Metadata-Version: 2.1
Name: grispy
Version: 0.0.4
Summary: Grid Search in Python
Home-page: https://github.com/mchalela/GriSPy
Author: ['Martin Chalela', 'Emanuel Sillero', 'Luis Pereyra', 'Alejandro Garcia']
Author-email: tinchochalela@gmail.com
License: MIT
Description: # GriSPy (Grid Search in Python)
        
        ![logo](https://github.com/mchalela/GriSPy/raw/master/res/logo_mid.png)
        
        
        [![PyPi Version](https://badge.fury.io/py/grispy.svg)](https://badge.fury.io/py/grispy)
        [![Build Status](https://travis-ci.org/mchalela/GriSPy.svg?branch=master)](https://travis-ci.org/mchalela/GriSPy)
        [![Documentation Status](https://readthedocs.org/projects/grispy/badge/?version=latest)](https://grispy.readthedocs.io/en/latest/?badge=latest)
        [![Coverage Status](https://coveralls.io/repos/github/mchalela/GriSPy/badge.svg?branch=master)](https://coveralls.io/github/mchalela/GriSPy?branch=master) 
        [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
        [![Python 3.6+](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/downloads/release/python-370/)
        [![ascl:1912.013](https://img.shields.io/badge/ascl-1912.013-blue.svg?colorB=262255)](http://ascl.net/1912.013)
        
        
        
        **GriSPy** is a regular grid search algorithm for quick nearest-neighbor lookup.
        
        This class indexes a set of k-dimensional points in a regular grid providing a fast aproach for nearest neighbors queries. Optional periodic boundary conditions can be provided for each axis individually.
        
        GriSPy has the following queries implemented:
        - **bubble_neighbors**: find neighbors within a given radius. A different radius for each centre can be provided.
        - **shell_neighbors**: find neighbors within given lower and upper radius. Different lower and upper radius can be provided for each centre.
        - **nearest_neighbors**: find the nth nearest neighbors for each centre.
        
        And the following method is available:
        - **set_periodicity**: define the periodicity conditions.
        
        --------------------------------
        
        ## Requirements
        
        You need Python 3.6 or later to run GriSPy. You can have multiple Python
        versions (2.x and 3.x) installed on the same system without problems.
        
        
        ## Standard Installation
        
        GriSPy is available at [PyPI](https://pypi.org/project/grispy/). You can install it via the pip command
        
                $ pip install grispy
        
        ## Development Install
        
        Clone this repo and then inside the local directory execute
        
                $ pip install -e .
                
        ## Citation
        
        If you use *GriSPy* in a scientific publication, we would appreciate
        citations to the following paper:
        
        > Chalela, M., Sillero, E., Pereyra, L., García, M. A., Cabral, J. B., Lares, M., & Merchán, M. (2019). 
        > GriSPy: A Python package for Fixed-Radius Nearest Neighbors Search. arXiv preprint arXiv:1912.09585.
        
        ### Bibtex
        
        ```bibtex
        @article{
          chalela2019grispy,
          title={GriSPy: A Python package for Fixed-Radius Nearest Neighbors Search},
          author={
            Chalela, Martin and Sillero, Emanuel and Pereyra, 
            Luis and Garc{\'\i}a, Mario Alejandro and Cabral, 
            Juan B and Lares, Marcelo and Merch{\'a}n, Manuel},
          journal={arXiv preprint arXiv:1912.09585},
          year={2019}
        }
        ```
        
        Full-text: https://ui.adsabs.harvard.edu/abs/2019arXiv191209585C/abstract
        
        
        ## Authors
        
        Martin Chalela (E-mail: tinchochalela@gmail.com),
        Emanuel Sillero, Luis Pereyra and Alejandro Garcia
        
Keywords: grispy,nearest,neighbors,search,grid
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
