PyFraME 0.1.1

PyFraME: Python tools for Fragment-based Multiscale Embedding

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Description

PyFraME is a Python package that provides tools for setting up and running fragment-based multiscale embedding calculations. The aim is to provide tools that can automatize the workflow of such calculations in a flexible manner.

The typical workflow is as follows:

1. a part of the total molecular system is chosen as the core region which is typically treated a high level of theory

2. the remainder is split into a number of regions each of which can be treated at different levels of theory

3. each region (except the core) is divided into fragments that consist of either small molecules or parts of larger molecules that have been fragmented into smaller computationally manageable fragments

4. a calculation is run on each fragment to obtain fragment parameters (if necessary)

5. all fragment parameters of all regions are assembled and constitute the embedding potential

6. a final calculation is run on the core region using the embedding potential to model the effect from the remainder of the molecular system

How to cite

To cite PyFraME please use a format similar to the following

“J. M. H. Olsen, PyFraME: Python tools for Fragment-based Multiscale Embedding (version 0.1.0), 2017, https://doi.org/10.5281/zenodo.293765”

where the version and DOI should of course correspond to the actual version that was used. A possible BibTeX entry could be:

@misc{pyframe,
      author = {Olsen, J. M. H.},
      title = {{PyFraME}: {P}ython tools for {F}ragment-based {M}ultiscale {E}mbedding (version 0.1.0)},
      year = {2017},
      note = {https://doi.org/10.5281/zenodo.293765}}

Alternatively, BibTeX and other formats can be generated by Zenodo.

Requirements

To use PyFraME you need:

• Python 3

• NumPy

• Numba

For certain functionality you will need one or more of the following:

• Dalton

• LoProp for Dalton

• Molcas 8

To run the test suite you need:

• nose

or

• pytest

Installation

The source can be downloaded from GitLab or Zenodo. Alternatively, it can be installed from PyPI:

pip install pyframe

Alternatively, it can be cloned from the repository:

git clone https://gitlab.com/FraME-projects/PyFraME.git

The package is installed by running:

python setup.py install

from the PyFraME root directory. You may wish to add --user in the last line if you do not have root access / sudo rights. Note that this will install NumPy and Numba if they are not installed already.

Tests

To run the test suite type:

nosetests

or:

pytest

from the PyFraME root directory.