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        "author": "Dominic Davis-Foster",
        "author_email": "dominic@davis-foster.co.uk",
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        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: End Users/Desktop",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v2 (GPLv2)",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Programming Language :: Python :: 3 :: Only",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Education",
            "Topic :: Scientific/Engineering :: Bio-Informatics",
            "Topic :: Scientific/Engineering :: Chemistry",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "************\nPyMassSpec\n************\n\n.. image:: https://travis-ci.org/domdfcoding/pymassspec.svg?branch=master\n    :target: https://travis-ci.org/domdfcoding/pymassspec\n    :alt: Build Status\n.. image:: https://readthedocs.org/projects/pymassspec/badge/?version=latest\n    :target: https://pymassspec.readthedocs.io/en/latest/?badge=latest\n    :alt: Documentation Status\n.. image:: https://img.shields.io/pypi/v/pymassspec.svg\n    :target: https://pypi.org/project/pymassspec/\n    :alt: PyPI\n.. image:: https://img.shields.io/pypi/pyversions/pymassspec.svg\n    :target: https://pypi.org/project/pymassspec/\n    :alt: PyPI - Python Version\n.. image:: https://coveralls.io/repos/github/domdfcoding/pymassspec/badge.svg?branch=master\n    :target: https://coveralls.io/github/domdfcoding/pymassspec?branch=master\n    :alt: Coverage\n\n\nA Python toolkit for processing of chromatography--mass spectrometry data\n\nPyMassSpec is a Python_ package for processing gas chromatography-mass spectrometry data.\nPyMassSpec provides a framework and a set of components for rapid development and testing of methods for processing of chromatography--mass spectrometry data.\nPyMassSpec can be used interactively through the Python shell, or the functions can be collected into scripts when it is preferable to perform data processing in the batch mode.\n\n|\n\nOriginally by Andrew Isaac, Sean O'Callaghan and Vladimir Liki\u0107\n\nThe original publication can be found here: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-13-115\n\n\nForked from the original PyMS Repository: https://github.com/ma-bio21/pyms.\n\nThe original project seems to have been abandoned as there has been no activity in 18 months.\n\n\n.. contents:: Table of Contents\n\n\n\nThe PyMassSpec project\n=========================\n\nThe directory structure of PyMassSpec is as follows:\n\n.. code-block:: text\n\n    /\n    \u251c\u2500\u2500 pyms:      The PyMassSpec code\n    \u2502\n    \u251c\u2500\u2500 pyms-data: Example GC-MS data files\n    \u2502\n    \u251c\u2500\u2500 pyms-demo: Examples of how to use PyMassSpec\n    \u2502\n    \u251c\u2500\u2500 tests: pytest tests\n    \u2502\n    \u2514\u2500\u2500 UserGuide: Sphinx source for documentation\n\nFeatures\n=========\n\nInstallation\n==============\n\nPyMassSpec can be installed with the following command:\n\n.. code-block:: bash\n\n    $ pip --user install PyMassSpec\n\nThis will also install the following dependencies:\n\n.. code-block:: bash\n\n    numpy >= 1.16.2\n    scipy >= 1.2.1\n    pymzml >= 2.2.1\n    matplotlib >= 3.0.2\n    openpyxl >= 2.6.2\n    netCDF4 >= 1.5.0\n    biopython >= 1.74\n    deprecation >= 2.0.6\n\n\nPyMassSpec also requires 'mp4py', installation instructions for which can be found at: https://mpi4py.readthedocs.io/en/stable/\n\n\nUsage\n=======\n\nA tutorial illustrating various PyMassSpec features in detail is provided\nin subsequent chapters of this User Guide. The commands executed\ninteractively are grouped together by example, and can be found\n`here <pyms_demo_>`__.\n\n.. If you are viewing this source, the examples can be found in the pyms-demo directory, and the data files in pyms-data\n\nThe data used in the PyMassSpec documentation and examples is available\n`here <datafiles_>`__.\n\nIn the \"`Demos and Examples <pyms_demo_>`__\" section there\nis a page corresponding to each example, coded with the chapter number\n(ie. \"`pyms-demo/20a/`\" corresponds to the Example 20a, from Chapter 2).\n\nEach example has a script named 'proc.py' which contains the commands given in the example.\nThese scripts can be run with the following command:\n\n.. code-block:: bash\n\n    $ python3 proc.py\n\nExample processing GC-MS data\n-------------------------------\n\nDownload the file ``gc01_0812_066.jdx`` and save it in the folder ``data``.\nThis file contains GC-MS data in the the JCAMP-DX format.\n\nFirst the raw data is loaded:\n\n    >>> from pyms.GCMS.IO.JCAMP import JCAMP_reader\n    >>> jcamp_file = \"data/gc01_0812_066.jdx\"\n    >>> data = JCAMP_reader(jcamp_file)\n    -> Reading JCAMP file 'Data/gc01_0812_066.jdx'\n    >>> data\n    <pyms.GCMS.Class.GCMS_data at 0x7f3ec77da0b8>\n\nThe intensity matrix object is then built by binning the data:\n\n    >>> from pyms.IntensityMatrix import build_intensity_matrix_i\n    >>> im = build_intensity_matrix_i(data)\n\nIn this example, we show how to obtain the dimensions of the\nnewly created intensity matrix, then loop over all ion chromatograms,\nand for each ion chromatogram apply Savitzky-Golay noise filter\nand tophat baseline correction:\n\n    >>> n_scan, n_mz = im.size\n    >>> from pyms.Noise.SavitzkyGolay import savitzky_golay\n    >>> from pyms.TopHat import tophat\n    >>> for ii in range(n_mz):\n    ...     print(\"working on IC\", ii)\n    ...     ic = im.get_ic_at_index(ii)\n    ...     ic1 = savitzky_golay(ic)\n    ...     ic_smooth = savitzky_golay(ic1)\n    ...     ic_base = tophat(ic_smooth, struct=\"1.5m\")\n    ...     im.set_ic_at_index(ii, ic_base)\n\nThe resulting noise and baseline corrected ion chromatogram is saved back into the intensity matrix.\n\nFurther examples can be found in the `documentation`_\n\nContributing\n==============\n\nContributions are very welcome. Tests can be run with `pytest`_. Please\nensure the coverage is at least .. image:: https://coveralls.io/repos/github/domdfcoding/pymassspec/badge.svg?branch=master\nbefore you submit a pull request.\n\nFor further information see the section `Contributing to PyMassSpec`_\n\nLicense\n=========\nPyMassSpec is Free and Open Source software released under the `GNU General Public License version 2 <GPL_>`__.\n\n\nIssues\n========\n\nIf you encounter any problems, please `file an issue`_ along with a\ndetailed description.\n\n\n.. _`documentation`: https://pymassspec.readthedocs.io\n.. _`Contributing to PyMassSpec`: https://pymassspec.readthedocs.io/en/master/Contributing/Contributing.html\n.. _`pytest`: https://pytest.org/\n.. _`file an issue`: https://github.com/domdfcoding/pymassspec/issues\n.. _Python: https://www.python.org/\n.. _GPL: https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html\n\n\n.. _pyms_demo: https://pymassspec.readthedocs.io/en/master/pyms-demo/introduction.html#pyms-demo\n.. _datafiles: https://pymassspec.readthedocs.io/en/master/pyms-demo/data-files.html\n\n\n\n",
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