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git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@8617 f3b2605a-c512-4ea7-a41b-209d697bcdaa

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sjplimp
2012-08-13 17:01:35 +00:00
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doc/Section_python.txt
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@ -93,6 +93,12 @@ them. See the discussion in "Section_start
shared library, for instructions on how to set the LD_LIBRARY_PATH
variable appropriately.
If your LAMMPS build is not using any auxiliary libraries which are in
non-default directories where the system cannot find them, you
typically just need to add something like this to your ~/.cshrc file:
setenv LD_LIBRARY_PATH ${LD_LIBRARY_PATH}:/home/sjplimp/lammps/src :pre
:line
11.2 Building LAMMPS as a shared library :link(py_2),h4
@ -110,11 +116,14 @@ make -f Makefile.shlib foo :pre
where foo is the machine target name, such as linux or g++ or serial.
This should create the file liblmp_foo.so in the src directory, as
well as a soft link liblmp.so which is what the Python wrapper will
load by default. If you are building multiple machine versions of the
shared library, the soft link is always set to the most recently built
version.
load by default. Note that if you are building multiple machine
versions of the shared library, the soft link is always set to the
most recently built version.
See "Section_start 5"_Section_start.html#start_5 for more details.
If this fails, see "Section_start 5"_Section_start.html#start_5 for
more details, especially if your LAMMPS build uses auxiliary
libraries, e.g. ones required by certain packages and found in the
lib/package directories.
:line
@ -135,11 +144,10 @@ These include
"myMPI"_http://nbcr.sdsc.edu/forum/viewtopic.php?t=89&sid=c997fefc3933bd66204875b436940f16
"Pypar"_http://code.google.com/p/pypar :ul
All of these except pyMPI work by wrapping the MPI library (which must
be available on your system as a shared library, as discussed above),
and exposing (some portion of) its interface to your Python script.
This means Python cannot be used interactively in parallel, since they
do not address the issue of interactive input to multiple instances of
All of these except pyMPI work by wrapping the MPI library and
exposing (some portion of) its interface to your Python script. This
means Python cannot be used interactively in parallel, since they do
not address the issue of interactive input to multiple instances of
Python running on different processors. The one exception is pyMPI,
which alters the Python interpreter to address this issue, and (I
believe) creates a new alternate executable (in place of "python"
@ -169,22 +177,17 @@ sudo python setup.py install :pre
The "sudo" is only needed if required to copy Numpy files into your
Python distribution's site-packages directory.
To install Pypar (version pypar-2.1.0_66 as of April 2009), unpack it
To install Pypar (version pypar-2.1.4_94 as of Aug 2012), unpack it
and from its "source" directory, type
python setup.py build
sudo python setup.py install :pre
Again, the "sudo" is only needed if required to copy PyPar files into
Again, the "sudo" is only needed if required to copy Pypar files into
your Python distribution's site-packages directory.
If you have successully installed Pypar, you should be able to run
python serially and type
Python and type
import pypar :pre
@ -200,6 +203,19 @@ print "Proc %d out of %d procs" % (pypar.rank(),pypar.size()) :pre
and see one line of output for each processor you run on.
IMPORTANT NOTE: To use Pypar and LAMMPS in parallel from Python, you
must insure both are using the same version of MPI. If you only have
one MPI installed on your system, this is not an issue, but it can be
if you have multiple MPIs. Your LAMMPS build is explicit about which
MPI it is using, since you specify the details in your lo-level
src/MAKE/Makefile.foo file. Pypar uses the "mpicc" command to find
information about the MPI it uses to build against. And it tries to
load "libmpi.so" from the LD_LIBRARY_PATH. This may or may not find
the MPI library that LAMMPS is using. If you have problems running
both Pypar and LAMMPS together, this is an issue you may need to
address, e.g. by moving other MPI installations so that Pypar finds
the right one.
:line
11.4 Testing the Python-LAMMPS interface :link(py_4),h4
@ -213,27 +229,17 @@ and type:
If you get no errors, you're ready to use LAMMPS from Python.
If the load fails, the most common error to see is
OSError: Could not load LAMMPS dynamic library
OSError: Could not load LAMMPS dynamic library :pre
which means Python was unable to load the LAMMPS shared library. This
can occur if it can't find the LAMMMPS library; see the environment
variable discussion "above"_#python_1. Or if it can't find one of the
auxiliary libraries that was specified in the LAMMPS build, in a
shared dynamic library format. This includes all libraries needed by
main LAMMPS (e.g. MPI or FFTW or JPEG), system libraries needed by
main LAMMPS (e.g. extra libs needed by MPI), or packages you have
installed that require libraries provided with LAMMPS (e.g. the
USER-ATC package require lib/atc/libatc.so) or system libraries
(e.g. BLAS or Fortran-to-C libraries) listed in the
lib/package/Makefile.lammps file. Again, all of these must be
available as shared libraries, or the Python load will fail.
typically occurs if the system can't find the LAMMMPS shared library
or one of the auxiliary shared libraries it depends on.
Python (actually the operating system) isn't verbose about telling you
why the load failed, so go through the steps above and in
"Section_start 5"_Section_start.html#start_5 carefully.
why the load failed, so carefully go through the steps above regarding
environment variables, and the instructions in "Section_start
5"_Section_start.html#start_5 about building a shared library and
about setting the LD_LIBRARY_PATH envirornment variable.
[Test LAMMPS and Python in serial:] :h5
@ -278,10 +284,10 @@ and you should see the same output as if you had typed
Note that if you leave out the 3 lines from test.py that specify Pypar
commands you will instantiate and run LAMMPS independently on each of
the P processors specified in the mpirun command. In this case you
should get 4 sets of output, each showing that a run was made on a
single processor, instead of one set of output showing that it ran on
4 processors. If the 1-processor outputs occur, it means that Pypar
is not working correctly.
should get 4 sets of output, each showing that a LAMMPS run was made
on a single processor, instead of one set of output showing that
LAMMPS ran on 4 processors. If the 1-processor outputs occur, it
means that Pypar is not working correctly.
Also note that once you import the PyPar module, Pypar initializes MPI
for you, and you can use MPI calls directly in your Python script, as
@ -289,6 +295,8 @@ described in the Pypar documentation. The last line of your Python
script should be pypar.finalize(), to insure MPI is shut down
correctly.
[Running Python scripts:] :h5
Note that any Python script (not just for LAMMPS) can be invoked in
one of several ways:
@ -340,7 +348,7 @@ C or Fortran program.
lmp = lammps() # create a LAMMPS object using the default liblmp.so library
lmp = lammps("g++") # create a LAMMPS object using the liblmp_g++.so library
lmp = lammps("",list) # ditto, with command-line args, list = \["-echo","screen"\]
lmp = lammps("",list) # ditto, with command-line args, e.g. list = \["-echo","screen"\]
lmp = lammps("g++",list) :pre
lmp.close() # destroy a LAMMPS object :pre
@ -379,13 +387,14 @@ lmp.put_coords(x) # set all atom coords via x :pre
:line
IMPORTANT NOTE: Currently, the creation of a LAMMPS object does not
take an MPI communicator as an argument. There should be a way to do
this, so that the LAMMPS instance runs on a subset of processors if
desired, but I don't know how to do it from Pypar. So for now, it
runs on MPI_COMM_WORLD, which is all the processors. If someone
figures out how to do this with one or more of the Python wrappers for
MPI, like Pypar, please let us know and we will amend these doc pages.
IMPORTANT NOTE: Currently, the creation of a LAMMPS object from within
lammps.py does not take an MPI communicator as an argument. There
should be a way to do this, so that the LAMMPS instance runs on a
subset of processors if desired, but I don't know how to do it from
Pypar. So for now, it runs with MPI_COMM_WORLD, which is all the
processors. If someone figures out how to do this with one or more of
the Python wrappers for MPI, like Pypar, please let us know and we
will amend these doc pages.
Note that you can create multiple LAMMPS objects in your Python
script, and coordinate and run multiple simulations, e.g.