.. pankus documentation master file, created by
   sphinx-quickstart on Fri Sep  7 22:16:10 2018.
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Welcome to pankus's documentation!
==================================

.. warning::
   This documentation is meant for software in active development

Pankus is meant as a collection of subpackages, under this name are available various spatial analyses libraries. Basic functionality of pankus package is meant to provide users with simple tools that might be combined into simulation models.

You can find here glossary, explained functions and tables as well as use cases for project structures.
Feel free to let us know if you think there is something missing ;)

If you are not equipped with a prepared network, it is advised to start with `network_generator` module followed by `route` module. Modules `analysis`, `intervening_opportunities` and `mst` allow to further operate on prepared networks. `data_journal` module serves as journal of executed actions and data results.

Installation
------------
Basic installation:

1. Python3.x and pip module are required
2. enter ``pip3 install -U pankus`` in command line terminal 

All the substantial packages are installed automatically

.. note:: additional documentation bundle installation for developers only:

   1. enter ``pip3 install sphinx`` in command line terminal
   2. enter ``pip3 install sphinx-bootstrap-theme`` in command line terminal

Terms
-------
.. toctree::
   :maxdepth: 1
   :glob:

   source/terms/terms

Tables
--------
.. toctree::
   :maxdepth: 1
   :glob:

   source/tables

Modules
---------
.. toctree::
   :maxdepth: 1
   :glob:

   source/modules/*

Examples of use
-----------------
Generating network and distances within it

.. code-block:: python

   #creating instance of Taurus Class, enabling progressbar and setting database to be created in memory
   T = Taurus(progressbar=True, database_name=":memory:")
   #generating network in specific shape in specified by the user size
   T.make_hexdiagonal_pattern_network(problem_size)
   #generating connections between pairs of points in the network
   T.generate_connections()
   #generating distances between pairs of origin-desination points from available connections
   T.distance()


Preparing network and running motion exchange simulation 

.. code-block:: python

   #creating specified by the user number of interval rings for each origin point
   T.build_uniform_rings(rings)
   #importing parameters of a model
   T.import_model_parameters()
   #calculating sum of destinations in rings
   T.ring_total()
   #calculating motion exchange
   T.motion_exchange()