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For the clustering in Python, another library for the clustering in Python is [scikit-learn](http://scikit-learn.org). It's quite a dependency but it provides more [clustering methods](http://scikit-learn.org/stable/modules/clustering.html) (at least k-means which scipy doesn't...

> The critical point of going to Python (scipy or scikit-learn) is to have the same results as in R for the results (for HC). psi_md_traj_1.pdb could be a good...

Indeed, here it is: http://nbviewer.ipython.org/gist/HubLot/9e0f76bc987489aedabe The downside, for now, is it's not possible to have directly medoid in scikit-learn with hclust. I search for an alternative way.

Interesting. I computed the medoids in the same way as the R script. I updated the gist

Ouch... By looking the [source code](https://github.com/scikit-learn/scikit-learn/blob/bb39b49/sklearn/cluster/hierarchical.py), the ward Hclust in scikit-learn is based on the scipy one, hence the same results. But for R... After digging a little bit, maybe...

Thanks. About the R methods, see #66

To sum up the results about hierarchical clustering in R vs Python (scipy), I made a [notebook](http://nbviewer.ipython.org/gist/HubLot/aef0ecd56f40ec2ceaab). Basically: - matrix input of scipy functions are different from R. - Ward...

I updated the notebook with scikit-learn as the input is different. This doesn't change the conclusion. I agree with the questions raised by @jbarnoud

It's doable now since MDAnalysis is already in a conda channel. I think @jbarnoud's modifications are enough to create a conda package in a custom channel. If it succeeds, yes,...

Yes, it is the main objective. I just wanted to try the build first before submitting to bioconda.