Move testing for PIL[low] in the _figure_format_changed(...) function instead

of testing it at module startup. The test is only run if figure_format is jpg.

In help/error messages, refer to PIL/Pillow (i.e. not just PIL).

IPython/core/pylabtools.py

@@ -1,346 +1,344 b''
 # -*- coding: utf-8 -*-
 """Pylab (matplotlib) support utilities.
 
 Authors
 -------
 
 * Fernando Perez.
 * Brian Granger
 """
 from __future__ import print_function
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2009  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.core.display import _pngxy
 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',
             'gtk3': 'GTK3Agg',
             'wx': 'WXAgg',
             'qt': 'Qt4Agg', # qt3 not supported
             'qt4': 'Qt4Agg',
             'osx': 'MacOSX',
             'inline' : 'module://IPython.kernel.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()))
 # Our tests expect backend2gui to just return 'qt'
 backend2gui['Qt4Agg'] = 'qt'
 # 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['GTK3Cairo'] = 'gtk3'
 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', quality=90):
-    """Convert a figure to svg, jpg (if PIL is installed) or png for inline display."""
+    """Convert a figure to svg, png or jpg for inline display."""
     from matplotlib import rcParams
     # 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()
     dpi = rcParams['savefig.dpi']
     if fmt == 'retina':
         dpi = dpi * 2
         fmt = 'png'
     fig.canvas.print_figure(bytes_io, format=fmt, bbox_inches='tight',
                             facecolor=fc, edgecolor=ec, dpi=dpi, quality=quality)
     data = bytes_io.getvalue()
     return data
     
 def retina_figure(fig):
     """format a figure as a pixel-doubled (retina) PNG"""
     pngdata = print_figure(fig, fmt='retina')
     w, h = _pngxy(pngdata)
     metadata = dict(width=w//2, height=h//2)
     return pngdata, metadata
 
 # 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, quality):
-    """Select figure format for inline backend, can be 'png', 'retina', or 'svg'.
+    """Select figure format for inline backend, can be 'png', 'retina', 'jpg', or 'svg'.
 
     Using this method ensures only one figure format is active at a time.
     """
     from matplotlib.figure import Figure
     from IPython.kernel.zmq.pylab import backend_inline
 
     svg_formatter = shell.display_formatter.formatters['image/svg+xml']
     png_formatter = shell.display_formatter.formatters['image/png']
     jpg_formatter = shell.display_formatter.formatters['image/jpeg']
 
+    [ f.type_printers.pop(Figure, None) for f in {svg_formatter, png_formatter, jpg_formatter} ]
+
     if fmt == 'png':
-        svg_formatter.pop(Figure, None)
         png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png'))
-    elif fmt in ('jpg', 'jpeg'):
-        svg_formatter.type_printers.pop(Figure, None)
-        jpg_formatter.for_type(Figure, lambda fig: print_figure(fig, 'jpg', quality))
     elif fmt in ('png2x', 'retina'):
-        svg_formatter.pop(Figure, None)
         png_formatter.for_type(Figure, retina_figure)
+    elif fmt in ('jpg', 'jpeg'):
+        jpg_formatter.for_type(Figure, lambda fig: print_figure(fig, 'jpg', quality))
     elif fmt == 'svg':
-        png_formatter.pop(Figure, None)
         svg_formatter.for_type(Figure, lambda fig: print_figure(fig, 'svg'))
     else:
-        raise ValueError("supported formats are: 'png', 'retina', 'svg', not %r" % fmt)
+        raise ValueError("supported formats are: 'png', 'retina', 'svg', 'jpg', 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, gui_select=None):
     """Given a gui string return the gui and mpl backend.
 
     Parameters
     ----------
     gui : str
         Can be one of ('tk','gtk','wx','qt','qt4','inline').
     gui_select : str
         Can be one of ('tk','gtk','wx','qt','qt4','inline').
         This is any gui already selected by the shell.
 
     Returns
     -------
     A tuple of (gui, backend) where backend is one of ('TkAgg','GTKAgg',
     'WXAgg','Qt4Agg','module://IPython.kernel.zmq.pylab.backend_inline').
     """
 
     import matplotlib
 
     if gui and gui != 'auto':
         # select backend based on requested gui
         backend = backends[gui]
     else:
         # We need to read the backend from the original data structure, *not*
         # from mpl.rcParams, since a prior invocation of %matplotlib may have
         # overwritten that.
         # WARNING: this assumes matplotlib 1.1 or newer!!
         backend = matplotlib.rcParamsOrig['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)
 
         # If we have already had a gui active, we need it and inline are the
         # ones allowed.
         if gui_select and gui != gui_select:
             gui = gui_select
             backend = backends[gui]
 
     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):
     """Populate the namespace with pylab-related values.
     
     Imports matplotlib, pylab, numpy, and everything from pylab and numpy.
     
     Also imports a few names from IPython (figsize, display, getfigs)
     
     """
 
     # 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, user_ns)
     
     if import_all:
         s = ("from matplotlib.pylab import *\n"
              "from numpy import *\n")
         exec(s, user_ns)
     
     # IPython symbols to add
     user_ns['figsize'] = figsize
     from IPython.core.display import display
     # Add display and getfigs to the user's namespace
     user_ns['display'] = display
     user_ns['getfigs'] = getfigs
 
 
 def configure_inline_support(shell, backend):
     """Configure an IPython shell object for matplotlib use.
 
     Parameters
     ----------
     shell : InteractiveShell instance
 
     backend : matplotlib backend
     """
     # 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.kernel.zmq.pylab.backend_inline import InlineBackend
     except ImportError:
         return
     from matplotlib import pyplot
 
     cfg = InlineBackend.instance(parent=shell)
     cfg.shell = shell
     if cfg not in shell.configurables:
         shell.configurables.append(cfg)
 
     if backend == backends['inline']:
         from IPython.kernel.zmq.pylab.backend_inline import flush_figures
         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)
     else:
         from IPython.kernel.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
     select_figure_format(shell, cfg.figure_format, cfg.quality)
 

IPython/kernel/zmq/pylab/config.py

@@ -1,104 +1,108 b''
 """Configurable for configuring the IPython inline backend
 
 This module does not import anything from matplotlib.
 """
 #-----------------------------------------------------------------------------
 #       Copyright (C) 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
 #-----------------------------------------------------------------------------
 
 from IPython.config.configurable import SingletonConfigurable
 from IPython.utils.traitlets import Dict, Instance, CaselessStrEnum, Bool, Int
 from IPython.utils.warn import warn
 
 #-----------------------------------------------------------------------------
 # Configurable for inline backend options
 #-----------------------------------------------------------------------------
 
-try:
-    from PIL import Image
-    has_pil = True
-except:
-    has_pil = False
+def pil_available():
+    """Test if PIL/Pillow is available"""
+    out = False
+    try:
+        from PIL import Image
+        out = True
+    except:
+        pass
+    return out
 
 # inherit from InlineBackendConfig for deprecation purposes
 class InlineBackendConfig(SingletonConfigurable):
     pass
 
 class InlineBackend(InlineBackendConfig):
     """An object to store configuration of the inline backend."""
 
     def _config_changed(self, name, old, new):
         # warn on change of renamed config section
         if new.InlineBackendConfig != old.InlineBackendConfig:
             warn("InlineBackendConfig has been renamed to InlineBackend")
         super(InlineBackend, self)._config_changed(name, old, new)
 
     # The typical default figure size is too large for inline use,
     # so we shrink the figure size to 6x4, and tweak fonts to
     # make that fit.
     rc = Dict({'figure.figsize': (6.0,4.0),
         # play nicely with white background in the Qt and notebook frontend
         'figure.facecolor': (1,1,1,0),
         'figure.edgecolor': (1,1,1,0),
         # 12pt labels get cutoff on 6x4 logplots, so use 10pt.
         'font.size': 10,
         # 72 dpi matches SVG/qtconsole
         # this only affects PNG export, as SVG has no dpi setting
         'savefig.dpi': 72,
         # 10pt still needs a little more room on the xlabel:
         'figure.subplot.bottom' : .125
         }, config=True,
         help="""Subset of matplotlib rcParams that should be different for the
         inline backend."""
     )
 
-    fmts = ['svg', 'png', 'retina']
 
-    if has_pil:
-        # If we have PIL using jpeg as inline image format can save some bytes.
-        fmts.append('jpg')
-
-    # Matplotlib's JPEG printer supports a quality option that can be tweaked.
-    # We expose it only if PIL is available so the user isn't confused. But it
-    # isn't guarded by "has_pil" test because core/pylabtools.py expects this
-    # field OR we need to propagate the has_pil test to that module too.
-    quality = Int(default_value=90, config=has_pil,
-                  help="Quality of compression [0-100], currently for lossy JPEG only.")
-
-    figure_format = CaselessStrEnum(fmts, default_value='png', config=True,
-        help="The image format for figures with the inline backend.")
+    figure_format = CaselessStrEnum(['svg', 'png', 'retina', 'jpg'],
+                                    default_value='png', config=True,
+                                    help="""The image format for figures with the inline backend.
+                                    JPEG requires the PIL/Pillow library.""")
 
     def _figure_format_changed(self, name, old, new):
         from IPython.core.pylabtools import select_figure_format
+        if new in {"jpg", "jpeg"}:
+            if not pil_available():
+                raise TraitError("Requires PIL/Pillow for JPG figures")
         if self.shell is None:
             return
         else:
             select_figure_format(self.shell, new)
+
+    quality = Int(default_value=90, config=True,
+                  help="Quality of compression [0-100], currently for lossy JPEG only.")
+
+    def _quality_changed(self, name, old, new):
+        if new < 0 or new > 100:
+            raise TraitError("figure quality must be in [0-100] range.")
     
     close_figures = Bool(True, config=True,
         help="""Close all figures at the end of each cell.
         
         When True, ensures that each cell starts with no active figures, but it
         also means that one must keep track of references in order to edit or
         redraw figures in subsequent cells. This mode is ideal for the notebook,
         where residual plots from other cells might be surprising.
         
         When False, one must call figure() to create new figures. This means
         that gcf() and getfigs() can reference figures created in other cells,
         and the active figure can continue to be edited with pylab/pyplot
         methods that reference the current active figure. This mode facilitates
         iterative editing of figures, and behaves most consistently with
         other matplotlib backends, but figure barriers between cells must
         be explicit.
         """)
 
     shell = Instance('IPython.core.interactiveshell.InteractiveShellABC')