Skip to content
forked from Amber-MD/cpptraj

Biomolecular simulation trajectory/data analysis.

License

Notifications You must be signed in to change notification settings

AvikDas20/cpptraj

 
 

Repository files navigation

CPPTRAJ

Fast, parallelized molecular dynamics trajectory data analysis.

Build Status

  • Travis-CI: Travis Build Status
  • AppVeyor: Windows Build Status
  • Jenkins: Jenkins Build Status
  • LGTM: Language grade: C/C++

Description

CPPTRAJ is a program designed to process and analyze molecular dynamics trajectories and relevant data sets derived from their analysis. CPPTRAJ supports many popular MD software packages including Amber, CHARMM, Gromacs, and NAMD.

CPPTRAJ is also distributed as part of the freely available AmberTools software package. The official AmberTools release version of CPPTRAJ can be found at the Amber website.

For those wanting to use CPPTRAJ in their Python scripts, see Pytraj.

See what's new in CPPTRAJ. For those just starting out you may want to check out some CPPTRAJ tutorials or Amber-Hub which contains many useful "recipes" for CPPTRAJ.

For more information (or to cite CPPTRAJ) see the following publication:

Daniel R. Roe and Thomas E. Cheatham, III, "PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data". J. Chem. Theory Comput., 2013, 9 (7), pp 3084-3095.

For more information regarding trajectory/ensemble parallelism via MPI in CPPTRAJ see the following publication:

Daniel R. Roe and Thomas E. Cheatham, III, "Parallelization of CPPTRAJ enables large scale analysis of molecular dynamics trajectory data". J. Comp. Chem., 2018, DOI: 10.1002/jcc25382.

Disclaimer and Copyright

CPPTRAJ is Copyright (c) 2010-2021 Daniel R. Roe. The terms for using, copying, modifying, and distributing CPPTRAJ are specified in the file LICENSE.

Documentation

The /doc subdirectory contains PDF and LyX versions of the CPPTRAJ manual. The latest version of the manual is compiled each time new code is merged and is available for download here. An HTML version can be found here. There is also limited help for commands in interactive mode via help [<command>]; help with no arguments lists all known commands.

Code documentation generated by doxygen are available here. You can generate the documentation yourself with the command make docs. A limited developers guide is available here and limited HTML-formatted documentation is available here.

Installation & Testing

Run ./configure --help for a short list of configure options. ./configure --full-help will list all available configure options. For full functionality, CPPTRAJ makes use of the following libraries:

  • NetCDF
  • BLAS
  • LAPACK
  • Gzip
  • Bzip2
  • Parallel NetCDF (-mpi build only, for NetCDF trajectory output in parallel)
  • CUDA (-cuda build only)
  • FFTW (mostly optional; required for PME functionality and very large FFTs)

CPPTRAJ also makes use of the following libraries that are bundled with CPPTRAJ. External ones can be used in place of these if desired.

  • ARPACK; without this diagonalization of sparse matrices in diagmatrix will be slow
  • helPME, required for PME functionality
  • XDR for reading GROMACS XTC trajectories
  • TNG for reading GROMACS TNG trajectories

./configure gnu should be adequate to set up compilation for most systems. For systems without BLAS/LAPACK/ARPACK and/or NetCDF libraries installed, the -amberlib flag can be specified to use the ones already compiled in an AmberTools installation ($AMBERHOME must be set), e.g. ./configure -amberlib gnu. C++11 support is required to enable particle mesh Ewald (PME) calculation support.

For multicore systems, the -openmp flag can be specified to enable OpenMP parallelization, e.g. ./configure -openmp gnu. An MPI-parallelized version of CPPTRAJ can also be built using the -mpi flag. CPPTRAJ can be built with both MPI and OpenMP; when running this build users should take care to properly set OMP_NUM_THREADS if using more than 1 MPI process per node (the number of processes * threads should not be greater than the number of physical cores on the machine).

A CUDA build is now also available via the -cuda configure flag. However, currently only a few commands benefit from this (see the manual for details). By default CPPTRAJ will be configured for multiple shader models; to restrict the CUDA build to a single shader model set the SHADER_MODEL environment variable before running configure.

Any combination of -cuda, -mpi, and -openmp may be used. The configure script by default sets everything up to link dynamically. The -static flag can be used to force static linking. If linking errors are encountered you may need to specify library locations using the --with-LIB= options. For example, to use NetCDF compiled in /opt/netcdf use the option --with-netcdf=/opt/netcdf. Alternatively, individual libraries can be disabled with the -no<LIB> options. The -libstatic flag can be used to static link only libraries that have been specified.

CPPTRAJ can also be built with support for OpenMM by specifying '--with-openmm=PATH', where PATH is the OpenMM directory containing the OpenMM library, i.e. PATH/lib/libOpenMM.so. Currently the only command that uses OpenMM is emin, so compiling with OpenMM is typically not required at this time.

After configure has been successfully run, make install will compile and place the cpptraj binary in the $CPPTRAJHOME/bin subdirectory. Note that on multithreaded systems make -j X install (where X is an integer > 1 and less than the max # cores on your system) will run much faster. After installation, It is highly recommended that make check be run as well to test the basic functionality of CPPTRAJ.

CPPTRAJ Authors

Lead Author: Daniel R. Roe ([email protected]) Laboratory of Computational Biology National Heart Lung and Blood Institute National Institutes of Health, Bethesda, MD.

CPPTRAJ began as a C++ rewrite of PTRAJ by Thomas E. Cheatham, III (Department of Medicinal Chemistry, University of Utah, Salt Lake City, UT, USA) and many routines from PTRAJ were adapted for use in CPPTRAJ, including code used in the following classes: Analysis_CrankShaft, Analysis_Statistics, Action_DNAionTracker, Action_RandomizeIons, Action_Principal, Action_Grid, GridAction, Action_Image, and ImageRoutines.

Contributors to CPPTRAJ

  • James Maier (Stony Brook University, Stony Brook, NY, USA) Code for calculating J-couplings (used in Action_Jcoupling).

  • Jason M. Swails (University of Florida, Gainesville, FL, USA) Action_LIE, Analysis_RunningAvg, Action_Volmap, Grid OpenDX output.

  • Jason M. Swails (University of Florida, Gainesville, FL, USA) Guanglei Cui (GlaxoSmithKline, Upper Providence, PA, USA) Action_SPAM.

  • Mark J. Williamson (Unilever Centre for Molecular Informatics, Department of Chemistry, Cambridge, UK) Action_GridFreeEnergy.

  • Hannes H. Loeffler (STFC Daresbury, Scientific Computing Department, Warrington, WA4 4AD, UK) Action_Density, Action_OrderParameter, Action_PairDist.

  • Crystal N. Nguyen (University of California, San Diego) Romelia F. Salomon (University of California, San Diego) Original Action_Gist.

  • Pawel Janowski (Rutgers University, NJ, USA) Normal mode wizard (nmwiz) output, original code for ADP calculation in Action_AtomicFluct.

  • Zahra Heidari (Faculty of Chemistry, K. N. Toosi University of Technology, Tehran, Iran) Original code for Analysis_Wavelet.

  • Chris Lee (University of California, San Diego) Support for processing force information in NetCDF trajectories.

  • Steven Ramsey (CUNY Lehman College, Bronx, NY) Enhancements to entropy calculation in original Action_Gist.

  • Amit Roy (University of Utah, UT) Code for the CUDA version of the 'closest' Action.

  • Andrew Simmonett (National Institutes of Health) Code for the reciprocal part of the particle mesh Ewald calculation (electrostatic and Lennard-Jones).

  • Christina Bergonzo (National Institute of Standards and Technology, Gaithersburg, MD) Fixes and improvements to nucleic acid dihedral angle definitions (DihedralSearch).

  • David S. Cerutti (Rutgers University, Piscataway, NJ, USA) Original code for the 'xtalsymm' Action.

Various Contributions

  • David A. Case (Rutgers University, Piscataway, NJ, USA)
  • Hai Nguyen (Rutgers University, Piscataway, NJ, USA)
  • Robert T. McGibbon (Stanford University, Stanford, CA, USA)

Code in CPPTRAJ that originated in PTRAJ

  • Holger Gohlke (Heinrich-Heine-University, Düsseldorf, Germany) Alrun N. Koller (Heinrich-Heine-University, Düsseldorf, Germany) Original implementation of matrix/vector functionality in PTRAJ, including matrix diagonalization, IRED analysis, eigenmode analysis, and vector time correlations.

  • Michael Crowley (University of Southern California, Los Angeles, CA, USA) Original code for dealing with truncated octahedral unit cells.

  • Viktor Hornak (Merck, NJ, USA) Original code for mask expression parser.

  • John Mongan (UCSD, San Diego, CA, USA) Original implementation of the Amber NetCDF trajectory format.

  • Hannes H. Loeffler (STFC Daresbury, Scientific Computing Department, Warrington, WA4 4AD, UK) Diffusion calculation code adapted for use in Action_STFC_Diffusion.

External libraries bundled with CPPTRAJ

  • CPPTRAJ makes use of the GNU readline library for the interactive command line.

  • CPPTRAJ uses the ARPACK library to calculate eigenvalues/eigenvectors from large sparse matrices.

  • CPPTRAJ uses the xdrfile library for reading XTC files; specifically a somewhat updated version from MDTRAJ that includes some bugfixes and enhancements. See src/xdrfile/README for details.

  • CPPTRAJ uses the GROMACS TNG library for reading TNG files. See sec/tng/README for details.

  • The reciprocal part of the PME calculation is handled by the helPME library by Andy Simmonett.

  • Support for reading DTR trajectories uses the VMD DTR plugin.

About

Biomolecular simulation trajectory/data analysis.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C++ 69.2%
  • C 22.8%
  • Fortran 4.3%
  • Shell 2.5%
  • Cuda 0.6%
  • Makefile 0.3%
  • Other 0.3%