Diffusion lammps (efficient_neuronet) Browse

README
baa39e88a0acefficient_neuronet

README
View Options

			This directory contains Python code which wraps LAMMPS as a library
			and allows the LAMMPS library interface to be invoked from Python,
			either from a Python script or using Python interactively.

			Details on the Python interface to LAMMPS and how to build LAMMPS as a
			shared library, for use with Python, are given in
			doc/Section_python.html and in doc/Section_start.html#start_5.

			Basically you need to follow these steps in the src directory:

			% make g++ mode=shlib # build for whatever machine target you wish
			% make install-python # may need to do this via sudo

			You can replace the last step by a one-time setting of environment
			variables in your shell script. Or you can run the python/install.py
			script directly to give you more control over where the two relevant
			files are installed. See doc/Section_python.html for details.

			You should then be able to launch Python and instantiate an instance
			of LAMMPS:

			% python
			>>> from lammps import lammps
			>>> lmp = lammps()

			If that gives no errors, you have succesfully wrapped LAMMPS with
			Python. See doc/Section_python.html#py_7 for tests you can then use
			to run LAMMPS both in serial or parallel thru Python.

			Note that you can also invoke Python code from within a LAMMPS input
			script, using the "python" command. See the doc/python.html doc page
			for details. The Python code you invoke can also call back to LAMMPS
			using the same interface described here for wrapping LAMMPS.

			-------------------------------------------------------------------

			Once you have successfully wrapped LAMMPS, you can run the Python
			scripts in the examples sub-directory:

			trivial.py read/run a LAMMPS input script thru Python
			demo.py invoke various LAMMPS library interface routines
			simple.py parallel example, mimicing examples/COUPLE/simple/simple.cpp
			split.py parallel example
			mc.py Monte Carlo energy relaxation wrapper on LAMMPS
			gui.py GUI go/stop/temperature-slider to control LAMMPS
			plot.py real-time temeperature plot with GnuPlot via Pizza.py
			viz_tool.py real-time viz via some viz package
			vizplotgui_tool.py combination of viz.py and plot.py and gui.py

			For the viz_tool.py and vizplotgui_tool.py commands, replace "tool"
			with "gl" or "atomeye" or "pymol", depending on what visualization
			package you have installed. We hope to add a VMD option soon.

			Note that for GL, you need to be able to run the Pizza.py GL tool,
			which is included in the pizza sub-directory. See the Pizza.py doc
			pages for more info:

			http://www.sandia.gov/~sjplimp/pizza.html

			Note that for AtomEye, you need version 3, and their is a line in the
			scripts that specifies the path and name of the executable. See
			the AtomEye WWW pages for more details:

			http://mt.seas.upenn.edu/Archive/Graphics/A
			http://mt.seas.upenn.edu/Archive/Graphics/A3/A3.html

			The latter link is to AtomEye 3 which has the scriping
			capability needed by these Python scripts.

			Note that for PyMol, you need to have built and installed the
			open-source version of PyMol in your Python, so that you can import it
			from a Python script. See the PyMol WWW pages for more details:

			http://www.pymol.org
			http://sourceforge.net/scm/?type=svn&group_id=4546

			The latter link is to the open-source version.

			-------------------------------------------------------------------

			Each example script has more documentation in the file that explains
			how to use it and what it is doing.

			You can run a particular script in either of the following ways:

			% trivial.py in.trivial
			% python -i trivial.py in.trivial

			The former assumes that you have changed the first line of the script
			to point to the Python installed on your box and made the script
			exectable (e.g. chmod +x trivial.py).

			The example scripts take the following arguments. The in.* args are
			LAMPS input scripts.

			trivial.py in.trivial
			demo.py
			simple.py in.simple # can run in parallel (see below)
			split.py in.simple # can run in parallel (see below)

			gui.py in.gui 100
			plot.py in.plot 10 1000 thermo_temp
			viz_tool.py in.viz 100 5000
			vizplotgui_tool.py in.viz 100 thermo_temp

			To run LAMMPS in parallel from Python, so something like this:

			% mpirun -np 4 simple.py in.simple
			% mpirun -np 4 python split.py in.simple

			If you run simple.py as-is, this will invoke P instances of a
			one-processor run, where both Python and LAMMPS will run on single
			processors. Each running job will read the same input file, and write
			to same log.lammps file, which isn't too useful.

			However, if you have either the Pypar or mpi4py packages installed in
			your Python, and uncomment the Pypar or mpi4py code in simple.py, then
			the above commands will invoke 1 instance of a P-processor run. Both
			Python and LAMMPS will run on P processors. The job will read the
			input file and write a single log.lammps file.

			The split.py script can also be run in parallel. It uses mpi4py
			version 2.0.0 (or later), which makes it possible to pass a
			communicator when creating the LAMMPS object and thus run multiple
			instances of LAMMPS at the same time, each on a different subset of
			MPI ranks. Or run LAMMPS on one subset and some other program on the
			rest of the MPI ranks, concurrently. See comments in the split.py
			script for more details.

lammps/python/READMEbaa39e88a0acefficient_neuronet

READMEView Options

lammps/python/README
baa39e88a0acefficient_neuronet

README
View Options