Metadata-Version: 1.2
Name: arpes
Version: 1.0.0
Summary: Modular data analysis code for angle resolved photoemission spectroscopy (ARPES)
Home-page: https://gitlab.com/lanzara-group/python-arpes
Author: Conrad Stansbury
Author-email: chstan@berkeley.edu
License: MIT
Description: 
        |Banner|
        
        .. |Banner| image:: PyPES-Banner.png
                    :alt: PyPES Banner
        
        +-----------------------+
        | **Documentation**     |
        +=======================+
        | |Documentation|       |
        +-----------------------+
        
        .. |Documentation| image:: https://img.shields.io/badge/api-reference-blue.svg
           :target: https://stupefied-bhabha-ce8a9f.netlify.com/
        
        Installation
        ============
        
        The simplest way to install the package is using pip. While this repository
        is private, you can install with pip by pointing pip to the URL of the repository
        as:
        
        ::
        
           pip install --process-dependency-links -e
        
        
        Once this project is published on PyPI, you can install by using
        
        ::
        
           pip install arpes
        
        
        You will need to install into a Python interpreter with version 3.5 or higher. Note that the
        `--process-dependency-links` directive appears in both commands and is necessary in order to
        include a patched version of the Igor interop library. If you have a newer version of ``pip``,
        you might not be able to use `-process-dependency-links` as the ``pip`` team has deprecated
        this option. Please consult the `FAQ`_ for how to manually install a few extra dependencies if this
        is the case.
        
        Windows Installation
        --------------------
        
        Windows is not the most friendly operating system for scientific software. Although
        installation is absolutely possible manually, I cannot advocate Anaconda enough for Windows
        users, as it smooths out a lot of inhomogeneity in the process. For details on how to
        install manually, consult also the `FAQ`_.
        
        
        Alternative Installation
        ========================
        
        If for whatever reason you do not want to install the project as a package but would
        like to import it locally, legacy install instructions are available in the first section
        of ``README.legacy.rst``.
        
        This can be advantageous if you want to frequently change the package source without
        reinstalling. A further alternative is to clone the package and ``pip install`` from the local folder,
        which has the advantage of a simple installation procedure and puts the code someplace easily editable.
        
        
        Additional Suggested Steps
        --------------------------
        
        1. Clone or duplicate the folder structure in the repository ``arpes-analysis-scaffold``,
           skipping the example folder and data if you like
        2. Install and configure standard tools like Jupyter_ or Jupyter Lab. Notes on installing
           and configuring Jupyter based installations can be found in ``jupyter.md``
        3. Explore the documentation and example notebooks at `the documentation site`_.
        
        ``local_config.py``
        -------------------
        
        The local configuration allows you to override the settings that are
        committed to the repository and therefore shared. You can use this to
        as adjust settings on various interactive tools. For reference, Conrad’s
        looks like:
        
        ::
        
           SETTINGS = {
               'interactive': {
                   'main_width': 600,
                   'marginal_width': 300,
                   'palette': 'magma',
               },
           }
        
        IPython Kernel Customization
        ----------------------------
        
        If you don’t want to have to import everything all the time, you should
        customize your IPython session so that it runs imports when you first
        spin up a kernel. There are good directions for how to do this online,
        but a short version is:
        
        1. Create an IPython profile, use this to start your notebooks
        2. In ``~/.ipython/profile_default/`` make a folder ``startup``
        3. Add the files
           ``~/.ipython/profile_default/startup/00-add-arpes-path.py`` and
           ``~/.ipython/{Your profile}/startup/01-common-imports.ipy`` according
           to the templates in ``ipython_templates``. See in particular note
           above about setting the environment variable using this file.
        4. Customize
        
        It is important that the filenames you put are such that
        ``00-add-arpes-path`` is lexographically first, as this ensures that it is
        executed first. The ``.ipy`` extension on ``01-common-imports.ipy`` is
        also essential. Ask Conrad if any of this is confusing.
        
        Contributing and Documentation
        ==============================
        
        See the section on the docs site about `contributing`_ for information on
        adding to PyPES and rebuilding documentation from source.
        
        Contact
        =======
        
        Questions, difficulties, and suggestions can be directed to Conrad Stansbury (chstan@berkeley.edu)
        or added to the repository as an issue. In the case trouble, also check the `FAQ`_.
        
        Copyright |copy| 2018 by Conrad Stansbury, all rights reserved.
        
        .. |copy|   unicode:: U+000A9 .. COPYRIGHT SIGN
        
        .. _Jupyter: https://jupyter.org/
        .. _the documentation site: https://pypes.netlify.com/
        .. _contributing: https://pypes.netlify.com/#/contributing
        .. _FAQ: https://pypes.netlify.com/#/faq
        
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Natural Language :: English
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows :: Windows 7
Classifier: Operating System :: Microsoft :: Windows :: Windows 8
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.5.0
