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    "info": {
        "author": "Gavin Burnell",
        "author_email": "g.burnell@leeds.ac.uk",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Physics"
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        "description": ".. image:: https://travis-ci.org/stonerlab/Stoner-PythonCode.svg?branch=master\n   :target: https://travis-ci.org/stonerlab/Stoner-PythonCode\n\n.. image:: https://coveralls.io/repos/github/stonerlab/Stoner-PythonCode/badge.svg?branch=master\n    :target: https://coveralls.io/github/stonerlab/Stoner-PythonCode?branch=master\n\n.. image:: https://api.codacy.com/project/badge/Grade/372f2f9227134fab9c6c2f2ba83962ba\n    :target: https://www.codacy.com/app/stonerlab/Stoner-PythonCode?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=stonerlab/Stoner-PythonCode&amp;utm_campaign=Badge_Grade\n\n.. image:: https://badge.fury.io/py/Stoner.svg\n   :target: https://badge.fury.io/py/Stoner\n\n.. image:: https://readthedocs.org/projects/stoner-pythoncode/badge/?version=latest\n   :target: http://stoner-pythoncode.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n\n.. image:: https://zenodo.org/badge/17265/gb119/Stoner-PythonCode.svg\n   :target: https://zenodo.org/badge/latestdoi/17265/gb119/Stoner-PythonCode\n\n.. image:: http://depsy.org/api/package/pypi/Stoner/badge.svg\n   :target: http://depsy.org/package/python/Stoner\n\nIntroduction\n============\n\n\nThe  *Stoner* Python package is a set of utility classes for writing data analysis code. It was written within\nthe Condensed Matter Physics group at the University of Leeds as a shared resource for quickly writing simple\nprograms to do things like fitting functions to data, extract curve parameters, churn through large numbers of\nsmall text data files and work with certain types of scientific image files.\n\nFor a general introduction, users are referred to the Users Guide, which is part of the `online documentation`_ along with the\nAPI Reference guide. The `github repository`_ also contains some example scripts.\n\nGetting this Code\n==================\n\n.. image:: https://i.imgur.com/h4mWwM0.png\n    :target: https://www.youtube.com/watch?v=uZ_yKs11W18\n    :alt: Introduction and Installation Guide to Stoner Pythin Package\n    :width: 320\n\nThe *Stoner* package requires numpy >=1.8, scipy >=0.14, matplotlib >=1.5, h5py, lmfit,Pillow  and has a number of optional dependencies\non blist, filemagic, npTDMS, imreg_dft and numba.\n\nAnanconda Python (and probably other scientific Python distributions) include nearly all of the dependencies, and the remaining\ndependencies are collected together in the phygbu repositry on anaconda cloud. The easiest way to install the Stoner package is,\ntherefore, to install the most recent Anaconda Python distribution (Python 3.7, 3.6, 3.5 or 2.7 should work) and then to install\nthe Stoner package via:\n\n.. code-block:: sh\n\n    conda install -c phygbu Stoner\n\nIf you are not using Anaconda python, then pip should also work:\n\n.. code-block:: sh\n\n    pip install Stoner\n\nThis will install the Stoner package and any missing dependencies into your current Python environment. Since the package is under fairly\nconstant updates, you might want to follow the development with git. The source code, along with example scripts\nand some sample data files can be obtained from the github repository: https://github.com/stonerlab/Stoner-PythonCode\n\nThe codebase is compatible with Python 2.7 and Python 3.5+, at present we still develop primarily in Python 3.6 and 3.7  but test with\n2.7 as well. *NB* Python 3.7 is only supported in version 0.9x onwards and is known to not work with version 0.8.x.\n\nOverview\n========\nThe main part of the **Stoner** package provides two basic top-level classes that describe an individual file of experimental data and a\nlist (such as a directory tree on disc) of many experimental files. For our research, a typical single experimental data file\nis essentially a single 2D table of floating point numbers with associated metadata, usually saved in some\nASCII text format. This seems to cover most experiments in the physical sciences, but it you need a more complex\nformat with more dimensions of data, we suggest you look elsewhere.\n\nData and Friends\n----------------\n\n**Stoner.Data** is the core class for representing individual experimental data sets.\nIt is actually composed of several mixin classes that provide different functionality, with methods\nto examine and manipulate data, manage metadata, load and save data files, plot results and carry out various analysis tasks.\nIt has a large number of sub classes - most of these are in Stoner.formats and are used to handle the loading of specific\nfile formats.\n\nDataFolder\n----------\n\n**Stoner.Folders.DataFolder** is a class for assisting with the work of processing lots of files in a common directory\nstructure. It provides methods to list. filter and group data according to filename patterns or metadata and then to execute\na function on each file or group of files. A key feature of DataFolder is its ability to work with the collated metadata from\nthe individual files that are held in the DataFolder. In combination with its ability to walk through a complete heirarchy of groups of\n**Data** objects, the handling of the common metadata provides powerful tools for quickly writing data reduction scripts.\n\nThe **Stoner.HDF5** module provides some experimental classes to manipulate *DataFile* and *DataFolder* objects within HDF5\nformat files. These are not a way to handle arbitary HDF5 files - the format is much to complex and flexible to make that\nan easy task, rather it is a way to work with large numbers of experimental sets using just a single file which may be less\nbrutal to your computer's OS than having directory trees with millions of individual files. The module also provides some classes to\nsupport loading some other HDF5 flavoured files into a **DataFile**.\n\nThe **Stoner.Zip** module provides a similar set of classes to **Stoner.HDF5** but working with the ubiquitous zip compressed file format.\n\nImage Subpackage\n----------------\n\nThe **Stoner.Image** package is a new feature of recent versions of the package and provides dedicated classes for working with image data,\nand in particular for analysing Kerr Microscope image files. It provides an **ImageFile** class that is functionally similar to **DataFile**\nexcept that the numerical data is understood to represent image data and additional methods are incorporated to facilitate processing. The **ImageFolder**\nand **ImageStack** classes provide similar functionality to **DataFolder** but with additional methods specific to handling collections of images. **ImageStack**\nuses a 3D numpy array as it's primary image store which permits faster access (at the expense of a larger memory footprint) than the lazy loading ordered\ndictionary of **ImageFolder**\n\nResources\n==========\n\nIncluded in the `github repository`_  are a (small) collection of sample scripts\nfor carrying out various operations and some sample data files for testing the loading and processing of data. There is also a\n`User_Guide`_ as part of this documentation, along with a doc(``complete API reference <Stoner>``)\n\nContact and Licensing\n=====================\n\nThe lead developer for this code is `Dr Gavin Burnell`_ <g.burnell@leeds.ac.uk>, but many current and former members of the CM Physics group have\ncontributed code, ideas and bug testing.\n\nThe User Guide gives the current list of other contributors to the project.\n\nThis code and the sample data are all (C) The University of Leeds 2008-2017 unless otherwise indficated in the source file.\nThe contents of this package are licensed under the terms of the GNU Public License v3\n\nRecent Changes\n==============\n\nCurrent PyPi Version\n--------------------\n\nThe current version of the package on PyPi will be the stable branch until the development branch enters beta testing, when we start\nmaking beta packages available.\n\n\nDevelopment Version\n-------------------\n\nThe current development version is hosted in the master branch of the repository and will become version 0.10. There is no definitive list of\nfeatures at this time. Better integration with pandas and xarray are under consideration as is depricating some of the less optimal parts of the api.\n\nBuild Status\n~~~~~~~~~~~~\n\nVersion 0.7 onwards are tested using the Travis-CI services with unit test coverage assessed by Coveralls.\n\nVersion 0.9 is tested with Python 2.7, 3.5, 3.6,\n\nThe development version - which will be 0.10 will be tested with Python 3.6 and Python 3.7 only until Python 3.8 becomes stable.\n\n\nCiting the Stoner Package\n~~~~~~~~~~~~~~~~~~~~~~~~~\n\nWe maintain a digital object identifier (doi) for this package (linked to on the status bar at the top of this readme) and\nencourage any users to cite this package via that doi.\n\nStable Versions\n---------------\n\nVersion 0.9 is the current stable version. This is the last version to support Python 2 and 3<3.6. Features of this release are:\n\n    *   Refactoring of the package into a more granual core, plot, formats, folders packages with submodules\n    *   Overhaul of the documentation and user guide\n    *   Dropping support for the older Stoner.Image.stack.ImageStack class\n    *   Droppping support for matplotlib<2.0\n    *   Support for Python 3.7\n    *   Unit tests now > 80% coverage across the package.\n\nOnline documentation for all versions can be found on the ReadTheDocs pages `online documentation`_\n\nVersion 0.8 is the previous stable release. The main new features were:\n\n    *   Reworking of the ImageArray, ImageFile and ImageFolder with many updates and new features.\n    *   New mixin based ImageStack2 that can manipulate a large number of images in a 3D numpy array\n    *   Continued re-factoring of DataFolder using the mixin approach\n    *   Further increases to unit-test coverage, bug fixes and refactoring of some parts of the code.\n    *   _setas objects implement a more complete MutableMapping interface and also support +/- operators.\n    *   conda packages now being prepared as the preferred package format\n\n0.8.2 was the final release of the 0.8.0 branch\n\nThe old stable version is 0.7.2. Features of 0.7.2 include\n\n    *   Replace older AnalyseFile and PlotFile with mixin based versions AnalysisMixin and PlotMixin\n    *   Addition of Stoner.Image package to handle image analysis\n    *   Refactor DataFolder to use Mixin classes\n    *   DataFolder now defaults to using Stoner.Core.Data\n    *   DataFolder has an options to skip iterating over empty Data files\n    *   Further improvements to Stoner.Core.DataFile.setas handline.\n\nNo further relases will be made to 0.7.x.\n\n0.6, 0.7 should work on Python 2.7 and 3.5\n0.8 is also tested on Python 3.6\n\n.. _online documentation: http://stoner-pythoncode.readthedocs.io/en/latest/\n.. _github repository: http://www.github.com/stonerlab/Stoner-PythonCode/\n.. _Dr Gavin Burnell: http://www.stoner.leeds.ac.uk/people/gb\n.. _User_Guide: http://stoner-pythoncode.readthedocs.io/en/latest/UserGuide/ugindex.html\n\n",
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