Skip to content

Latest commit

 

History

History
66 lines (52 loc) · 2.19 KB

README.md

File metadata and controls

66 lines (52 loc) · 2.19 KB

About

FastPCA is a PCA-calculator programmed in C++11 parallelized with OpenMP.

The FastPCA package is an implementation of the principal component analysis of large MD data sets, using either Cartesian atom coordinates, interatom distances or backbone dihedral angles as input coordinates. In particular, it features the dihedral angle PCA on a torus (dPCA+) by Sittel et al., 2017, which performs maximal gap shifting to treat periodic data correctly. It is optimized and parallelized with constant memory consumption for large data sets.

For fast matrix diagonalization, LAPACK is used (and needed, of course).

The project includes the 'xdrfile' library of GROMACS. Thus, you can use data files written as ASCII data as well as .xtc-trajectories.

For bug-reports just open an issue.

Happy Computing.

Licensing

The code is published "AS IS" under the simplified BSD license. For details, please see LICENSE.txt

If you use the code for published works, please cite as

  • F. Sittel et al., Principal component analysis on a torus: Theory and application to protein dynamics, J. Chem. Phys 147, 244101, 2017; DOI:10.1063/1.4998259

Installation

This package can be installed with conda via

    conda install fastpca -c conda-forge

If conda is not available, it can be compiled as well.

Compilation

Download this repo

    git clone https://github.com/moldyn/FastPCA.git

If gcc > 7.x.x is used, please use the following branch

    git clone --branch fix_gcc8 https://github.com/moldyn/FastPCA.git

Create a build-directory in the project root and change into that directory:

    mkdir build
    cd build

Run cmake, based on the underlying project:

    cmake ..

Hopefully, everything went right. If not, carefully read the error messages. Typical errors are missing dependencies...

If everything is o.k., run make (on multicore machines, use '-j' to parallelize compilation, e.g. 'make -j 4' for up to four parallel jobs):

    make

Now, you should find the 'fastca' binary in the 'src' folder.

Requirements

  • LAPACK
  • Boost (program_options), min. version 1.49
  • cmake, min. version 2.8
  • g++ <= 7.x.x (otherwise use fix_gcc8 branch)