"IndexError: tuple index out of range"

[Chilkos]

I've just tried to use bnlearn for the first time, and am trying to run the example code from the readme. However, it gives an error when running G = bn.plot(model)

Python 3.8.8 (default, Apr 13 2021, 15:08:03) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import bnlearn as bn
>>> df = bn.import_example()
[bnlearn] >Import dataset..
>>> model = bn.structure_learning.fit(df)
[bnlearn] >Computing best DAG using [hc]
[bnlearn] >Set scoring type at [bic]
>>> G = bn.plot(model)
[bnlearn] >Plot based on BayesianModel
Traceback (most recent call last):
  File "C:\Users\JasperKueppers\anaconda3\envs\BNLEARN\lib\site-packages\networkx\utils\decorators.py", line 396, in _random_state
    random_state_arg = args[random_state_index]
IndexError: tuple index out of range

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\JasperKueppers\anaconda3\envs\BNLEARN\lib\site-packages\bnlearn\bnlearn.py", line 600, in plot
    pos = network.graphlayout(model, pos=pos, scale=scale, layout=layout, verbose=verbose)
  File "C:\Users\JasperKueppers\anaconda3\envs\BNLEARN\lib\site-packages\bnlearn\helpers\network.py", line 405, in graphlayout
    pos = nx.fruchterman_reingold_layout(model, scale=scale, iterations=50)
  File "C:\Users\JasperKueppers\anaconda3\envs\BNLEARN\lib\site-packages\decorator.py", line 231, in fun
    return caller(func, *(extras + args), **kw)
  File "C:\Users\JasperKueppers\anaconda3\envs\BNLEARN\lib\site-packages\networkx\utils\decorators.py", line 400, in _random_state
    raise nx.NetworkXError("random_state_index is incorrect") from e
networkx.exception.NetworkXError: random_state_index is incorrect

This is in a fresh Anaconda installation (Python 3.8.8), with pgmpy and pip installed as per the quickstart/installation guide (using conda and pip respectively)

[erdogant]

Im going to check it. Issues with networkx is most of the time versioning stuf. So you can try python 3.6 or 3.8 and the recommended networkx version (see requirements)

[erdogant]

I did check the working with python 3.8.8 and it seems to work fine. Maybe your networkx version is <2.5?

Can you check the following:

import networkx
print(networkx.__version__)
# This should be >= 2.5

Force update networkx with: pip install -U networkx

[Chilkos]

Seems that I was on version 2.5 of networkx, and updating installed version 2.5.1. Running the example code works now and shows the graph, thanks for the help!