<commit_before>.. image:: docs/_static/molyso-banner.png

molyso Readme
=============

.. image:: https://img.shields.io/pypi/v/molyso.svg
   :target: https://pypi.python.org/pypi/molyso

.. image:: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat
   :target: https://molyso.readthedocs.io/en/latest/

.. image:: https://img.shields.io/pypi/l/molyso.svg
   :target: https://opensource.org/licenses/BSD-2-Clause

.. image:: https://zenodo.org/badge/doi/10.5281/zenodo.53764.svg
   :target: https://dx.doi.org/10.5281/zenodo.53764

.. image:: https://zenodo.org/badge/doi/10.1371/journal.pone.0163453.svg
   :target: https://dx.doi.org/10.1371/journal.pone.0163453
   

Publication
-----------
When using *molyso* for scientific applications, cite our publication:

    <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME> (2016)
    Image-Based Single Cell Profiling:
    High-Throughput Processing of Mother Machine Experiments.
    PLoS ONE 11(9): e0163453. doi: 10.1371/journal.pone.0163453

It is available on the PLoS ONE homepage at `DOI: 10.1371/journal.pone.0163453 <https://dx.doi.org/10.1371/journal.pone.0163453>`_

Example Datasets
----------------
You can find example datasets (as used in the publication) deposited at zenodo `DOI: 10.5281/zenodo.53764 <https://dx.doi.org/10.5281/zenodo.53764>`_.

Documentation
-------------
Documentation can be built using sphinx, but is available online as well at `Read the Docs <https://molyso.readthedocs.io/en/latest/>`_.

License
-------
*molyso* is free/libre open source software under the 2-clause BSD License. See :doc:`license`

Prerequisites
-------------
*molyso* needs Python 3, if you are using Windows, we recommend WinPython_, as it contains the necessary modules already. Pick a >=3.4 64 bit version.

.. _WinPython: https://winpython.github.io

If you are using Ubuntu, install the necessary packages via:

.. code-block:: bash

    > sudo apt-get install python3 python3-pip python3-numpy python3-scipy python3-matplotlib


Ways to install molyso
----------------------

There are three different ways to install molyso:

Via the Python Package Index (recommended)
##########################################

.. code-block:: bash

    > pip3 install --user molyso

Via the Python Package Index with the github Version
####################################################

.. code-block:: bash

    > pip3 install --user git+https://github.com/modsim/molyso

From github
###########

.. code-block:: bash

    > git clone https://github.com/modsim/molyso
    > cd molyso
    > python3 setup.py install --user

First Steps
-----------
*molyso* is packaged as a Python module, to run it, just use:

.. code-block:: bash

    > python3 -m molyso

And you will be greeted by the help screen of molyso:

.. code-block:: none<commit_msg>another method to install molyso from github without git installed, and some clarifications for installation procedures<commit_after>.. image:: docs/_static/molyso-banner.png

molyso Readme
=============

.. image:: https://img.shields.io/pypi/v/molyso.svg
   :target: https://pypi.python.org/pypi/molyso

.. image:: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat
   :target: https://molyso.readthedocs.io/en/latest/

.. image:: https://img.shields.io/pypi/l/molyso.svg
   :target: https://opensource.org/licenses/BSD-2-Clause

.. image:: https://zenodo.org/badge/doi/10.5281/zenodo.53764.svg
   :target: https://dx.doi.org/10.5281/zenodo.53764

.. image:: https://zenodo.org/badge/doi/10.1371/journal.pone.0163453.svg
   :target: https://dx.doi.org/10.1371/journal.pone.0163453
   

Publication
-----------
When using *molyso* for scientific applications, cite our publication:

    <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME> (2016)
    Image-Based Single Cell Profiling:
    High-Throughput Processing of Mother Machine Experiments.
    PLoS ONE 11(9): e0163453. doi: 10.1371/journal.pone.0163453

It is available on the PLoS ONE homepage at `DOI: 10.1371/journal.pone.0163453 <https://dx.doi.org/10.1371/journal.pone.0163453>`_

Example Datasets
----------------
You can find example datasets (as used in the publication) deposited at zenodo `DOI: 10.5281/zenodo.53764 <https://dx.doi.org/10.5281/zenodo.53764>`_.

Documentation
-------------
Documentation can be built using sphinx, but is available online as well at `Read the Docs <https://molyso.readthedocs.io/en/latest/>`_.

License
-------
*molyso* is free/libre open source software under the 2-clause BSD License. See :doc:`license`

Prerequisites
-------------
*molyso* needs Python 3, if you are using Windows, we recommend WinPython_, as it contains the necessary modules already. Pick a >=3.4 64 bit version.

.. _WinPython: https://winpython.github.io

If you are using Ubuntu, install the necessary packages via:

.. code-block:: bash

    > sudo apt-get install python3 python3-pip python3-numpy python3-scipy python3-matplotlib


Ways to install molyso
----------------------

There are different ways to install molyso (although not always perfectly stable, usually the latest github version is the best choice):

Via the Python Package Index (release version)
##############################################

.. code-block:: bash

    > pip3 install --user molyso

Via the pip with the github Version
###################################

.. code-block:: bash

    > pip3 install --user git+https://github.com/modsim/molyso

Via the pip with the github Version (alternate, e.g. for Windows, no git required)
##################################################################################

.. code-block:: bash

    > pip3 install --user https://github.com/modsim/molyso/archive/master.zip

From github
###########

.. code-block:: bash

    > git clone https://github.com/modsim/molyso
    > cd molyso
    > python3 setup.py install --user

First Steps
-----------
*molyso* is packaged as a Python module, to run it, just use:

.. code-block:: bash

    > python3 -m molyso

And you will be greeted by the help screen of molyso:

.. code-block:: none
{'fraction_non_alphanumeric': 0.19351653776534475, 'fraction_numerical': 0.04591081125555373, 'mean_word_length': 3.332145402708482, 'pattern_counts': {'":': 0, '<': 23, '<?xml version=': 0, '>': 40, 'https://': 33, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '5271373', 'n_tokens_mistral': 2198, 'n_tokens_neox': 1906, 'n_words': 552}