Metadata-Version: 2.1
Name: radiopadre
Version: 1.1.1
Summary: A data visualization framework for jupyter notebooks
Home-page: http://github.com/ratt-ru/radiopadre
Author: Oleg Smirnov
Author-email: osmirnov@gmail.com
License: MIT
Description: .. image:: icons/radiopadre-logo-long-400px.png?raw=True 
           :width: 400
        
        Python (Radio) Astronomy Data & Results Examiner
        ================================================
        
        |Build Status|
        |PyPI version|
        |PyPI pyversions|
        |PyPI status|
        |Project License|
        
        Radiopadre is a Jupyter
        notebook framework for quick and easy visualization of [radio astronomy, primarily]
        data products and pipelines.
        
        **Radiopadre includes integration with** `JS9 <https://js9.si.edu/>`_
        **and** `CARTA <https://cartavis.github.io/>`_
        **for live FITS viewing of [remote] FITS files straight from your browser.**
        (In boldface, because this is a pretty neat capability to have!)
        
        Radiopadre is a custom Jupyter kernel, so in principle you could install it
        and create radiopadre notebooks directly from a Jupyter session. Some of the
        tight integration with JS9 and CARTA, however, works smoother if you start your sessions
        via the ``run-radiopadre`` `client script <https://github.com/ratt-ru/radiopadre-client>`_,
        which takes care of starting up and stopping appropriate
        helper processes and such.
        
        The general use case for Radiopadre is "here I am sitting with a slow ssh connection into a remote cluster node, my pipeline has produced 500 plots/logs/FITS images, how do I make sense of this mess?" More specifically, there are three (somewhat overlapping) scenarios that Radiopadre is designed for:
        
        * Just browsing: interactively exploring the aforementioned 500 files using a notebook.
        
        * Automated reporting: customized Radiopadre notebooks that automatically generate a report composed of a pipeline's outputs and intermediate products. Since your pipeline's output is (hopefully!) structured, i.e. in terms of filename conventions etc., you can write a notebook to exploit that structure and make a corresponding report automatically.
        
        * Sharing notebooks: fiddle with a notebook until everything is visualized just right, insert explanatory text in mardkdown cells in between, voila, you have an instant report you can share with colleagues.
        
        ======================
        Usage, in a nutshell
        ======================
        
        See `radiopadre-client package <https://github.com/ratt-ru/radiopadre-client>`_.
        
        
        ==========
        Tutorial
        ==========
        
        For a quick tutorial on radiopadre, download the tutorial_package_,
        untar, and run radiopadre inside the resulting directory, locally or remotely (you can also refer to the PDF 
        enclosed in the tarball for a poor man's rendering of the notebook).
        
        .. |Build Status| image:: https://travis-ci.org/ratt-ru/radiopadre.svg?branch=master
                          :target: https://travis-ci.org/radio-astro/radiopadre/
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        .. |PyPI version| image:: https://img.shields.io/pypi/v/radiopadre.svg
                          :target: https://pypi.python.org/pypi/radiopadre/
                          :alt:
        
        .. |PyPI pyversions| image:: https://img.shields.io/pypi/pyversions/radiopadre.svg
                          :target: https://pypi.python.org/pypi/radiopadre/
                          :alt:
        
        .. |PyPI status| image:: https://img.shields.io/pypi/status/radiopadre.svg
                          :target: https://pypi.python.org/pypi/radiopadre/
                          :alt:
        .. |Project License| image:: https://img.shields.io/github/license/ratt-ru/radiopadre
                             :target: https://github.com/ratt-ru/radiopadre/blob/master/LICENSE
                             :alt:
        
        .. _tutorial_package: https://www.dropbox.com/sh/be4pc23rsavj67s/AAB2Ejv8cLsVT8wj60DiqS8Ya?dl=0
        
Keywords: ipython notebook jupyter fits dataset resultset visualisation
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Topic :: Utilities
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.6
Provides-Extra: casacore
