Metadata-Version: 1.1
Name: geospatial-learn
Version: 0.121
Summary: geospatial-learn is a Python module for using scikit-learn andxgb models with geo-spatial data, chiefly raster and vectorformats.
Home-page: https://github.com/Ciaran1981/geospatial-learn
Author: Ciaran Robb
Author-email: UNKNOWN
License: GPLv3+
Description: .. -*- mode: rst -*-
        
        .. |Python35| image:: https://img.shields.io/badge/python-3.5-blue.svg
        
        geospatial-learn
        ============
        
        geospatial-learn is a Python module for using scikit-learn and xgb models with geo-spatial data, chiefly raster and vector formats. 
        
        The module also contains various fuctionality for manipulating raster and vector data as well as some utilities aimed at processing Sentinel 2 data.
        
        The aim is to produce convenient, minimal commands for putting together geo-spatial processing chains using machine learning libs. Development will aim to expand the variety of libs/algorithms available for machine learning beyond the current complement.  
        
        
        Dependencies
        ~~~~~~~~~~~~
        
        geospatial-learn requires:
        
        - Python 3
        
        User installation
        ~~~~~~~~~~~~~~~~~
        
        At present the setup.py only installs some of the dependencies. An anaconda package is in the works, but until that is done please do the following. This assumes you have an anaconda installation with a python 3  root OR env.
        
        Linux - based
        ~~~~~~~~~~~~~~~~~
        
        Library & pypi install
        
        Step 1.
        
        - open a terminal and type:
        
        .. code-block:: bash
           
           pip install geospatial-learn
        
        OR
        
        - download the zip from here: 
        
          https://github.com/Ciaran1981/geospatial-learn/raw/master/archive/geospatial-learn-0.1.tar.gz
        
        
        - cd into the folder
        
        - open a terminal and type:
        
        .. code-block:: bash
            
           python setup.py install
        
        This will install the library and packages unavailable on anaconda.
        
        Step 2.
        
        Conda is very handy at managing packages, hence the 2 stage install, as some of these are external to python or themselves have multiple depends.
        
        Next, type the following (in the same terminal).
        
        .. code-block:: bash
        
           chmod +x install_conda_packages.sh
        
           bash ./install_conda_packages.sh
        
        All the appropriate anaconda packages will then install
        
        Windows - based
        ~~~~~~~~~~~~~~~~~   
        
        Commiserations, you are using Windows (hehe). This seems to work, though I have only tested on 1 machine. 
        
        Library & pypi install
        
        Step 1.
        
        - open a powershell/anaconda prompt and type:
        
        .. code-block:: bash
           
           pip install geospatial-learn
        
        OR
        
        - download the zip from here: 
        
          https://github.com/Ciaran1981/geospatial-learn/raw/master/archive/geospatial-learn-0.1.tar.gz
        
        - cd into the folder
        
        - open a powershell and type:
        
        .. code-block:: bash
            
           python setup.py install
        
        This will install the library and packages unavailable on anaconda.
        
        Step 2.
        
        Conda is very handy at managing packages, hence the 2 stage install, as some of these are external to python or themselves have multiple depends.
        
        Next, type the following (in the same terminal).
        
        .. code-block:: bash
        
           .\install_conda_packages.bat
        
        If you run into problems here, such as certain packages unavailable with Python 3.5/6, I suggest creating a conda environment with python 3.4, then following the above procedure. At the time of writing for example (31/08/17), gdal is not available in py3.5+ on windows anaconda and py3.6 on linux platforms.
        
        I have not provided xgboost instructions here, there are some on the native website along with ensuring the lib points to your python environment of choice. 
        
        Development
        -----------
        
        New contributors of all experience levels are welcome
        
        Useful links
        ~~~~~~~~~~~~~~~
        Here are some links to the principal libs used in geospatial-learn.
        
        https://github.com/scikit-learn/
        
        http://xgboost.readthedocs.io/en/latest/
        
        http://scikit-learn.org/stable/
        
        http://www.gdal.org/
        
        http://www.numpy.org/
        
        https://www.scipy.org/
        
        http://scikit-image.org/
        
        Submitting a Pull Request
        ~~~~~~~~~~~~~~~~~~~~~~~~~
        available soon
        
        Project History
        ---------------
        
        It is currently maintained voluntaliry by Dr Ciaran Robb, University of Leicester. The functionality was originally written as part of various research projects involving Earth observation & geo-spatial data. The module is at a very early stage at present and there is more material wrtten that has yet to be added (including docs!).     
        
        Help and Support
        ----------------
        
        available soon
        
        Citation
        ~~~~~~~~
        
        If you use geospatial-learn in a scientific publication, citations would be appreciated 
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Utilities
