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Expose `Video` and make some variable private....
Expose `Video` and make some variable private. Closes #10432

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plotting.rst
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Jonathan Frederic
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Plotting
--------
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r21587 One major feature of the IPython kernel is the ability to display plots that
Jonathan Frederic
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r21584 are the output of running code cells. The IPython kernel is designed to work
seamlessly with the matplotlib_ plotting library to provide this functionality.
Matthias Bussonnier
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r22598 To set this up, before any plotting or import of matplotlib is performed you
must execute the ``%matplotlib`` :ref:`magic command <magics_explained>`. This
performs the necessary behind-the-scenes setup for IPython to work correctly
hand in hand with ``matplotlib``; it does *not*, however, actually execute any
Python ``import`` commands, that is, no names are added to the namespace.
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If the ``%matplotlib`` magic is called without an argument, the
output of a plotting command is displayed using the default ``matplotlib``
backend in a separate window. Alternatively, the backend can be explicitly
requested using, for example::
%matplotlib gtk
A particularly interesting backend, provided by IPython, is the ``inline``
backend. This is available only for the Jupyter Notebook and the
Lev Givon
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r21602 Jupyter QtConsole. It can be invoked as follows::
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%matplotlib inline
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r22598 With this backend, the output of plotting commands is displayed *inline* within
frontends like the Jupyter notebook, directly below the code cell that produced
it. The resulting plots will then also be stored in the notebook document.
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.. seealso::
`Plotting with Matplotlib`_ example notebook
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The matplotlib_ library also ships with ``%matplotlib notebook`` command that
allows interactive figures if your environment allows it.
See the matplotlib_ documentation for more information.
Jonathan Frederic
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r21587 .. include:: ../links.txt