Metadata-Version: 2.1
Name: NISP
Version: 1.2.0
Summary: The Nanocluster Interpolation Scheme Program (NISP) is designed to perform an interpolation scheme that gives idea of the types of perfect, closed-shell and open-shell clusters for a cluster at selected sizes.
Home-page: https://blogs.otago.ac.nz/annagarden/
Author: Geoffrey R. Weal, Dr. Anna L. Garden, Dr. Andreas Pedersen and Prof. Hannes Jónsson
Author-email: anna.garden@otago.ac.nz
License: GNU AFFERO GENERAL PUBLIC LICENSE
Download-URL: https://github.com/GardenGroupUO/NIS/archive/v1.2.0.tar.gz
Description: # The Nanocluster Interpolation Scheme Program (NISP)
        
        [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/NISP)](https://docs.python.org/3/)
        [![GitHub release (latest by date)](https://img.shields.io/github/v/release/GardenGroupUO/NISP)](https://github.com/GardenGroupUO/NISP)
        [![PyPI](https://img.shields.io/pypi/v/NISP)](https://pypi.org/project/NISP/)
        [![Conda](https://img.shields.io/conda/v/gardengroupuo/nisp)](https://anaconda.org/GardenGroupUO/nisp)
        [![Documentation Status](https://readthedocs.org/projects/nisp/badge/?version=latest)](https://nisp.readthedocs.io/en/latest/)
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/GardenGroupUO/NISP/main?urlpath=lab)
        [![GitHub](https://img.shields.io/github/license/GardenGroupUO/NISP)](https://www.gnu.org/licenses/agpl-3.0.en.html)
        
        The Nanocluster Interpolation Scheme Program (NISP) is designed to perform an interpolation scheme that can give an idea of perfect, closed-shell and open-shell clusters that can be formed with a given number of atoms. 
        
        This scheme is based on the work by Garden et al. as described in "Reassignment of ‘magic numbers’ for Au clusters of decahedral and FCC structural motifs", 
        
        	*A. L. Garden, A. Pedersen, H. Jónsson, “Reassignment of ‘magic numbers’ of decahdral and FCC structural motifs”, Nanoscale, 10, 5124-5132 (2018).*
        
        See https://doi.org/10.1039/C7NR09440J for more information on this scheme.
        
        **If you are new to NISP, it is recommended try it out by running NISP live on our interactive Jupyter+Binder page before you download it. On Jupyter+Binder, you can play around with NISP on the web. You do not need to install anything to try NISP out on Jupyter+Binder.** 
        
        **Click the Binder button below to try NISP out on the web! (The Binder page may load quickly or may take 1 or 2 minutes to load)**
        
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/GardenGroupUO/NISP/main?urlpath=lab)
        
        All the information about this program is found online at [nisp.readthedocs.io/en/latest/](https://nisp.readthedocs.io/en/latest/). It is recommended to read the installation page before using the algorithm ([nisp.readthedocs.io/en/latest/Installation.html](https://nisp.readthedocs.io/en/latest/Installation.html)). Note that you can install NISP through ``pip3`` and ``conda``. See the [installation instructions](https://nisp.readthedocs.io/en/latest/Installation.html) on how to do this. 
Keywords: nanoclusters,nanoparticles,clusters
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Unix
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
