SAGA_optimize
=============
.. image:: https://img.shields.io/pypi/l/SAGA_optimize.svg
:target: https://choosealicense.com/licenses/bsd-3-clause-clear/
:alt: License information
.. image:: https://img.shields.io/pypi/v/SAGA_optimize.svg
:target: https://pypi.org/project/SAGA_optimize
:alt: Current library version
.. image:: https://img.shields.io/pypi/pyversions/SAGA_optimize.svg
:target: https://pypi.org/project/SAGA_optimize
:alt: Supported Python versions
.. image:: https://api.travis-ci.org/MoseleyBioinformaticsLab/SAGA_optimize.svg?branch=master
:target: https://travis-ci.org/MoseleyBioinformaticsLab/SAGA_optimize
:alt: Travis CI status
`SAGA_optimize` is a novel type of combined simulated annealing and genetic algorithm
used to find the optimal solutions to a set of parameters based on a given energy
function calculated using the set of parameters.
Citation
~~~~~~~~
Please cite the GitHub repository until our manuscript is accepted for
publications: https://github.com/MoseleyBioinformaticsLab/SAGA_optimize.git
Installation
~~~~~~~~~~~~
`SAGA_optimize` runs under Python 3.6+ and is available through python3-pip.
Install via pip or clone the git repo and install the following dependencies
and you are ready to go!
Install on Linux
----------------
Pip installation
................
.. code:: bash
python3 -m pip install SAGA-optimize
GitHub Package installation
...........................
Make sure you have git_ installed:
.. code:: bash
git clone https://github.com/MoseleyBioinformaticsLab/SAGA_optimize.git
Dependecies
...........
`SAGA_optimize` requires the following Python libraries:
* JSONPickle_ for saving Python objects in a JSON serializable form and outputting to a file.
Quickstart
~~~~~~~~~~
.. code:: python
>>> import SAGA_optimize
>>> saga = SAGA_optimize.SAGA(stepNumber=100000, temperatureStepSize=100, startTemperature=0.5,
alpha=1, direction=-1, energyCalculation=energyCalculation, crossoverRate=0.5,
mutationRate=3, annealMutationRate=1, populationSize=20) # SAGA instance creation.
>>> saga.addElementDescriptions(SAGA_optimize.ElementDescription(low=0, high=10),
SAGA_optimize.ElementDescription(low=0, high=10),
SAGA_optimize.ElementDescription(low=0, high=10),
SAGA_optimize.ElementDescription(low=0, high=10),
SAGA_optimize.ElementDescription(low=0, high=10)) # Add optimized parameters.
>>> optimized_population = saga.optimize() # the population returned after the opitimization.
.. note:: Read the User Guide and the ``SAGA_optimize`` Tutorial on ReadTheDocs_ to learn more and to see code examples on using the ``SAGA_optimize`` as a library.
License
~~~~~~~
Made available under the terms of The Clear BSD License. See full license in LICENSE_.
Authors
~~~~~~~
* **Huan Jin**
* **Hunter N.B. Moseley**
.. _ReadTheDocs: https://saga-optimize.readthedocs.io/en/latest/
.. _jsonpickle: https://jsonpickle.github.io/
.. _git: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git/
.. _LICENSE: https://choosealicense.com/licenses/bsd-3-clause-clear/
