Metadata-Version: 1.2
Name: mpld3
Version: 0.3
Summary: D3 Viewer for Matplotlib
Home-page: http://mpld3.github.com
Author: Jake VanderPlas
Author-email: jakevdp@cs.washington.edu
Maintainer: Jake VanderPlas
Maintainer-email: jakevdp@cs.washington.edu
License: BSD 3-clause
Download-URL: http://github.com/jakevdp/mpld3
Description: mpld3: A D3 Viewer for Matplotlib
        =================================
        
        - Author: Jake Vanderplas <jakevdp@cs.washington.edu>
        - License: BSD 3-clause
        
        This is an interactive D3js-based viewer which brings matplotlib graphics to the browser.
        Please visit [http://mpld3.github.io](http://mpld3.github.io) for documentation and examples.
        
        You may also see the [blog post](http://jakevdp.github.io/blog/2013/12/19/a-d3-viewer-for-matplotlib/), or the
        [IPython notebook examples](http://nbviewer.ipython.org/github/jakevdp/mpld3/tree/master/notebooks/)
        available in the ``notebooks`` directory of this repository.
        
        [![version status](https://img.shields.io/pypi/v/mpld3.svg)](https://pypi.python.org/pypi/mpld3)
        [![downloads](https://img.shields.io/pypi/dm/mpld3.svg)](https://pypi.python.org/pypi/mpld3)
        [![build status](https://travis-ci.org/jakevdp/mpld3.svg?branch=master)](https://travis-ci.org/jakevdp/mpld3)
        
        
        About
        -----
        mpld3 provides a custom stand-alone javascript library built on D3, which
        parses JSON representations of plots.  The mpld3 python module provides a
        set of routines which parses matplotlib plots (using the 
        [mplexporter](http://github.com/mpld3/mplexporter) framework) and outputs
        the JSON description readable by mpld3.js.
        
        
        Installation
        ------------
        mpld3 is compatible with python 2.6-2.7 and 3.3-3.4. It requires
        [matplotlib](http://matplotlib.org) version 1.3 and
        [jinja2](http://jinja.pocoo.org/) version 2.7+.
        
        Optionally, mpld3 can be used with [IPython](http://ipython.org) notebook,
        and requires IPython version 1.x or (preferably) version 2.0+.
        
        This package is based on the [mplexporter](http://github.com/mpld3/mplexporter)
        framework for crawling and exporting matplotlib images. mplexporter is bundled
        with the source distribution via git submodule.
        
        Within the git source directory, you can download the mplexporter dependency
        and copy it into the mpld3 source directory using the following command:
        
            [~]$ python setup.py submodule
        
        The submodule command is not necessary if you are installing from a distribution
        rather than from the git source.
        
        Once the submodule command has been run, you can build the package locally using
        
            [~]$ python setup.py build
        
        or install the package to the standard Python path using:
        
            [~]$ python setup.py install
        
        Or, to install to another location, use
        
            [~]$ python setup.py install --prefix=/path/to/location/
        
        Then make sure your PYTHONPATH environment variable points to this location.
        
        Trying it out
        -------------
        The package is pure python, and very light-weight.  You can take a look at
        the notebooks in the examples directory, or run ``create_example.py``, which
        will create a set of plots and launch a browser window showing interactive
        views of these plots.
        
        For a more comprehensive set of examples, see the
        [IPython notebook examples](http://nbviewer.ipython.org/github/jakevdp/mpld3/tree/master/notebooks/) available in the ``notebooks`` directory.
        
        Test Plots
        ----------
        To explore the comparison between D3 renderings and matplotlib renderings for
        various plot types, run the script ``visualize_tests.py``.  This will generate
        an HTML page with the D3 renderings beside corresponding matplotlib renderings.
        
        Features
        --------
        Many of the core features of matplotlib are already supported.  And additionally
        there is some extra interactivity provided via the plugin framework.  The
        following is a non-exhausive list of features that are yet to be supported:
        
        - tick specification & formatting
        - some legend features
        - blended transforms, such as those required by ``axvlines`` and ``axhlines``
        - twin axes (i.e. multiple scales on one plot) tied together
        
        If any of these look like something you'd like to tackle, feel free to submit
        a pull request!
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4