pmda 0.3.0

Ready to use analysis and buildings blocks to write parallel analysis algorithms using MDAnalysis with dask.

For example, run a rmsd analysis on all available cores:

import MDAnalysis as mda
from pmda import rms

u = mda.Universe(top, traj)
ref = mda.Universe(top, traj)

rmsd_ana = rms.RMSD(u.atoms, ref.atoms).run(n_jobs=-1)

print(rmsd_ana.rmsd)

By default PMDA use the multiprocessing scheduler of dask. This is sufficient if you want to run your simulation on a single machine. If your analysis takes a very long time (>30 min) you can also spread it to several nodes using the distributed scheduler. To do this you can pass a scheduler keyword argument to the run method.

To write your own parallel algorithms you can subclass the pmda.parallel.ParallelAnalysisBase class.

pip install --upgrade pmda

git clone git@github.com:MDAnalysis/pmda.git
cd pmda
python setup.py install