{ "info": { "author": "yc", "author_email": "yang.chen@scilifelab.se", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7" ], "description": "====\nfcsy\n====\n\n\n.. image:: https://img.shields.io/pypi/v/fcsy.svg\n :target: https://pypi.python.org/pypi/fcsy\n\n.. image:: https://img.shields.io/travis/nehcgnay/fcsy.svg\n :target: https://travis-ci.org/nehcgnay/fcsy\n\n\n\nA package for processing FCS files.\n\n\n* Free software: MIT license\n\nInstallation\n------------\n.. code:: python\n\n pip install fcsy\n\n\nUsage\n-----\n\nRead a fcs file to pandas DataFrame.\n\n.. code:: python\n\n from fcsy.fcs import read_fcs\n\n df = read_fcs('input_file')\n\nRead a fcs file with \"long name\"\n\n.. code:: python\n\n df = read_fcs('input_file', name_type='long')\n\n # or only read the names\n from fcsy.fcs import read_fcs_names\n\n long_names = read_fcs_names('input_file', name_type='long')\n\n\nWrite a data frame to fcs. df.columns is written to both short and long names of the fcs.\n\n.. code:: python\n\n from fcsy.fcs import write_fcs\n\n write_fcs(df, 'output_file')\n\n\nWrite to fcs with \"long name\". df.columns and long_names are written to short and long names of the fcs.\n\n.. code:: python\n\n write_fcs(df, 'output_file', long_names=['a','b','c'])\n\n\n\n\nCredits\n-------\n\nThis package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: 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