Hi Tiago,

Tiago Peixoto wrote

I cannot reproduce this.

As you should have learned by now, we can only make any progress understanding problems like this if you provide at least some _minimial_ information, such as the version of graph-tool that is being used, as well as a complete example that shows the problem (in this case, we need the actual network used.)

Of course, the network is attached ( graph_1950_clean.zip http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027139/graph_1950_clean.zip ) and here is the script that I ran ( model_class_selection_test.py http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027139/model_class_selection_test.py )

Tiago Peixoto wrote

Did you read the documentation?

If you want to use the layered model, you have to supply the edge covariates, i.e.

state = gt.minimize_blockmodel_dl(g, deg_corr=deg_corr,
                                  overlap=overlap,
                                  layers=True,
                                  state_args=dict(ec=eprop))

You are right, this is in the cookbook, I could have spotted that myself. I was looking only at the documentation. Thanks for the explanation though.

Best,

Philipp

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On 22.03.2017 15:42, P-M wrote:

Of course, the network is attached ( graph_1950_clean.zip http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027139/graph_1950_clean.zip ) and here is the script that I ran ( model_class_selection_test.py http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027139/model_class_selection_test.py )

With the help of your script, I was able to reproduce the problem, which only occurs with filtered graphs. I have already fixed it in git.

Best, Tiago

Hi Tiago,

A new error message:

Running:

import graph_tool.all as gt import numpy as np import cPickle as pickle import timeit

g = gt.load_graph('graph_no_multi_1950.gt')

with open('model_selection_results_1950.dat','w') as output: deg_corr = False overlap = True nL = 10

# Initialize the Markov chain from the "ground state" state = gt.minimize_nested_blockmodel_dl(g, deg_corr=deg_corr,overlap=overlap) print 'minimised state' bs = state.get_bs() # Get hierarchical partition. bs += [np.zeros(1)] * (nL - len(bs)) # Augment it to L = 10 with # single-group levels.

state = state.copy(bs=bs, sampling=True)

Returns the following error message:

Traceback (most recent call last): File "model_class_selection_nested_ndc_o.py", line 27, in <module> state = state.copy(bs=bs, sampling=True) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/nested_blockmodel.py", line 146, in copy **kwargs) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/nested_blockmodel.py", line 90, in __init__ nb[:len(b)] = b ValueError: could not broadcast input array from shape (63754) into shape (15643)

Here is the graph ( graph_no_multi_1950_clean.zip http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027153/graph_no_multi_1950_clean.zip ) and the script ( model_class_selection_nested_ndc_o.py http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027153/model_class_selection_nested_ndc_o.py ). The graph-tool version is 2.23dev (commit 8c8fa901, Mon Mar 6 16:13:20 2017 +0100).

Do you know what this might be caused by?

Best,

Philipp

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OK, will investigate further and get back to you if it persists. Thanks for looking into it though.

Best,

Philipp

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Do I have to ask you again to send a complete example?

There is zero I can do with error messages without any context.

Best, Tiago

On 27.03.2017 17:13, P-M wrote:

Running the newest git version (2.23dev (commit 0b766917, Mon Mar 27 12:31:02 2017 +0100)) I now get the following screen output:

minimised state /home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/overlap_blockmodel.py:253: UserWarning: unrecognized keyword arguments: ['vweight', 'eweight'] str(list(kwargs.keys()))) /home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/blockmodel.py:410: UserWarning: unrecognized keyword arguments: ['copy_bg'] str(list(kwargs.keys()))) equilibrating Traceback (most recent call last): File "model_class_selection_nested_ndc_o.py", line 44, in <module> callback=collect_marginals) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/mcmc.py", line 125, in mcmc_equilibrate delta, nmoves = state.mcmc_sweep(**mcmc_args) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/nested_blockmodel.py", line 588, in mcmc_sweep return self._h_sweep(lambda s, **a: s.mcmc_sweep(**a), c=c, **kwargs) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/nested_blockmodel.py", line 505, in _h_sweep get_entropy_args(eargs)) File "/home/pmj27/anaconda2/lib/python2.7/site-packages/graph_tool/inference/blockmodel.py", line 715, in _couple_state self._state.couple_state(state._state, entropy_args) AttributeError: 'graph_tool::OverlapBlockState<boost::adj_list<unsi' object has no attribute 'couple_state'

Seeing as it ran error free for you previously I presume you can't reproduce this error either? What could we do to pinpoint it?

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On 27.03.2017 17:26, P-M wrote:

Hi Tiago,

graph and script are entirely unchanged from my previous message. Here they are again just in case ( graph_no_multi_1950_clean.zip http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027160/graph_no_multi_1950_clean.zip , model_class_selection_nested_ndc_o.py http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027160/model_class_selection_nested_ndc_o.py )

This time, I can in fact reproduce the problem.

I have already fixed it in git.

Best, Tiago