Add code to de-init the inline backend.

Save the rcParameters before activating inline mode. Then unwind all the
changes when activating a different mode.

IPython/core/pylabtools.py

@@ -1,334 +1,346 b''
 # -*- coding: utf-8 -*-
 """Pylab (matplotlib) support utilities.
 
 Authors
 -------
 
 * Fernando Perez.
 * Brian Granger
 """
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2009-2011  The IPython Development Team
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
 import sys
 from io import BytesIO
 
 from IPython.utils.decorators import flag_calls
 
 # If user specifies a GUI, that dictates the backend, otherwise we read the
 # user's mpl default from the mpl rc structure
 backends = {'tk': 'TkAgg',
             'gtk': 'GTKAgg',
             'wx': 'WXAgg',
             'qt': 'Qt4Agg', # qt3 not supported
             'qt4': 'Qt4Agg',
             'osx': 'MacOSX',
             'inline' : 'module://IPython.zmq.pylab.backend_inline'}
 
 # We also need a reverse backends2guis mapping that will properly choose which
 # GUI support to activate based on the desired matplotlib backend.  For the
 # most part it's just a reverse of the above dict, but we also need to add a
 # few others that map to the same GUI manually:
 backend2gui = dict(zip(backends.values(), backends.keys()))
 # In the reverse mapping, there are a few extra valid matplotlib backends that
 # map to the same GUI support
 backend2gui['GTK'] = backend2gui['GTKCairo'] = 'gtk'
 backend2gui['WX'] = 'wx'
 backend2gui['CocoaAgg'] = 'osx'
 
 #-----------------------------------------------------------------------------
 # Matplotlib utilities
 #-----------------------------------------------------------------------------
 
 
 def getfigs(*fig_nums):
     """Get a list of matplotlib figures by figure numbers.
 
     If no arguments are given, all available figures are returned.  If the
     argument list contains references to invalid figures, a warning is printed
     but the function continues pasting further figures.
 
     Parameters
     ----------
     figs : tuple
         A tuple of ints giving the figure numbers of the figures to return.
     """
     from matplotlib._pylab_helpers import Gcf
     if not fig_nums:
         fig_managers = Gcf.get_all_fig_managers()
         return [fm.canvas.figure for fm in fig_managers]
     else:
         figs = []
         for num in fig_nums:
             f = Gcf.figs.get(num)
             if f is None:
                 print('Warning: figure %s not available.' % num)
             else:
                 figs.append(f.canvas.figure)
         return figs
 
 
 def figsize(sizex, sizey):
     """Set the default figure size to be [sizex, sizey].
 
     This is just an easy to remember, convenience wrapper that sets::
 
       matplotlib.rcParams['figure.figsize'] = [sizex, sizey]
     """
     import matplotlib
     matplotlib.rcParams['figure.figsize'] = [sizex, sizey]
 
 
 def print_figure(fig, fmt='png'):
     """Convert a figure to svg or png for inline display."""
     # When there's an empty figure, we shouldn't return anything, otherwise we
     # get big blank areas in the qt console.
     if not fig.axes and not fig.lines:
         return
 
     fc = fig.get_facecolor()
     ec = fig.get_edgecolor()
     bytes_io = BytesIO()
     fig.canvas.print_figure(bytes_io, format=fmt, bbox_inches='tight',
                             facecolor=fc, edgecolor=ec)
     data = bytes_io.getvalue()
     return data
 
 
 # We need a little factory function here to create the closure where
 # safe_execfile can live.
 def mpl_runner(safe_execfile):
     """Factory to return a matplotlib-enabled runner for %run.
 
     Parameters
     ----------
     safe_execfile : function
       This must be a function with the same interface as the
       :meth:`safe_execfile` method of IPython.
 
     Returns
     -------
     A function suitable for use as the ``runner`` argument of the %run magic
     function.
     """
     
     def mpl_execfile(fname,*where,**kw):
         """matplotlib-aware wrapper around safe_execfile.
 
         Its interface is identical to that of the :func:`execfile` builtin.
 
         This is ultimately a call to execfile(), but wrapped in safeties to
         properly handle interactive rendering."""
 
         import matplotlib
         import matplotlib.pylab as pylab
 
         #print '*** Matplotlib runner ***' # dbg
         # turn off rendering until end of script
         is_interactive = matplotlib.rcParams['interactive']
         matplotlib.interactive(False)
         safe_execfile(fname,*where,**kw)
         matplotlib.interactive(is_interactive)
         # make rendering call now, if the user tried to do it
         if pylab.draw_if_interactive.called:
             pylab.draw()
             pylab.draw_if_interactive.called = False
 
     return mpl_execfile
 
 
 def select_figure_format(shell, fmt):
     """Select figure format for inline backend, either 'png' or 'svg'.
 
     Using this method ensures only one figure format is active at a time.
     """
     from matplotlib.figure import Figure
     from IPython.zmq.pylab import backend_inline
 
     svg_formatter = shell.display_formatter.formatters['image/svg+xml']
     png_formatter = shell.display_formatter.formatters['image/png']
 
     if fmt=='png':
         svg_formatter.type_printers.pop(Figure, None)
         png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png'))
     elif fmt=='svg':
         png_formatter.type_printers.pop(Figure, None)
         svg_formatter.for_type(Figure, lambda fig: print_figure(fig, 'svg'))
     else:
         raise ValueError("supported formats are: 'png', 'svg', not %r"%fmt)
 
     # set the format to be used in the backend()
     backend_inline._figure_format = fmt
 
 #-----------------------------------------------------------------------------
 # Code for initializing matplotlib and importing pylab
 #-----------------------------------------------------------------------------
 
 
 def find_gui_and_backend(gui=None):
     """Given a gui string return the gui and mpl backend.
 
     Parameters
     ----------
     gui : str
         Can be one of ('tk','gtk','wx','qt','qt4','inline').
 
     Returns
     -------
     A tuple of (gui, backend) where backend is one of ('TkAgg','GTKAgg',
     'WXAgg','Qt4Agg','module://IPython.zmq.pylab.backend_inline').
     """
 
     import matplotlib
 
     if gui and gui != 'auto':
         # select backend based on requested gui
         backend = backends[gui]
     else:
         backend = matplotlib.rcParams['backend']
         # In this case, we need to find what the appropriate gui selection call
         # should be for IPython, so we can activate inputhook accordingly
         gui = backend2gui.get(backend, None)
     return gui, backend
 
 
 def activate_matplotlib(backend):
     """Activate the given backend and set interactive to True."""
 
     import matplotlib
     matplotlib.interactive(True)
 
     # Matplotlib had a bug where even switch_backend could not force
     # the rcParam to update. This needs to be set *before* the module
     # magic of switch_backend().
     matplotlib.rcParams['backend'] = backend
 
     import matplotlib.pyplot
     matplotlib.pyplot.switch_backend(backend)
 
     # This must be imported last in the matplotlib series, after
     # backend/interactivity choices have been made
     import matplotlib.pylab as pylab
 
     pylab.show._needmain = False
     # We need to detect at runtime whether show() is called by the user.
     # For this, we wrap it into a decorator which adds a 'called' flag.
     pylab.draw_if_interactive = flag_calls(pylab.draw_if_interactive)
 
 
 def import_pylab(user_ns, import_all=True):
     """Import the standard pylab symbols into user_ns."""
 
     # Import numpy as np/pyplot as plt are conventions we're trying to
     # somewhat standardize on.  Making them available to users by default
     # will greatly help this.
     s = ("import numpy\n"
           "import matplotlib\n"
           "from matplotlib import pylab, mlab, pyplot\n"
           "np = numpy\n"
           "plt = pyplot\n"
           )
     exec s in user_ns
 
     if import_all:
         s = ("from matplotlib.pylab import *\n"
              "from numpy import *\n")
         exec s in user_ns
 
 
 def configure_inline_support(shell, backend, user_ns=None):
     """Configure an IPython shell object for matplotlib use.
 
     Parameters
     ----------
     shell : InteractiveShell instance
 
     backend : matplotlib backend
 
     user_ns : dict
       A namespace where all configured variables will be placed.  If not given,
       the `user_ns` attribute of the shell object is used.
     """
     # If using our svg payload backend, register the post-execution
     # function that will pick up the results for display.  This can only be
     # done with access to the real shell object.
 
     # Note: if we can't load the inline backend, then there's no point
     # continuing (such as in terminal-only shells in environments without
     # zeromq available).
     try:
         from IPython.zmq.pylab.backend_inline import InlineBackend
     except ImportError:
         return
+    from matplotlib import pyplot
 
     user_ns = shell.user_ns if user_ns is None else user_ns
     
     cfg = InlineBackend.instance(config=shell.config)
     cfg.shell = shell
     if cfg not in shell.configurables:
         shell.configurables.append(cfg)
 
     if backend == backends['inline']:
         from IPython.zmq.pylab.backend_inline import flush_figures
-        from matplotlib import pyplot
         shell.register_post_execute(flush_figures)
+
+        # Save rcParams that will be overwrittern
+        shell._saved_rcParams = dict()
+        for k in cfg.rc:
+            shell._saved_rcParams[k] = pyplot.rcParams[k]
         # load inline_rc
         pyplot.rcParams.update(cfg.rc)
         # Add 'figsize' to pyplot and to the user's namespace
         user_ns['figsize'] = pyplot.figsize = figsize
+    else:
+        from IPython.zmq.pylab.backend_inline import flush_figures
+        if flush_figures in shell._post_execute:
+            shell._post_execute.pop(flush_figures)
+        if hasattr(shell, '_saved_rcParams'):
+            pyplot.rcParams.update(shell._saved_rcParams)
+            del shell._saved_rcParams
 
     # Setup the default figure format
     fmt = cfg.figure_format
     select_figure_format(shell, fmt)
 
     # The old pastefig function has been replaced by display
     from IPython.core.display import display
     # Add display and getfigs to the user's namespace
     user_ns['display'] = display
     user_ns['getfigs'] = getfigs
 
 
 def pylab_activate(user_ns, gui=None, import_all=True, shell=None):
     """Activate pylab mode in the user's namespace.
 
     Loads and initializes numpy, matplotlib and friends for interactive use.
 
     Parameters
     ----------
     user_ns : dict
       Namespace where the imports will occur.
 
     gui : optional, string
       A valid gui name following the conventions of the %gui magic.
 
     import_all : optional, boolean
       If true, an 'import *' is done from numpy and pylab.
 
     Returns
     -------
     The actual gui used (if not given as input, it was obtained from matplotlib
     itself, and will be needed next to configure IPython's gui integration.
     """
     gui, backend = find_gui_and_backend(gui)
     activate_matplotlib(backend)
     import_pylab(user_ns, import_all)
     if shell is not None:
         configure_inline_support(shell, backend, user_ns)
         
     print """
 Welcome to pylab, a matplotlib-based Python environment [backend: %s].
 For more information, type 'help(pylab)'.""" % backend
     # flush stdout, just to be safe
     sys.stdout.flush()
     
     return gui