Metadata-Version: 1.2
Name: intros-MaxEnt
Version: 0.9.91
Summary: A MaxEnt package with introspection for ecological niche modeling.
Home-page: https://wholetale.org
Author: Santiago Nunez-Corrales
Author-email: nunezco2@illinois.edu
License: LICENSE.txt
Description: intros-MaxEnt
        =============
        
        **The Whole Tale Project**
        
        Author: Santiago Nunez-Corrales
                (nunezco2@illinois.edu)
        
        
        **intros-MaxEnt** is a Python software package that provides an open
        implementation of the MaxEnt algorithm for ecological niche modeling
        as described in
        
            Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum
            entropy modeling of species geographic distributions.
            Ecological modelling, 190(3-4), 231-259.
        
        Our goal with this package is, scientifically, to help improve the
        modeling landscape in ecological niche modeling by making explicit the
        consequences of varying various parameters in MaxEnt based on
        biologically informed hypotheses.
        
        The packaged provides facilities for the following tasks:
        
        1. Importing georeferenced data from taxa records for modeling species
           distribution, as well as environmental variables data for locations
           compliant with WGS84 latitude-longitude coordinates.
        2. Executing the MaxEnt algorithm with inspection and reparametrization
           capabilities of models and outcomes.
        3. Analyzing and differentially comparing model outcomes including KML
           and PNG image generation at various resolutions.
        4. Packaging of model configurations and experiments for extended
           scientific replication.
        
        This package is also intended to be used in Jupyter Notebooks at The
        Whole Tale environment as an example of scientific reproducibility. The
        current software implementation was heavily informed by
        
            Merow, C., Smith, M. J., & Silander, J. A. (2013). A practical guide
            to MaxEnt for modeling species’ distributions: what it does, and why
            inputs and settings matter. Ecography, 36(10), 1058-1069.
        
        This code is part of The Whole Tale Summer Internship 2018.
        
Platform: UNKNOWN
Requires-Python: >3.4
