Metadata-Version: 2.1
Name: iris-ued
Version: 5.2.5
Summary: Ultrafast electron diffraction data exploration
Home-page: http://iris-ued.readthedocs.io
Author: Laurent P. René de Cotret
Author-email: laurent.renedecotret@mail.mcgill.ca
Maintainer: Laurent P. René de Cotret
Maintainer-email: laurent.renedecotret@mail.mcgill.ca
License: GPLv3
Download-URL: http://github.com/LaurentRDC/iris-ued
Project-URL: Documentation, http://iris-ued.readthedocs.io/en/master/
Project-URL: Source, https://github.com/LaurentRDC/iris-ued
Project-URL: Tracker, https://github.com/LaurentRDC/iris-ued/issues
Project-URL: Home, http://www.physics.mcgill.ca/siwicklab/software.html
Description: # Iris - Ultrafast Electron Scattering Data Exploration
        
        [![Documentation Build Status](https://readthedocs.org/projects/iris-ued/badge/?version=master)](http://iris-ued.readthedocs.io/) [![PyPI Version](https://img.shields.io/pypi/v/iris-ued.svg)](https://pypi.python.org/pypi/iris-ued) [![Conda-forge Version](https://img.shields.io/conda/vn/conda-forge/iris-ued.svg)](https://anaconda.org/conda-forge/iris-ued)
        
        
        Iris is both a library for interacting with ultrafast electron
        diffraction data, as well as a GUI frontend for interactively exploring
        this data.
        
        Iris also includes a plug-in manager so that you can explore your data.
        
        ![Two instances of the iris GUI showing data exploration for ultrafast
        electron diffraction of single crystals and
        polycrystals.](iris_screen.png)
        
        ## Contents:
          - [Installation](#installation)
          - [Usage](#usage)
          - [Test Data](#test-data)
          - [Documentation](#documentation)
          - [Citations](#citations)
          - [Support / Report Issues](#support--report-issues)
          - [License](#license)
        
        ## Installation
        
        To interact with [iris]{.title-ref} datasets from a Python environment,
        the [iris-ued]{.title-ref} package must be installed. [iris]{.title-ref}
        is available on PyPI; it can be installed with
        [pip](https://pip.pypa.io).:
        
            python -m pip install iris-ued
        
        [iris]{.title-ref} is also available on the conda-forge channel:
        
            conda config --add channels conda-forge
            conda install iris-ued
        
        To install the latest development version from
        [Github](https://github.com/LaurentRDC/iris-ued):
        
            python -m pip install git+git://github.com/LaurentRDC/iris-ued.git
        
        Each version is tested against Python 3.6+. If you are using a different
        version, tests can be run using the `pytest` package.
        
        ## Usage
        
        Once installed, the package can be imported as `iris`.
        
        The GUI component can be launched from a command line interpreter as
        `python -m iris` or `pythonw -m iris` (no console window).
        
        ## Test Data
        
        Test datasets are made available on the Siwick research group public
        data server, which can be [accessed anonymously
        here](http://www.physics.mcgill.ca/siwicklab/publications.html).
        
        ## Documentation
        
        The [Documentation on readthedocs.io](https://iris-ued.readthedocs.io)
        provides API-level documentation, as well as tutorials.
        
        ## Citations
        
        If you find this software useful, please consider citing the following
        publications:
        
        ## Support / Report Issues
        
        All support requests and issue reports should be [filed on Github as an
        issue](https://github.com/LaurentRDC/iris-ued/issues).
        
        ## License
        
        iris is made available under the GPLv3 License. For more details, see
        [LICENSE.txt](https://github.com/LaurentRDC/iris-ued/blob/master/LICENSE.txt).
        
Keywords: ultrafast electron diffraction visualization pyqtgraph
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >= 3.6
Description-Content-Type: text/markdown
