Assortative community structure - argument error
After running the following example, reported in the documentation
g = gt.collection.data["football"]
# We can use the same agglomerative heuristic as before, but we need
# to specify PPBlockState as the internal state.
state = gt.minimize_blockmodel_dl(g, state=gt.PPBlockState)
# Now we run 100 sweeps of the MCMC with zero temperature, as a
# refinement. This is often not necessary.
state.multiflip_mcmc_sweep(beta=np.inf, niter=100)
state.draw(pos=g.vp.pos, output="football-pp.svg")
I got the following error
TypeError Traceback (most recent call last)
<ipython-input-95-1820d69b5f7f> in <module>
4 # to specify PPBlockState as the internal state.
5
----> 6 state = gt.minimize_blockmodel_dl(g, state=gt.PPBlockState)
7
8
TypeError: minimize_blockmodel_dl() got an unexpected keyword argument 'state'
All the packages are up to dated to the latest versions. Why this happens? Has the implementation of minimize_blockmodel been changed? Thank you