On 14.02.2017 17:20, P-M wrote:
> 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/file/n4027034/graph_no_multi_reac_type.gt>
>
> ). 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,
>
> PhilippPlease supply the actual graph you used, so this can be investigated. The git version you tried is more than a month old; do you see this problem with a current git version? Since you tried with 2.20dev, I assume you compiled it yourself. What OS are you using, what GCC version do you have, and are you using sparsehash or not? Best, Tiago -- Tiago de Paula Peixoto <[email protected]>
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