Metadata-Version: 2.1
Name: geonomics
Version: 0.0.3
Summary: A package for landscape genomic simulation
Home-page: https://github.com/drewhart/geonomics
Author: Drew Ellison Hart
Author-email: drew.ellison.hart@gmail.com
License: UNKNOWN
Project-URL: Documentation, https://htmlpreview.github.io/?https://github.com/drewhart/geonomics/blob/master/doc/built/doc.html
Project-URL: Source, https://github.com/drewhart/geonomics
Description: *********
        Geonomics
        *********
        
        Forward-time, individual-based, landscape genomic simulation in Python.
        
        .. code-block:: python
        
                           #   ::::::          :::    :: :::::::::::#
                     #::::::    ::::   :::      ::    :: :: ::::::::::: ::#
                  #:::::::::     ::            ::   :::::::::::::::::::::::::#
                #::::::::::                      :::::::::: :::::: ::::::::  ::#
              #  : ::::  ::                    ::::  : ::    :::::::: : ::  :    #
             # GGGGG  EEEE: OOOOO   NN   NN   OOOOO   MM   MM IIIIII  CCCCC SSSSS #
            # GG     EE    OO   OO  NNN  NN  OO   OO  MM   MM   II   CC     SS     #
            # GG     EE   OO     OO NN N NN OO     OO MMM MMM   II   CC     SSSSSS #
            # GG GGG EEEE OO     OO NN  NNN OO     OO MM M MM   II   CC         SS #
            # GG   G EE    OO   OO  NN   NN  OO   OO  MM   MM   II   CC        SSS #
             # GGGGG  EEEE: OOOOO   NN   NN   OOOOO   MM   MM IIIIII  CCCCC SSSSS #
              #     :::::::::               :::::::::: ::              ::  :   : #
                #::   :::::                    :::::: :::             :::::::  #
                  #    :::                      :::::  ::              ::::: #
                     #  ::                      ::::                      #
                           #                                        #
                              #  :: ::    :::             #
        
        
        
        
        **Geonomics** allows users to build and run arbitrarily complex, forward-time,
        agent-based, and spatially explicit simulations for landscape genomics. It is
        designed to allow novice Python users to create sophisticated simulations with
        minimal code, while also allowing advanced users a high level of extensibility
        and customizability.
        
        We will continue to expand and add functionality in future versions. Please
        contact us with questions, suggestions, or requests!
        
        Main Features
        -------------
        The following is a short list of highlights. For the full monty, please see
        the `homepage <https://github.com/drewhart/geonomics>`_,
        the `docs <https://htmlpreview.github.io/?https://github.com/drewhart/geonomics/blob/master/doc/built/doc.html>`_,
        and the `original methods paper <PAPER_URL_HERE>`_.
        
            - a model object, which serves as the primary user interface and which
              contains all other model components
            - a landscape object consisting of an arbitrary number of environmental
              raster layers
            - a community object consisting of an arbitrary number of species objects,
              each consisting of an arbitrary number of individuals
            - an optional genomic-architecture object, upon which individuals' genomes
              are based
            - spatialized logistic growth regulating local population densities
            - the capability to model realistic movement and offspring dispersal
              across conductance surfaces
            - neutral and non-neutral evolution capabilities, with spatially contingent
              selection
            - demographic- and environmental-change capabilities
            - the capability to run an arbitrary number of iterations of a model
            - the capability to sample data and a variety of statistics at any desired
              timesteps during a model run
            - numerous visualization methods to aid in model design, exploration,
              analysis, and presentation
        
        
        Installation
        ------------
        
        Geonomics can be installed with `pip`:
        
        .. code-block:: python
        
            pip install geonomics
        
        
        Quickstart
        ----------
        For impatient beginners, the following code will run Geonomics' default model::
        
          >>> import geonomics as gnx
          >>> mod = gnx.run_default_model()
        
        This will build and run **geonomics**' default model, return its `Model` object
        as `mod`, and leave its parameters file in your current working directory under
        the name 'GNX_default_model_params.py'.
        
        For patient folks, the following diagrams should provide more insight, and the
        `documentation <https://htmlpreview.github.io/?https://github.com/drewhart/geonomics/blob/master/doc/built/doc.html>`_
        provides full details.
        
        
        Details
        -------
        
        Procedural Diagram
        ~~~~~~~~~~~~~~~~~~
        
        .. image:: ./img/procedural_diagram.jpg
        
        Users can run Geonomics models in as few as three steps.
        
        1. **Create and edit a parameters file**: After importing geonomics as `gnx`,
           users can run the function `gnx.make_parameters_file()` function, feeding in
           a series of arguments to indicate the desired number and type of landscape layers,
           number and parameterization of species, data and statistics to be recorded, and parameters
           file name. Users can then edit the default parameter values in the resulting file to parameterize
           their model. Within the parameters file, they have the option of referencing external files
           to be used by their model, including static raster files or directories of raster time series, as well
           as a CSV file defining a custom genomic architecture.
        
        2. **Use the parameters file to create a model**: After setting up their parameters file, users can
           call the `gnx.make_model()` function, providing their parameters file's name as an argument. This
           will create a new `gnx.Model` object, containing a `gnx.Landscape` with the defined number of layers,
           and a `gnx.Community` with the defined number of species composed of starting individuals. The landscape,
           species, and individuals will all be described by a number of characteristics, in accordance with the values
           defined in the parameters file.
        
        3. **Run the model**: Users can then call the model's `mod.run` or `mod.walk` methods, to either run their model
           to completion or run it manually for some number of time steps. Each time step will include, as applicable,
           movement, mating, mortality, environmental and demographic change, and data-writing operations. For more detail
           on these operations, see the conceptual diagram that follows.
        
        Conceptual Diagram
        ~~~~~~~~~~~~~~~~~~
        
        .. image:: ./img/conceptual_diagram.jpg
        
        Operations during the main phase of a Geonomics model run. In the center is a
        species on a multi-layer landscape that includes a selection layer (above) and
        a movement and carrying capacity layer (below). Surrounding the landscape is a
        flow-diagram of the major operations during a time step. Operations in dashed
        boxes are optional.
        
        - **movement**: During the movement stages (top-left), individuals move
          along movement vectors drawn from various distribution options.
        
        - **mating**: During the mating stage (top-right), an individual (purple outline) randomly
          chooses a mate (green outline) from all potential mates within its mating radius
          (dashed circle). The resulting offspring (dashed outline)  disperses from its
          parents' midpoint along a randomly drawn dispersal vector.
        
        - **mortality**: During the mortality stage (bottom-right), deaths are modeled as a Bernoulli
          process, with the probability of mortality being a product of density-dependence
          and selection on all traits.
        
        - **changes**: During the changes stage (bottom-left), demographic change events
          (not pictured) and environmental change events (represented as a
          series of change rasters corresponding to scheduled time steps,
          t1, t2, …, tn), take place.
        
        
        Disclaimer
        ----------
        **Geonomics** claims no affiliation with the philosophy and economic ideology
        `Georgism <https://en.wikipedia.org/wiki/Georgism>`_, sometimes referred to as
        'geonomics'. It is a portmanteau of **geo**\graphy and ge\ **nomics**.
        I just thought it sounded neat, and found it delightfully confusing.
        
Keywords: landscape genomics genetics ecology evolution simulation model environmental model agent-based
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.5
Description-Content-Type: text/x-rst
Provides-Extra: simulation on neutral landscape models
Provides-Extra: reading and writing of common raster data formats
