{ "info": { "author": "Corentin Le Guillou", "author_email": "corentin.le-guillou@univ-lille1.fr", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Physics" ], "description": "QUANTORXS : QUANTification of ORganics by X-ray Spectrosocopy\n=============================================================\n\nQUANTORXS is an open-source program to automatically analyze XANES\nspectra at Carbon, Nitrogen and Oxygen K-edges edges to quantify the\nconcentration of functional groups and the elemental ratios (N/C and\nO/C). It is based on a novel quantification method published in\n`Analytical\nchemistry `__.\n\nQUANTORXS performs the following tasks automatically:\n\n- Load the data from the file(s)\n- Remove background\n- Normalize the spectra\n- Generate a model of the fine structure a fit it to the experimental\n data\n- Calculate the functional groups abundances and elemental rations from\n the results of the fit\n- Generate an Excel file and multiple figures with the results and\n normalised spectra files.\n\nThis is illustrated in more detail in the following diagram:\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/Program_sequence.jpg\n :alt: Sequence of operations performed by the program\n\n Alt text\n\nQUANTORXS is designed to work without any user input other than the\nexperimental spectra. Users willing to modify the details of the\nquantification can download the code from its `GitHub\nrepository `__.\n\nThe code was initially written by `Corentin Le\nGuillou `__.\n`Francisco de la\nPe\u00f1a `__\ncreated the command line and graphical user interfaces.\n\nInstalling QUANTORXS.\n---------------------\n\nQUANTORXS is written in the Python programming languague and is\navailable from `pypi `__. It runs in\nany operating system with the Python programming language installed.\n\nTo install QUANTORXS execute the following in a terminal:\n\n.. code:: bash\n\n pip install quantorxs\n\nStep-by-step installation instructions for Windows users\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nIf you are new to Python we reccomend you to install the opensource and\nfree `Anaconda Python\ndistribution `__ for your platform\nfirst. Afterwards, from the Microsoft Windows ``Start Menu``, open\n\u201canaconda prompt\u201d as in the image below:\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/Anaconda_prompt.jpg\n :alt: where to find anaconda prompt\n\n Alt text\n\nThen type the following and press ``Enter`` (requires connection to the\ninternet):\n\n.. code:: bash\n\n pip install quantorxs\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/Install_command_line.jpg\n :alt: The install command line\n\n Alt text\n\nThat\u2019s all! QUANTORXS should now be installed in your system.\n\nStarting the QUANTORXS Graphical User Interface\n-----------------------------------------------\n\nTo start the graphical interface execute the ``quantorxs_gui`` e.g.\u00a0a\nterminal. Alternatively, Windows users can start it by searching for the\nexecutable file \u201cquantorxs_gui\u201d in the ``Start Menu`` and launching it\nas shown in the image below.\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/Start_quantorxs.jpg\n :alt: where to find quantorxs\n\n Alt text\n\nHow to use the graphical interface\n----------------------------------\n\nThe program is designed to process several spectra at once. All source\nspectra should be assembled in one folder. QUANTORXS reads only the\nformat produced by\n`aXis2000 `__\n\n- Click on the ``Choose data directory`` button and select the folder\n containing the source spectra.\n- Type in an output folder name (relative to the data directory) to\n store the results of the analysis. The default is\n ``QUANTORXS results``.\n- Make sure that the ``demo`` box is not checked. If checked, it uses\n default files as input to produce an example of the output files.\n- Select the format of the figure output (the default is SVG)\n- Set the ``offset`` if required to compensate from any energy\n misalignment (e.g.\u00a0from poorly calibrated monochromator) *common to\n all spectra*.\n- Click the ``Run`` button and wait until the analysis is completed\n (usually a few secondes per spectrum).\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/Quantorxs_gui.jpg\n :alt: The graphical user interface\n\n Alt text\n\nDescription of the output files\n-------------------------------\n\nThe output folder will be created in the folder from which the data have\nbeen taken. An .xls result file and two different sub-folders are\ncreated:\n\na .xls file contains several sheets:\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n- The fitting parameters\n- The quantified data (aromatic, ketones, aliphatics, carboxylics; as\n well as N/C and O/C ratios) and some related plots\n- The spectra at the C-K edge normalized by the area ratio method\n- The spectra at the N-K edge normalized by the area ratio method\n- The spectra at the O-K edge normalized by the area ratio method\n- The fitted heights of the Gaussians for the area-based normalization\n at the C-K edge\n- The fitted heights of the Gaussians for the area-based normalization\n at the N-K edge\n- The fitted heights of the Gaussians for the area-based normalization\n at the O-K edge\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/excel_Tab1.jpg\n :alt: Analysis parameters\n\n Alt text\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/excel_Tab2.jpg\n :alt: Quantified data\n\n Alt text\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/excel_Tab3.jpg\n :alt: normalized spectra\n\n Alt text\n\n.. figure:: https://github.com/CorentinLG/QuantORXS/raw/master/Images/excel_Tab4.jpg\n :alt: fitted gaussians\n\n Alt text\n\nA folder containing the .txt files of each normalized spectrum\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nA folder with figures displaying:\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n- The cross-section fit\n- The normalized spectra\n- The deconvolution (all gaussians included)", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/corentinlg/quantorxs", "keywords": "XANES abundance quantification", "license": "GPLv3", "maintainer": "", "maintainer_email": "", "name": "quantorxs", "package_url": "https://pypi.org/project/quantorxs/", "platform": "", "project_url": "https://pypi.org/project/quantorxs/", "project_urls": { "Homepage": "https://github.com/corentinlg/quantorxs" }, "release_url": "https://pypi.org/project/quantorxs/0.1.1/", "requires_dist": null, "requires_python": "", "summary": "XANES quantification of functional group abundances", "version": "0.1.1" }, "last_serial": 4007584, "releases": { "0.1": [ { "comment_text": "", "digests": { "md5": "3ce691043900d8d9114a9e519ff0a2c4", "sha256": "9b178ebedd1c8a87325633dc471c29a0abd847de9b3ef3990fd94b03565dbc49" }, "downloads": -1, "filename": "quantorxs-0.1.tar.gz", "has_sig": false, "md5_digest": "3ce691043900d8d9114a9e519ff0a2c4", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 78467, "upload_time": "2018-05-28T15:26:47", "url": "https://files.pythonhosted.org/packages/33/ba/9bd19353bc8044d3392beabe30e22fdae9a043f7c55e6cd381da5b8043b5/quantorxs-0.1.tar.gz" } ], "0.1.1": [ { "comment_text": "", "digests": { "md5": "990902ae6c2e23fb1573c1ec2109eac7", "sha256": "b6164c563d3b926c3351cc03b41f2a6c418329d1ea7f2807c5d917de3bca9032" }, "downloads": -1, "filename": "quantorxs-0.1.1.tar.gz", "has_sig": false, "md5_digest": "990902ae6c2e23fb1573c1ec2109eac7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 78194, "upload_time": "2018-06-27T13:53:25", "url": "https://files.pythonhosted.org/packages/65/d4/6b764ed5fbd8fe319cb6a3f654d4a87ed6e01c625181b8ab1f2775d6151e/quantorxs-0.1.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "990902ae6c2e23fb1573c1ec2109eac7", "sha256": "b6164c563d3b926c3351cc03b41f2a6c418329d1ea7f2807c5d917de3bca9032" }, "downloads": -1, "filename": "quantorxs-0.1.1.tar.gz", "has_sig": false, "md5_digest": "990902ae6c2e23fb1573c1ec2109eac7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 78194, "upload_time": "2018-06-27T13:53:25", "url": "https://files.pythonhosted.org/packages/65/d4/6b764ed5fbd8fe319cb6a3f654d4a87ed6e01c625181b8ab1f2775d6151e/quantorxs-0.1.1.tar.gz" } ] }