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Please use the issue tracker only to report bugs (i.e. errors in the library that need to be fixed) or feature requests.

For questions about how to compile, install or use the library, please use instead the mailing list at https://graph-tool.skewed.de/mailing
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When opening new issues, please choose the BUG template from the drop-down menu, and fill out the required information.

  • Tiago Peixoto
  • graph-toolgraph-tool
  • Issues
  • #452

Closed
Open
Opened Mar 26, 2018 by Katharina Baum@kbaum

get_edges_prob() alters state entropy with real-normal edge covariates

Bug report:

Experienced in version 2.26, under Python 2.7 and 3.6 as well as using the latest Docker image (18-03-26).

Bug description

Calling get_edges_prob() alters the state object and gives inconsistent results if using a real-normal edge prior (apparently not for real-exponential prior or models without edge covariates).

Example illustrating the problem

import graph_tool.all as gt
g=gt.collection.data['celegansneural']
state=gt.minimize_blockmodel_dl(g,state_args=dict(recs=[g.ep.value],rec_types=['real-normal']))
original_entropy=state.entropy()
edge_prob=[]
for i in range(10000): edge_prob.append(state.get_edges_prob(missing=[],spurious=[(0,2)]))

original_entropy-state.entropy() #this is not zero...
edge_prob[0]-edge_prob[-1] #this is not zero...
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Reference: count0/graph-tool#452