Coder Social home page Coder Social logo

gloria's Introduction

Gloria version 0.3 May 16th, 2017

gloria.py is a Python program to identify areas of endemism from geographic distribution data, using Hidden Markov Random Fields.

Input is a csv file containing localities (geographic coordinates) of the taxa to analyze (format specification under INSTRUCTIONS).

Output is a log file and several geojson files (basegrid and one for each area of endemism).

REQUIREMENTS

Currently, Gloria is only supported in Linux and OS operating systems. Either case it is required:

  • a Python 2.7 interpreter.

  • a C compiler.

  • attention to detail.

INSTALLING

After download, simply execute python setup.py test to test the source distribution. To fully install the program type python setup.py install.

Installation can alternatively be done through pip: pip install <Gloria tar file>.

INSTRUCTIONS

The input file should conform to the following directions:

  1. Data should be organize in three columns: taxon name, longitud, and latitude.

  2. The first row should contain the headers "Taxon", "Latitude", and "Longitude".

  3. Longitude and latitude should be in decimal format, with periods used as decimal marks.

  4. Datapoints belonging to the same taxa should have the same string as "Taxon".

Example:

Taxon_name Latitude Longitude
Sp_0 -95.67 1.44
Sp_0 -96.07 0.84
Sp_1 -85.61 -1.68
Sp_1 -75.87 4.12

which in raw csv format should be:

Taxon_name,Latitude,Longitude
Sp_0,-95.67,1.44
Sp_0,-96.07,0.84
Sp_1,-85.61,-1.68
Sp_1,-75.87,4.12

WARNINGS

Poorly curated datasets usually lead to ambiguous results.

As of version 0.3, this program does not include a graphical interface.

COPYRIGHT INFORMATION AND LICENSE

Copyright 2016-2017 Nelson R. Salinas

This file is part of Gloria.

Gloria is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

Gloria is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with Gloria. If not, see http://www.gnu.org/licenses/.

CONTACT

Nelson R. Salinas [email protected]

CITATION

If you use this program, please cite:

Salinas, N. R. and W. C. Wheeler. Statistical Modeling of Distribution Patterns: a Markov Random Field Implementation and its Application on Areas of Endemism. In preparation.

gloria's People

Contributors

nrsalinas avatar

Watchers

James Cloos avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.