Metadata-Version: 2.1
Name: porems
Version: 0.2.3
Summary: Pore Generator for Molecular Simulations.
Home-page: https://github.com/Ajax23/PoreMS
Author: Hamzeh Kraus
Author-email: kraus@itt.uni-stuttgart.de
License: UNKNOWN
Description: # PoreMS: A Pore Generator for Molecular Simulations
        
        [![PyPI Version](https://img.shields.io/badge/PyPI-0.2.2-orange)](https://pypi.org/project/porems/)
        [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://github.com/Ajax23/PoreMS/blob/master/LICENSE)
        [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5675066.svg)](https://doi.org/10.5281/zenodo.5675066)
        [![Build Status](https://github.com/Ajax23/PoreMS/actions/workflows/workflow.yml/badge.svg)](https://github.com/Ajax23/PoreMS/actions/workflows/workflow.yml)
        [![codecov](https://codecov.io/gh/Ajax23/PoreMS/branch/master/graph/badge.svg)](https://codecov.io/gh/Ajax23/PoreMS)
        [![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/Ajax23/PoreMS.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/Ajax23/PoreMS/context:python)
        
        ## Documentation
        
        Online documentation is available at [ajax23.github.io/PoreMS](https://ajax23.github.io/PoreMS/).
        
        The docs include an example for generating [molecules](https://ajax23.github.io/PoreMS/molecule.html) and [pores](https://ajax23.github.io/PoreMS/pore.html), and an [API reference](https://ajax23.github.io/PoreMS/api.html). Visit [process](https://ajax23.github.io/PoreMS/process.html) for an overview of the programs operating principle.
        
        An examplary [workflow](https://ajax23.github.io/PoreMS/workflow.html) has been provided for using the PoreMS package to create a pore system and run molecular dynamics simulation using [Gromacs](http://www.gromacs.org/).
        
        ## Dependencies
        
        PoreMS supports Python 3.5+.
        
        Installation requires [numpy](https://numpy.org/), [pandas](https://pandas.pydata.org/) and [matplotlib](https://matplotlib.org/).
        
        
        ## Installation
        
        The latest stable release (and older versions) can be installed from PyPI:
        
            pip install porems
        
        You may instead want to use the development version from Github:
        
            pip install git+https://github.com/ajax23/porems.git#egg=porems
        
            pip install git+https://github.com/ajax23/porems.git@develop#egg=porems
        
        Or download the repository and install in the top directory via:
        
            pip install .
        
        
        ## Testing
        
        To test porems, run the test in the test directory.
        
        
        ## Development
        
        PoreMS development takes place on Github: [www.github.com/Ajax23/PoreMS](https://github.com/Ajax23/PoreMS)
        
        Please submit any reproducible bugs you encounter to the [issue tracker](https://github.com/Ajax23/PoreMS/issues).
        
        
        ## How to Cite PoreMS
        
        When citing PoreMS please use the following: **Kraus et al., Molecular Simulation, 2021, DOI: [10.1080/08927022.2020.1871478](https://doi.org/10.1080/08927022.2020.1871478)**
        
        Additionaly, to assure reproducability of the generated pore systems, please cite the **Zenodo DOI** corresponding to the used PoreMS version. (Current DOI is listed in the badges.)
        
        ## Published Work
        * Kraus et al., 2021. PoreMS: a software tool for generating silica pore models with user-defined surface functionalisation and pore dimensions. Molecular Simulation, 47(4), pp.306-316, doi:[10.1080/08927022.2020.1871478](https://doi.org/10.1080/08927022.2020.1871478).
          - Data-Repository: doi:[10.18419/darus-1170](https://doi.org/10.18419/darus-1170)
        * Ziegler et al., 2021. Confinement Effects for Efficient Macrocyclization Reactions with Supported Cationic Molybdenum Imido Alkylidene N-Heterocyclic Carbene Complexes. ACS Catalysis, 11(18), pp. 11570-11578, doi:[10.1021/acscatal.1c03057](https://doi.org/10.1021/acscatal.1c03057)
          - Data-Repository: doi:[10.18419/darus-1752](https://doi.org/10.18419/darus-1752)
        * Kobayashi et al., 2021. Confined Ru-catalysts in a Two-phase Heptane/Ionic Liquid Solution: Modeling Aspects. ChemCatChem, 13(2), pp.739-746, doi:[10.1002/cctc.202001596](https://doi.org/10.1002/cctc.202001596).
          - Data-Repository: doi:[10.18419/darus-1138](https://doi.org/10.18419/darus-1138)
        * Ziegler et al., 2019. Olefin Metathesis in Confined Geometries: A Biomimetic Approach toward Selective Macrocyclization. Journal of the American Chemical Society, 141(48), pp.19014-19022, doi:[10.1021/jacs.9b08776](https://doi.org/10.1021/jacs.9b08776).
          - Data-Repository: doi:[10.18419/darus-477](https://doi.org/10.18419/darus-477)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
