08 Mar 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.
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
28 Feb 2016
We have just released MDAnalysis version 0.14.0. This release contains a large
number of new features and bug fixes. The highlights are listed below but for
more details see the
release notes.
Upgrade
You can upgrade with pip install --upgrade MDAnalysis
Noticable Changes
Implicit OR in selections
Many long selection strings used in select_atoms have been simplified through
allowing implicit OR in the arguments. For example to select all atoms
with one of a few names previous required lots of ORs
# OLD
u.select_atoms('name Ca or name N or name Ch')
# NEW
u.select_atoms('name Ca N Ch')
The new syntax allows multiple arguments after the keyword name.
The selection will keep eating arguments till it hits a keyword.
The use of wildcards is still possible too, making the selection
of all atoms with a type beginning with ‘C’ or ‘N’ as simple as:
u.select_atoms('type C* N*')
Similarly, for selecting ranges of resids
# OLD
u.select_atoms('resid 1:10 or resid 40:50 or resid 56 or resid 67')
# NEW
u.select_atoms('resid 1:10 40:50 56 67')
This new behaviour works for name, type, resname, segid, altLoc, resid,
resnum and bynum selections! The old behaviour will still work,
but we feel this should save a lot of typing!
Boolean indexing of trajectories
You can now treat trajectories like numpy arrays in a fully pythonic fashion:
You could already do fancy indexing and now you can also do boolean indexing. One application
is building simple re-usable trajectory filters with ease, e.g., in order to slice
data.
# build a filter array for re-use: only frames where the centroids
# of groups A and B are closer than 3 A
idx = [np.linalg.norm(A.centroid() - B.centroid()) < 3.0 for ts in u.trajectory]
for ts in u.trajectory[idx]:
# analyze the frames where |A - B| distance < 3
for ts in u.trajectory[np.logical_not(idx)]:
# do analysis on the other frames, |A - B| >= 3
New analysis module to calculate linear densities
The
MDAnalysis.analysis.lineardensity
module contains the class LinearDensity that simplifies calculation of mass
and charge densities profiles along the primary axes of a simulation cell.
Rewrite of TRR and XTC file handling
Our wrapper of the Gromacs library
xdrlib
has been completely rewritten in cython. This changes brings us one
step closer towards supporting Python 3. The only user facing API change is that
we don’t save persistent frame offsets with the pickle module anymore but
with numpy’s ‘npz’ format. This improves reopening of xtc/trr files.
Experimental Python 3 Support
With this release it is possible to run MDAnalysis under Python 3. We have
ported most of our coordinate readers, DCD is still missing, and topology
readers to be python2/3 compatible. Most features should already work but expect
there to be some minor glitches.
Others
This release contains other performance enhancements and fixes. For a detailed
list see the release notes.
16 Jan 2016
We have just released MDAnalysis version 0.13.0.
Upgrade
You can upgrade with pip install --upgrade MDAnalysis
Noticable Changes
Usage of openMP
The MDAnalysis.lib.parallel.distances module has been merged into
MDAnalysis.lib.distances. To select the openMP implementation all functions in
that module now accept a backend='openMP' keyword. See
#530.
Reading GRO files has been sped up for large files. Velocities will now also be
written written for GRO files if possible.
Others
This release contains other performance enhancements and fixes. For a detailed
list see the
release notes