Re: [AMBER-Developers] Tests Errors in AmberTools

From: Jason Swails <>
Date: Wed, 8 Jun 2016 13:55:16 -0400

On Wed, Jun 8, 2016 at 1:33 PM, David A Case <> wrote:

> On Wed, Jun 08, 2016, Claudia Ramírez wrote:
> >
> > I did a git pull on Monday (June 6), with gnu 4.8 compilers and doing
> just
> > ./configure gnu (serial for now) in Ubuntu 14.04 LTS. And it has 4 tests
> on
> > AmberTools that aren't working (this is without my modifications), and I
> > don't know why. I'm attaching the log file to see if anyone could help me
> > make it work.
> All the problems are python-related problems, related either to pytraj or
> to the sander api interface.
> What is the PYTHON variable in your config.h? If you are not already
> using a miniconda python, try going to $AMBERHOME/AmberTools/src and
> running
> configure_python. Then go back to AMBERHOME and re-run configure.
> [I still am pushing the (so-far, minority) viewpoint that all users should
> be offered the choice to install the miniconda python. Users that have
> both
> experience with python, and the desire/need to use a different interpreter,
> are welcome to decline the offer. But configure2 is still prone to
> deciding
> that the python in a user's path is OK when it is in fact not OK. So,
> letting
> us know which python your Amber installation is using would be a help
> here.]

​I give :). Based on citations, questions to the mailing list, and age of
the various Python projects, I think the predominant use of Python in Amber
is, which carries with it only what ParmEd needs to run (Python
2.7 + numpy these days, which is a lot more than it used to require).

For that, miniconda+everything seems like overkill. But on the flip side,
deciding on a "standardized" setup *drastically* reduces the effort we need
to spend to fully test all "common" user configurations. My only
trepidation here is that, on OS X, the libc++/libstdc++ issues still seem
to be wreaking havoc with pytraj and cpptraj. I hope we can soon find
something to settle on to make deployment easy, because the added benefit
from stability, performance, and avoiding effort duplication we get by
integrating with mature Python packages provided through the Anaconda stack
is a big win.

All the best,

Jason M. Swails
AMBER-Developers mailing list
Received on Wed Jun 08 2016 - 11:00:04 PDT
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