Metadata-Version: 1.2
Name: arpes
Version: 2.1.0
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: 
        +-----------------------+
        | **Documentation**     |
        +=======================+
        | |Documentation|       |
        +-----------------------+
        
        .. |Documentation| image:: https://img.shields.io/badge/api-reference-blue.svg
           :target: https://arpes.netlify.com/
        
        .. image:: https://dev.azure.com/lanzara-group/PyARPES/_apis/build/status/PyARPES%20CI%20Build?branchName=master
           :target: https://dev.azure.com/lanzara-group/PyARPES/_build?definitionId=2
        
        .. image:: https://img.shields.io/azure-devops/coverage/lanzara-group/PyARPES/2.svg
           :target: https://dev.azure.com/lanzara-group/PyARPES/_build?definitionId=2
        
        .. image:: https://img.shields.io/pypi/v/arpes.svg
           :target: https://pypi.org/project/arpes/
        
        .. image:: https://img.shields.io/conda/v/arpes/arpes.svg
           :target: https://anaconda.org/arpes/arpes
        
        .. image:: https://img.shields.io/pypi/pyversions/arpes.svg
           :target: https://pypi.org/project/arpes/
        
        PyARPES
        =======
        
        PyARPES simplifies the analysis and collection of angle-resolved photoemission spectroscopy (ARPES) and emphasizes
        
        * modern, best practices for data science
        * support for a standard library of ARPES analysis tools mirroring those available in Igor Pro
        * interactive and extensible analysis tools
        
        It supports a variety of data formats from synchrotron and laser-ARPES sources including ARPES at the Advanced
        Light Source (ALS), the data produced by Scienta Omicron GmbH's "SES Wrapper", data and experiment files from
        Igor Pro, NeXuS files, and others.
        
        To learn more about installing and using PyARPES in your analysis or data collection application,
        visit `the documentation site`_.
        
        PyARPES is currently developed by Conrad Stansbury of the Lanzara Group at the University of California, Berkeley.
        
        Installation
        ============
        
        PyARPES can be installed from source, or using either ``pip`` or ``conda`` into a Python 3.6 or 3.7 environment.
        ``conda`` is preferred as a package manager in order to facilitate installing the libraries for reading HDF and
        NetCDF files.
        
        Pip installation
        ----------------
        
        ::
        
           pip install arpes
        
        Platform specific instructions to install the HDF and NetCDF libraries are
        available below.
        
        Conda installation
        ------------------
        
        PyARPES is distributed through the ``arpes`` Anaconda channel. A minimal install looks like
        
        ::
        
           conda install -c arpes arpes
        
        
        Local installation from source
        ------------------------------
        
        If you want to modify the source for PyARPES as you use it, you might prefer a local installation from source.
        Details can be found on `the documentation site`_.
        
        
        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`_.
        
        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 of trouble, also check the `FAQ`_.
        
        Copyright |copy| 2018-2019 by Conrad Stansbury, all rights reserved.
        
        .. |copy|   unicode:: U+000A9 .. COPYRIGHT SIGN
        
        .. _Jupyter: https://jupyter.org/
        .. _the documentation site: https://arpes.netlify.com/
        .. _contributing: https://arpes.netlify.com/#/contributing
        .. _FAQ: https://arpes.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 :: 3.6
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
