped with a similar instrumentation (see the code above) that seems to leak on your machine, that would be great. (Note that you'll need to install psutil from pip). All the best, T. On Mon, Dec 7, 2015 at 9:29 AM, wrote: > Hi, > > I am developing a network analysis tool for evolutionary biology, which uses > python-igraph. It appears that repeatedly calling get_all_shortest_paths() > on the graph results in the consumption of available memory quite quickly. I > have narrowed the memory leak down to get_all_shortest_paths() by using a > memory profiler. > > I was using python-igraph-0.6 earlier and then upgraded to > python-igraph-0.7.1.post6. The upgrade did not solve the problem. The OS is > Ubuntu 14.04 LTS, with python 2.7.6. > > Has someone else come across the same issue? > > Regards, > /Fahad > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help > ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] Need help with plotting
Thank you Sir for the tip. I will get back to you after testing.
Raj
On Mon, Dec 7, 2015 at 8:42 AM, Gábor Csárdi wrote:
> I guess the problem is that edge.betweenness.community interprets edge
> weights the opposite way. Small numbers mean short links, so strong
> connections. Use 1 / weights, maybe?
>
> Gabor
>
> On Mon, Dec 7, 2015 at 4:39 PM, Raj Balakrishnan wrote:
>
>> Dear Gabor,
>>
>> Isn't the example I have included enough?
>>
>> Thanks,
>>
>> Raj
>>
>> Raj Balakrishnan
>>
>> Sent from my mobile phone
>> --
>> From: Gábor Csárdi
>> Sent: 07-12-2015 07:26
>> To: Help for igraph users
>> Subject: Re: [igraph] Need help with plotting
>>
>> I am not sure what is going on here? Are you saying
>> that edge.betweenness.community is buggy? Possibly, but then please show us
>> why on some small example?
>>
>> Gabor
>>
>> On Mon, Dec 7, 2015 at 2:40 PM, Rk Lata wrote:
>>
>>> Hi there,
>>>
>>> I am trying to plot self and cross reactions of bunch of proteins. I
>>> have three states: Positive=1, Negative=0 and Partial=0.5. When I plot the
>>> values in the matrix using the code below, I get the plot shown in Fig A. I
>>> am expecting a plot as in Fig B. (Please see the Figures attached).
>>> What should I do to make the weakly self reacting proteins (c & d)
>>> appear as a separate group and not in group with other strongly self
>>> reacting proteins.
>>>
>>>
>>> abcdefghia1b01100c000.500d.50e00000f1110
>>> 0g11100h00011i00011
>>>
>>> m <- as.matrix(read.csv("C:/Users/balakrr1/Desktop/csv/n3.csv",
>>> header=TRUE, sep = ",", row.names = 1))
>>> g = graph.adjacency(m,mode="undirected",weighted=TRUE)
>>> g=simplify(g, remove.loops=TRUE)
>>> eb=edge.betweenness.community(g,directed=FALSE,weights=E(g)$weight)
>>> fr=layout.fruchterman.reingold(g)
>>> plot(eb,g,layout=fr,edge.width=E(g)$weight,main="Edge Betweenness")
>>>
>>>
>>> Thanks,
>>>
>>> Raj
>>>
>>>
>>> ___
>>> igraph-help mailing list
>>> igraph-help@nongnu.org
>>> https://lists.nongnu.org/mailman/listinfo/igraph-help
>>>
>>>
>>
>> ___
>> igraph-help mailing list
>> igraph-help@nongnu.org
>> https://lists.nongnu.org/mailman/listinfo/igraph-help
>>
>>
>
> ___
> igraph-help mailing list
> igraph-help@nongnu.org
> https://lists.nongnu.org/mailman/listinfo/igraph-help
>
>
___
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Re: [igraph] Need help with plotting
I guess the problem is that edge.betweenness.community interprets edge
weights the opposite way. Small numbers mean short links, so strong
connections. Use 1 / weights, maybe?
Gabor
On Mon, Dec 7, 2015 at 4:39 PM, Raj Balakrishnan wrote:
> Dear Gabor,
>
> Isn't the example I have included enough?
>
> Thanks,
>
> Raj
>
> Raj Balakrishnan
>
> Sent from my mobile phone
> --
> From: Gábor Csárdi
> Sent: 07-12-2015 07:26
> To: Help for igraph users
> Subject: Re: [igraph] Need help with plotting
>
> I am not sure what is going on here? Are you saying
> that edge.betweenness.community is buggy? Possibly, but then please show us
> why on some small example?
>
> Gabor
>
> On Mon, Dec 7, 2015 at 2:40 PM, Rk Lata wrote:
>
>> Hi there,
>>
>> I am trying to plot self and cross reactions of bunch of proteins. I have
>> three states: Positive=1, Negative=0 and Partial=0.5. When I plot the
>> values in the matrix using the code below, I get the plot shown in Fig A. I
>> am expecting a plot as in Fig B. (Please see the Figures attached).
>> What should I do to make the weakly self reacting proteins (c & d) appear
>> as a separate group and not in group with other strongly self reacting
>> proteins.
>>
>>
>> abcdefghia1b01100c000.500d.50e00000f11100
>> g11100h00011i00011
>>
>> m <- as.matrix(read.csv("C:/Users/balakrr1/Desktop/csv/n3.csv",
>> header=TRUE, sep = ",", row.names = 1))
>> g = graph.adjacency(m,mode="undirected",weighted=TRUE)
>> g=simplify(g, remove.loops=TRUE)
>> eb=edge.betweenness.community(g,directed=FALSE,weights=E(g)$weight)
>> fr=layout.fruchterman.reingold(g)
>> plot(eb,g,layout=fr,edge.width=E(g)$weight,main="Edge Betweenness")
>>
>>
>> Thanks,
>>
>> Raj
>>
>>
>> ___
>> igraph-help mailing list
>> igraph-help@nongnu.org
>> https://lists.nongnu.org/mailman/listinfo/igraph-help
>>
>>
>
> ___
> igraph-help mailing list
> igraph-help@nongnu.org
> https://lists.nongnu.org/mailman/listinfo/igraph-help
>
>
___
igraph-help mailing list
igraph-help@nongnu.org
https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] Need help with plotting
Dear Gabor,
Isn't the example I have included enough?
Thanks,
Raj
Raj Balakrishnan
Sent from my mobile phone
-Original Message-
From: "Gábor Csárdi"
Sent: 07-12-2015 07:26
To: "Help for igraph users"
Subject: Re: [igraph] Need help with plotting
I am not sure what is going on here? Are you saying that
edge.betweenness.community is buggy? Possibly, but then please show us why on
some small example?
Gabor
On Mon, Dec 7, 2015 at 2:40 PM, Rk Lata wrote:
Hi there,
I am trying to plot self and cross reactions of bunch of proteins. I have three
states: Positive=1, Negative=0 and Partial=0.5. When I plot the values in the
matrix using the code below, I get the plot shown in Fig A. I am expecting a
plot as in Fig B. (Please see the Figures attached).
What should I do to make the weakly self reacting proteins (c & d) appear as a
separate group and not in group with other strongly self reacting proteins.
abcdefghi
a1
b01100
c000.500
d.50
e00000
f11100
g11100
h00011
i00011
m <- as.matrix(read.csv("C:/Users/balakrr1/Desktop/csv/n3.csv", header=TRUE,
sep = ",", row.names = 1))
g = graph.adjacency(m,mode="undirected",weighted=TRUE)
g=simplify(g, remove.loops=TRUE)
eb=edge.betweenness.community(g,directed=FALSE,weights=E(g)$weight)
fr=layout.fruchterman.reingold(g)
plot(eb,g,layout=fr,edge.width=E(g)$weight,main="Edge Betweenness")
Thanks,
Raj
___
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Re: [igraph] Need help with plotting
I am not sure what is going on here? Are you saying
that edge.betweenness.community is buggy? Possibly, but then please show us
why on some small example?
Gabor
On Mon, Dec 7, 2015 at 2:40 PM, Rk Lata wrote:
> Hi there,
>
> I am trying to plot self and cross reactions of bunch of proteins. I have
> three states: Positive=1, Negative=0 and Partial=0.5. When I plot the
> values in the matrix using the code below, I get the plot shown in Fig A. I
> am expecting a plot as in Fig B. (Please see the Figures attached).
> What should I do to make the weakly self reacting proteins (c & d) appear
> as a separate group and not in group with other strongly self reacting
> proteins.
>
>
> abcdefghia1b01100c000.500d.50e00000f11100g
> 11100h00011i00011
>
> m <- as.matrix(read.csv("C:/Users/balakrr1/Desktop/csv/n3.csv",
> header=TRUE, sep = ",", row.names = 1))
> g = graph.adjacency(m,mode="undirected",weighted=TRUE)
> g=simplify(g, remove.loops=TRUE)
> eb=edge.betweenness.community(g,directed=FALSE,weights=E(g)$weight)
> fr=layout.fruchterman.reingold(g)
> plot(eb,g,layout=fr,edge.width=E(g)$weight,main="Edge Betweenness")
>
>
> Thanks,
>
> Raj
>
>
> ___
> igraph-help mailing list
> igraph-help@nongnu.org
> https://lists.nongnu.org/mailman/listinfo/igraph-help
>
>
___
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Re: [igraph] make check fails 45 times
We don't actually test on cygwin. I suspect that most of these
failures are not serious. They seem linking errors from the build
system.
If your program links OK, everything is fine, I think.
Gabor
On Tue, Nov 10, 2015 at 5:58 PM, MARIA PEREDA GARCIA wrote:
> Hello,
>
>
>
> I need help with the igraph installation via Cygwin in Windows 8.1
>
>
>
> After successfully complete
>
> ./configure
>
> make
>
> make check
>
>
>
> I have the following tests that have failed (I repeated the process twice)
>
>
>
> 46: Query many edge ids (igraph_get_eids): FAILED (basic.at:79)
>
>
>
> Iterators aka vertex and edge sequences
>
>
>
> 47: Vertices in a vector (igraph_vs_vector):ok
>
> 48: Non-adjacent vertices (igraph_vs_nonadj): ok
>
> 49: Sequence (igraph_vs_seq): ok
>
> 50: Edges given by end points (igraph_es_pairs):ok
>
> 51: Edges in a path (igraph_es_path): ok
>
>
>
> Structure generators
>
>
>
> 52: Simple graph creation (igraph_create): ok
>
> 53: Barabasi-Albert model (igraph_barabasi_game): FAILED
> (structure_generators.at:31)
>
> 54: More Barabasi-Albert model (igraph_barabasi_game): FAILED
> (structure_generators.at:36)
>
> 55: Erdos-Renyi model (igraph_erdos_renyi_game):FAILED
> (structure_generators.at:41)
>
> 56: Degree sequence (igraph_degree_sequence_game): FAILED
> (structure_generators.at:46)
>
> 57: k-regular graphs (igraph_k_regular_game): FAILED
> (structure_generators.at:51)
>
> 58: Growing random (igraph_growing_random_game):ok
>
> 59: Preference model (igraph_preference_game): FAILED
> (structure_generators.at:61)
>
> 60: From adjacency matrix (igraph_adjacency): ok
>
> 61: From weighted adjacency matrix (igraph_weighted_adjacency): ok
>
> 62: Star graph (igraph_star): ok
>
> 63: Lattice graph (igraph_lattice): FAILED
> (structure_generators.at:81)
>
> 64: Ring graph (igraph_ring): FAILED
> (structure_generators.at:86)
>
> 65: Tree graph (igraph_tree): ok
>
> 66: Full graph (igraph_full): ok
>
> 67: Graph atlas (igraph_atlas): ok
>
> 68: Small graph (igraph_small): ok
>
> 69: Geomeric random graphs (igraph_grg_game): FAILED
> (structure_generators.at:111)
>
> 70: Graphs in LCF notation (igraph_lcf{,_vector}): FAILED
> (structure_generators.at:116)
>
> 71: Watts-Strogatz graphs (igraph_watts_strogatz_game): FAILED
> (structure_generators.at:121)
>
>
>
> Structural properties
>
>
>
> 72: Two vertices connected by an edge: ok
>
> 73: Density of a graph (igraph_density):FAILED
> (structural_properties.at:31)
>
> 74: Diameter of a graph (igraph_diameter): FAILED
> (structural_properties.at:36)
>
> 75: Average geodesic length (igraph_average_path_length): FAILED
> (structural_properties.at:41)
>
> 76: Google PageRank (igraph_pagerank): FAILED
> (structural_properties.at:46)
>
> 77: Random rewiring (igraph_rewire):ok
>
> 78: Get the shortest paths (igraph_get_shortest_paths): ok
>
> 79: Get the shortest paths #2 (igraph_get_shortest_paths): ok
>
> 80: Weighted shortest paths (Dijkstra): ok
>
> 81: Weighted shortest paths (Bellman-Ford): ok
>
> 82: Get the weighted shortest paths (Dijkstra): ok
>
> 83: Get all weighted shortest paths (Dijkstra): ok
>
> 84: Shortest path wrappers for single target node: ok
>
> 85: Betweenness (igraph_betweenness): FAILED
> (structural_properties.at:96)
>
> 86: Betweenness, big integers (igraph_betweenness): FAILED
> (structural_properties.at:101)
>
> 87: Edge betweenness (igraph_edge_betweenness): FAILED
> (structural_properties.at:107)
>
> 88: Transitivity (igraph_transitivity): ok
>
> 89: Local transitivity (igraph_local_transitivity): FAILED
> (structural_properties.at:117)
>
> 90: Reciprocity (igraph_reciprocity): ok
>
> 91: Minimum spanning tree (igraph_minimum_spanning_tree_*): FAILED
> (structural_properties.at:128)
>
> 92: Cocitation and bibcoupling (igraph_cocitation,igraph_bibcoupling): ok
>
> 93: Similarity coefficients (igraph_similarity_*): ok
>
> 94: Simplification of non-simple graphs (igraph_simplify): ok
>
> 95: Topological sorting (igraph_topological_sorting, igraph_is_dag): ok
>
> 96: Feedback arc sets, Eades heuristics (igraph_feedback_arc_set): ok
>
> 97: Feedback arc sets, integer programming (igraph_feedback_arc_set): ok
>
> 98: Loop edges test (igraph_is_loop): ok
>
> 99: Multiple edges test (igraph_is_multiple): ok
>
> 100: Multiple edges test (igraph_has_multiple): ok
>
> 101: Girth (igraph_girth): ok
>
> 102: Convergence degree (igraph_convergence_degree): ok
>
> 103: Assortativity coefficient (igraph_assortativity): ok
>
> 104: Average nearest neighbor degree (igraph_avg_nearest_neighbor_degree
Re: [igraph] directed graph
This is not possible currently. Gabor On Fri, Nov 20, 2015 at 4:39 PM, Giulia Rossello wrote: > dear all, > I am a new user of R. I would like to know if is possible to compute average > nearest neighbor strength/degree and weighted/unweighted clustering > coefficient taking into account also the direction. it is available an > extension of functions graph.knn and transitivity? > Thank you in advance > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help > ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] Need help with plotting
Hi there,
I am trying to plot self and cross reactions of bunch of proteins. I have
three states: Positive=1, Negative=0 and Partial=0.5. When I plot the
values in the matrix using the code below, I get the plot shown in Fig A. I
am expecting a plot as in Fig B. (Please see the Figures attached).
What should I do to make the weakly self reacting proteins (c & d) appear
as a separate group and not in group with other strongly self reacting
proteins.
abcdefghia1b01100c000.500d.50e00000f11100g00
0011100h00011i00011
m <- as.matrix(read.csv("C:/Users/balakrr1/Desktop/csv/n3.csv",
header=TRUE, sep = ",", row.names = 1))
g = graph.adjacency(m,mode="undirected",weighted=TRUE)
g=simplify(g, remove.loops=TRUE)
eb=edge.betweenness.community(g,directed=FALSE,weights=E(g)$weight)
fr=layout.fruchterman.reingold(g)
plot(eb,g,layout=fr,edge.width=E(g)$weight,main="Edge Betweenness")
Thanks,
Raj
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Re: [igraph] What exactly does igraph_transitivity_undirected() compute for directed graphs?
On Mon, Dec 7, 2015 at 1:28 PM, Szabolcs Horvát wrote: [...] > Do you think a patch that converts directed graphs to undirected > simple graphs before computing the local clustering coefficient would > be appropriate here? Converting the whole graph is not a good solution, because that is O(n+m), and local transitivity is O(1). Converting the graph locally, at the queried vertex, is maybe a better idea, but also harder to implement. So we might as well modify the local transitivity code. Gabor > On 7 December 2015 at 13:16, Gábor Csárdi wrote: >> I am not sure if it is defined. I guess this is just a case when the >> behavior is not defined for multi-graphs. >> >> Gabor >> >> On Mon, Dec 7, 2015 at 12:14 PM, Szabolcs Horvát wrote: >>> Thank you for the explanation. >>> >>> Could you elaborate a bit on how igraph defines the local clustering >>> coefficient when multiple (parallel) edges are present? >>> >>> On 7 December 2015 at 12:56, Gábor Csárdi wrote: It's because of the multiple edges in the first graph. I.e.: > transitivity(as.undirected(g, mode = "each"),"local") [1] 0.333 0.333 1.000 Gabor On Mon, Dec 7, 2015 at 10:05 AM, Szabolcs Horvát wrote: > Hello, > > What precisely does igraph_transitivity_undirected() compute for > directed graphs? > > The C documentation states that > > "Directed graphs are considered as undirected ones." > > but this is not exactly the case. > > With an example using the R interface (for simplicity), > >> g<-make_graph(c(1,2, 2,1, 2,3, 3,1)) >> transitivity(g,"local") > [1] 0.333 0.333 1.000 > >> transitivity(as.undirected(g),"local") > [1] 1 1 1 > > Can someone clarify what precisely is computed in the directed case? > > Szabolcs > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help >>> >>> ___ >>> igraph-help mailing list >>> igraph-help@nongnu.org >>> https://lists.nongnu.org/mailman/listinfo/igraph-help >> >> ___ >> igraph-help mailing list >> igraph-help@nongnu.org >> https://lists.nongnu.org/mailman/listinfo/igraph-help > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] What exactly does igraph_transitivity_undirected() compute for directed graphs?
Thanks again for the clarification! I think what actually happens is that the neighbours of a vertex are counted as the degree of that vertex (which is not the same thing for multigraphs). Do you think a patch that converts directed graphs to undirected simple graphs before computing the local clustering coefficient would be appropriate here? On 7 December 2015 at 13:16, Gábor Csárdi wrote: > I am not sure if it is defined. I guess this is just a case when the > behavior is not defined for multi-graphs. > > Gabor > > On Mon, Dec 7, 2015 at 12:14 PM, Szabolcs Horvát wrote: >> Thank you for the explanation. >> >> Could you elaborate a bit on how igraph defines the local clustering >> coefficient when multiple (parallel) edges are present? >> >> On 7 December 2015 at 12:56, Gábor Csárdi wrote: >>> It's because of the multiple edges in the first graph. I.e.: >>> transitivity(as.undirected(g, mode = "each"),"local") >>> [1] 0.333 0.333 1.000 >>> >>> Gabor >>> >>> On Mon, Dec 7, 2015 at 10:05 AM, Szabolcs Horvát wrote: Hello, What precisely does igraph_transitivity_undirected() compute for directed graphs? The C documentation states that "Directed graphs are considered as undirected ones." but this is not exactly the case. With an example using the R interface (for simplicity), > g<-make_graph(c(1,2, 2,1, 2,3, 3,1)) > transitivity(g,"local") [1] 0.333 0.333 1.000 > transitivity(as.undirected(g),"local") [1] 1 1 1 Can someone clarify what precisely is computed in the directed case? Szabolcs ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help >>> >>> ___ >>> igraph-help mailing list >>> igraph-help@nongnu.org >>> https://lists.nongnu.org/mailman/listinfo/igraph-help >> >> ___ >> igraph-help mailing list >> igraph-help@nongnu.org >> https://lists.nongnu.org/mailman/listinfo/igraph-help > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] What exactly does igraph_transitivity_undirected() compute for directed graphs?
I am not sure if it is defined. I guess this is just a case when the behavior is not defined for multi-graphs. Gabor On Mon, Dec 7, 2015 at 12:14 PM, Szabolcs Horvát wrote: > Thank you for the explanation. > > Could you elaborate a bit on how igraph defines the local clustering > coefficient when multiple (parallel) edges are present? > > On 7 December 2015 at 12:56, Gábor Csárdi wrote: >> It's because of the multiple edges in the first graph. I.e.: >> >>> transitivity(as.undirected(g, mode = "each"),"local") >> [1] 0.333 0.333 1.000 >> >> Gabor >> >> On Mon, Dec 7, 2015 at 10:05 AM, Szabolcs Horvát wrote: >>> Hello, >>> >>> What precisely does igraph_transitivity_undirected() compute for >>> directed graphs? >>> >>> The C documentation states that >>> >>> "Directed graphs are considered as undirected ones." >>> >>> but this is not exactly the case. >>> >>> With an example using the R interface (for simplicity), >>> g<-make_graph(c(1,2, 2,1, 2,3, 3,1)) transitivity(g,"local") >>> [1] 0.333 0.333 1.000 >>> transitivity(as.undirected(g),"local") >>> [1] 1 1 1 >>> >>> Can someone clarify what precisely is computed in the directed case? >>> >>> Szabolcs >>> >>> ___ >>> igraph-help mailing list >>> igraph-help@nongnu.org >>> https://lists.nongnu.org/mailman/listinfo/igraph-help >> >> ___ >> igraph-help mailing list >> igraph-help@nongnu.org >> https://lists.nongnu.org/mailman/listinfo/igraph-help > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] What exactly does igraph_transitivity_undirected() compute for directed graphs?
Thank you for the explanation. Could you elaborate a bit on how igraph defines the local clustering coefficient when multiple (parallel) edges are present? On 7 December 2015 at 12:56, Gábor Csárdi wrote: > It's because of the multiple edges in the first graph. I.e.: > >> transitivity(as.undirected(g, mode = "each"),"local") > [1] 0.333 0.333 1.000 > > Gabor > > On Mon, Dec 7, 2015 at 10:05 AM, Szabolcs Horvát wrote: >> Hello, >> >> What precisely does igraph_transitivity_undirected() compute for >> directed graphs? >> >> The C documentation states that >> >> "Directed graphs are considered as undirected ones." >> >> but this is not exactly the case. >> >> With an example using the R interface (for simplicity), >> >>> g<-make_graph(c(1,2, 2,1, 2,3, 3,1)) >>> transitivity(g,"local") >> [1] 0.333 0.333 1.000 >> >>> transitivity(as.undirected(g),"local") >> [1] 1 1 1 >> >> Can someone clarify what precisely is computed in the directed case? >> >> Szabolcs >> >> ___ >> igraph-help mailing list >> igraph-help@nongnu.org >> https://lists.nongnu.org/mailman/listinfo/igraph-help > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] What exactly does igraph_transitivity_undirected() compute for directed graphs?
It's because of the multiple edges in the first graph. I.e.: > transitivity(as.undirected(g, mode = "each"),"local") [1] 0.333 0.333 1.000 Gabor On Mon, Dec 7, 2015 at 10:05 AM, Szabolcs Horvát wrote: > Hello, > > What precisely does igraph_transitivity_undirected() compute for > directed graphs? > > The C documentation states that > > "Directed graphs are considered as undirected ones." > > but this is not exactly the case. > > With an example using the R interface (for simplicity), > >> g<-make_graph(c(1,2, 2,1, 2,3, 3,1)) >> transitivity(g,"local") > [1] 0.333 0.333 1.000 > >> transitivity(as.undirected(g),"local") > [1] 1 1 1 > > Can someone clarify what precisely is computed in the directed case? > > Szabolcs > > ___ > igraph-help mailing list > igraph-help@nongnu.org > https://lists.nongnu.org/mailman/listinfo/igraph-help ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
[igraph] Python-igraph: Possible memory leak in GraphBase.get_all_shortest_paths()
Hi, I am developing a network analysis tool for evolutionary biology, which uses python-igraph. It appears that repeatedly calling get_all_shortest_paths() on the graph results in the consumption of available memory quite quickly. I have narrowed the memory leak down to get_all_shortest_paths() by using a memory profiler. I was using python-igraph-0.6 earlier and then upgraded to python-igraph-0.7.1.post6. The upgrade did not solve the problem. The OS is Ubuntu 14.04 LTS, with python 2.7.6. Has someone else come across the same issue? Regards, /Fahad ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
[igraph] What exactly does igraph_transitivity_undirected() compute for directed graphs?
Hello, What precisely does igraph_transitivity_undirected() compute for directed graphs? The C documentation states that "Directed graphs are considered as undirected ones." but this is not exactly the case. With an example using the R interface (for simplicity), > g<-make_graph(c(1,2, 2,1, 2,3, 3,1)) > transitivity(g,"local") [1] 0.333 0.333 1.000 > transitivity(as.undirected(g),"local") [1] 1 1 1 Can someone clarify what precisely is computed in the directed case? Szabolcs ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
Re: [igraph] Direction of edges along shortest path
> But how can I get the directions of the edges that are passed along the way > for each path? If your network is not too large, the easiest is probably to: 1. Convert your original graph into another one where each edge is present in both directions: g2 = g.as_undirected() g2.to_directed(mutual=True) 2. Call g2.get_shortest_paths(v=0, weights="length", output="vpath") - this will give you each path as a list of vertex indices 3. For each consecutive vertex index pair (i, j), check whether there is an edge between them in present in g. If so, this is an edge that follows the directions in the original graph, otherwise it goes against them: from itertools import izip def pairs(iterable): return izip(iterable, iterable[1:]) for path in shortest_paths_from_some_source_vertex: edge_follows_direction = [g.are_connected(u, v) for u, v in pairs(path)] Best, T. ___ igraph-help mailing list igraph-help@nongnu.org https://lists.nongnu.org/mailman/listinfo/igraph-help
