Blog

Official Conda Builds

Starting today MDAnalysis is officially building conda packages. The package are published in the MDAnalysis organization on anaconda.org. The conda package includes the MDAnalysis packages as well as the MDAnalysisTests package.

To install MDAnalysis with conda use:

conda config --add channels MDAnalysis
conda install mdanalysis

If you later want to update to the next release use:

conda update mdanalysis

Currently we only support linux 64bit builds for conda. OSX users still have to use pip. We plan to support OSX in the future as well; we’d appreciate any help here.

The GridDataFormats package is also available through conda on OSX and linux.

@kain88-de

Molecular visualization in the Jupyter Notebook with nglview

nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook. The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objects directly:

import MDAnalysis as mda
import nglview as nv
from nglview.datafiles import PDB, XTC

u = mda.Universe(PDB, XTC)

protein = u.select_atoms('protein')

Although we could use the full Universe, selecting a subset of the atoms as an AtomGroup will give better performance when viewing the trajectory interactively. We can feed this directly to the nglview.show_mdanalysis function to produce the Jupyter widget:

w = nv.show_mdanalysis(protein)
w

This will give something like this in the notebook itself:

The notebook widget (you’ll have to try it yourself to see — what you see above is a limited view but you can still rotate and zoom the molecule) also lets you select atoms by clicking on the molecule, add custom representations to atom selections, and interactively view different frames of the trajectory, both programmatically and with a graphical slider. Be sure to double-click the notebook viewer widget to have a look at everything in a lovely full-screen view, too!

nglview is just a pip install away:

pip install nglview

Give it a try, and be sure to thank Alexander Rose (@arose) and Hai Nguyen (@hainm) for pushing this project forward!

@dotsdl

Google Summer of Code 2016

Google Summer of Code 2016

MDAnalysis has been accepted as a sub-org of the Python software foundation, PSF, for Google Summer of Code 2016. If you are interested in working with us this summer as a student read the advice and links below and write to us on the mailing list.

We are looking forward to all applications from interested students (undergraduates and graduates).

The application window deadline is March 25, 2016 at 12:00 (MST). As part of the application process you must complete all the steps listed under Information for Students and familiarize yourself with Google Summer of Code 2016. Apply as soon as possible.

Project Ideas

We have listed several possible projects for you to work on on our wiki. Each project is rated with a difficulty and lists the possible mentors for it.

Alternatively, if you have another idea about a project please write to us on the developer list and we can discuss it there.

Information for Students

You must meet our own requirements and the PSF requirements if you want to be a student with MDAnalysis this year (read all the docs behind these links!). You must also meet the eligibility criteria.

As a start to get familiar with MDAnalysis and open source development you should follow these steps:

Complete the Tutorial

We have a tutorial explaining the basics of MDAnalysis. You should go through the tutorial at least once to understand how MDAnalysis is used.

Introduce yourself to us

Introduce yourself on the mailing list. Tell us what you plan to work on during the summer or what you have already done with MDAnalysis

Close an issue of MDAnalysis

You must have at least one commit in the development branch of MDAnalysis in order to be eligible, i.e.. you must demonstrate that you have been seriously engaged with the MDAnalysis project.

We have a list of easy bugs to work on in our issue tracker on GitHub. We also appreciate if you write more tests or update/improve our documentation. To start developing for MDAnalysis have a look at our guide for developers and write us on the mailing list if you have more questions about setting up a development environment.

@kain88-de