.. _mpl-shell:

**********************************
Using matplotlib in a python shell
**********************************

By default, matplotlib defers drawing until the end of the script
because drawing can be an expensive operation, and you may not want
to update the plot every time a single property is changed, only once
after all the properties have changed.

But when working from the python shell, you usually do want to update
the plot with every command, e.g., after changing the
:func:`~matplotlib.pyplot.xlabel`, or the marker style of a line.
While this is simple in concept, in practice it can be tricky, because
matplotlib is a graphical user interface application under the hood,
and there are some tricks to make the applications work right in a
python shell.


.. _ipython-pylab:

IPython to the rescue
=====================

.. note::

    The mode described here still exists for historical reasons, but it is
    highly advised not to use. It pollutes namespaces with functions that will
    shadow python built-in and can lead to hard to track bugs. To get IPython
    integration without imports the use of the  `%matplotlib` magic is
    preferred. See
    `ipython documentation <http://ipython.org/ipython-doc/stable/interactive/reference.html#plotting-with-matplotlib>`_
    .

Fortunately, `ipython <http://ipython.org/>`_, an enhanced
interactive python shell, has figured out all of these tricks, and is
matplotlib aware, so when you start ipython in the *pylab* mode.

.. sourcecode:: ipython

    johnh@flag:~> ipython
    Python 2.4.5 (#4, Apr 12 2008, 09:09:16)
    IPython 0.9.0 -- An enhanced Interactive Python.

    In [1]: %pylab

      Welcome to pylab, a matplotlib-based Python environment.
      For more information, type 'help(pylab)'.

    In [2]: x = randn(10000)

    In [3]: hist(x, 100)

it sets everything up for you so interactive plotting works as you
would expect it to.  Call :func:`~matplotlib.pyplot.figure` and a
figure window pops up, call :func:`~matplotlib.pyplot.plot` and your
data appears in the figure window.

Note in the example above that we did not import any matplotlib names
because in pylab mode, ipython will import them automatically.
ipython also turns on *interactive* mode for you, which causes every
pyplot command to trigger a figure update, and also provides a
matplotlib aware ``run`` command to run matplotlib scripts
efficiently.  ipython will turn off interactive mode during a ``run``
command, and then restore the interactive state at the end of the
run so you can continue tweaking the figure manually.

There has been a lot of recent work to embed ipython, with pylab
support, into various GUI applications, so check on the ipython
mailing `list
<http://projects.scipy.org/mailman/listinfo/ipython-user>`_ for the
latest status.

.. _other-shells:

Other python interpreters
=========================

If you can't use ipython, and still want to use matplotlib/pylab from
an interactive python shell, e.g., the plain-ole standard python
interactive interpreter, you
are going to need to understand what a matplotlib backend is
:ref:`what-is-a-backend`.



With the TkAgg backend, which uses the Tkinter user interface toolkit,
you can use matplotlib from an arbitrary non-gui python shell.  Just set your
``backend : TkAgg`` and ``interactive : True`` in your
:file:`matplotlibrc` file (see :ref:`customizing-matplotlib`) and fire
up python.  Then::

  >>> from pylab import *
  >>> plot([1,2,3])
  >>> xlabel('hi mom')

should work out of the box.  This is also likely to work with recent
versions of the qt4agg and gtkagg backends, and with the macosx backend
on the Macintosh. Note, in batch mode,
i.e. when making
figures from scripts, interactive mode can be slow since it redraws
the figure with each command.  So you may want to think carefully
before making this the default behavior via the :file:`matplotlibrc`
file instead of using the functions listed in the next section.

Gui shells are at best problematic, because they have to run a
mainloop, but interactive plotting also involves a mainloop.  Ipython
has sorted all this out for the primary matplotlib backends. There
may be other shells and IDEs that also work with matplotlib in interactive
mode, but one obvious candidate does not:
the python IDLE IDE is a Tkinter gui app that does
not support pylab interactive mode, regardless of backend.

.. _controlling-interactive:

Controlling interactive updating
================================

The *interactive* property of the pyplot interface controls whether a
figure canvas is drawn on every pyplot command.  If *interactive* is
*False*, then the figure state is updated on every plot command, but
will only be drawn on explicit calls to
:func:`~matplotlib.pyplot.draw`.  When  *interactive* is
*True*, then every pyplot command triggers a draw.


The pyplot interface provides 4 commands that are useful for
interactive control.

:func:`~matplotlib.pyplot.isinteractive`
    returns the interactive setting *True|False*

:func:`~matplotlib.pyplot.ion`
    turns interactive mode on

:func:`~matplotlib.pyplot.ioff`
    turns interactive mode off

:func:`~matplotlib.pyplot.draw`
    forces a figure redraw

When working with a big figure in which drawing is expensive, you may
want to turn matplotlib's interactive setting off temporarily to avoid
the performance hit::


    >>> #create big-expensive-figure
    >>> ioff()      # turn updates off
    >>> title('now how much would you pay?')
    >>> xticklabels(fontsize=20, color='green')
    >>> draw()      # force a draw
    >>> savefig('alldone', dpi=300)
    >>> close()
    >>> ion()      # turn updating back on
    >>> plot(rand(20), mfc='g', mec='r', ms=40, mew=4, ls='--', lw=3)



