enable retina matplotlib figures

IPython/core/pylabtools.py

@@ -1,370 +1,391 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 struct
 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.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()))
 # 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."""
+    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
     fig.canvas.print_figure(bytes_io, format=fmt, bbox_inches='tight',
-                            facecolor=fc, edgecolor=ec)
+                            facecolor=fc, edgecolor=ec, dpi=dpi)
     data = bytes_io.getvalue()
     return data
 
+def pngxy(data):
+    """read the width/height from a PNG header"""
+    ihdr = data.index(b'IHDR')
+    # next 8 bytes are width/height
+    w4h4 = data[ihdr+4:ihdr+12]
+    return struct.unpack('>ii', w4h4)
+
+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):
-    """Select figure format for inline backend, either 'png' or 'svg'.
+    """Select figure format for inline backend, can be 'png', 'retina', 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']
 
     if fmt=='png':
         svg_formatter.type_printers.pop(Figure, None)
         png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png'))
+    elif fmt in ('png2x', 'retina'):
+        svg_formatter.type_printers.pop(Figure, None)
+        png_formatter.for_type(Figure, retina_figure)
     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)
+        raise ValueError("supported formats are: 'png', 'retina', '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, 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:
         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)
 
         # 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):
     """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.kernel.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.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)
         # Add 'figsize' to pyplot and to the user's namespace
         user_ns['figsize'] = pyplot.figsize = figsize
     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
     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, welcome_message=False):
     """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.
 
     welcome_message : optional, boolean
       If true, print a welcome message about pylab, which includes the backend
       being used.
 
     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.
     """
     pylab_gui_select = shell.pylab_gui_select if shell is not None else None
     # Try to find the appropriate gui and backend for the settings
     gui, backend = find_gui_and_backend(gui, pylab_gui_select)
     if shell is not None and gui != 'inline':
         # If we have our first gui selection, store it
         if pylab_gui_select is None:
             shell.pylab_gui_select = gui
         # Otherwise if they are different
         elif gui != pylab_gui_select:
             print ('Warning: Cannot change to a different GUI toolkit: %s.'
                     ' Using %s instead.' % (gui, pylab_gui_select))
             gui, backend = find_gui_and_backend(pylab_gui_select)
     activate_matplotlib(backend)
     import_pylab(user_ns, import_all)
     if shell is not None:
         configure_inline_support(shell, backend, user_ns)
     if welcome_message:
         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

IPython/kernel/zmq/pylab/backend_inline.py

@@ -1,215 +1,215 b''
 """Produce SVG versions of active plots for display by the rich Qt frontend.
 """
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 from __future__ import print_function
 
 # Standard library imports
 import sys
 
 # Third-party imports
 import matplotlib
 from matplotlib.backends.backend_agg import new_figure_manager, FigureCanvasAgg
 from matplotlib._pylab_helpers import Gcf
 
 # Local imports.
 from IPython.config.configurable import SingletonConfigurable
 from IPython.core.display import display
 from IPython.core.displaypub import publish_display_data
 from IPython.core.pylabtools import print_figure, select_figure_format
-from IPython.utils.traitlets import Dict, Instance, CaselessStrEnum, CBool
+from IPython.utils.traitlets import Dict, Instance, CaselessStrEnum, Bool
 from IPython.utils.warn import warn
 
 #-----------------------------------------------------------------------------
 # Configurable for inline backend options
 #-----------------------------------------------------------------------------
 # 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': 'white',
         'figure.edgecolor': 'white',
         # 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."""
     )
 
-    figure_format = CaselessStrEnum(['svg', 'png'], default_value='png', config=True,
+    figure_format = CaselessStrEnum(['svg', 'png', 'retina'], default_value='png', config=True,
         help="The image format for figures with the inline backend.")
 
     def _figure_format_changed(self, name, old, new):
         if self.shell is None:
             return
         else:
             select_figure_format(self.shell, new)
     
-    close_figures = CBool(True, config=True,
+    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')
 
 
 #-----------------------------------------------------------------------------
 # Functions
 #-----------------------------------------------------------------------------
 
 def show(close=None):
     """Show all figures as SVG/PNG payloads sent to the IPython clients.
 
     Parameters
     ----------
     close : bool, optional
       If true, a ``plt.close('all')`` call is automatically issued after
       sending all the figures. If this is set, the figures will entirely
       removed from the internal list of figures.
     """
     if close is None:
         close = InlineBackend.instance().close_figures
     try:
         for figure_manager in Gcf.get_all_fig_managers():
             display(figure_manager.canvas.figure)
     finally:
         show._to_draw = []
         if close:
             matplotlib.pyplot.close('all')
 
 
 
 # This flag will be reset by draw_if_interactive when called
 show._draw_called = False
 # list of figures to draw when flush_figures is called
 show._to_draw = []
 
 
 def draw_if_interactive():
     """
     Is called after every pylab drawing command
     """
     # signal that the current active figure should be sent at the end of
     # execution.  Also sets the _draw_called flag, signaling that there will be
     # something to send.  At the end of the code execution, a separate call to
     # flush_figures() will act upon these values
 
     fig = Gcf.get_active().canvas.figure
 
     # Hack: matplotlib FigureManager objects in interacive backends (at least
     # in some of them) monkeypatch the figure object and add a .show() method
     # to it.  This applies the same monkeypatch in order to support user code
     # that might expect `.show()` to be part of the official API of figure
     # objects.
     # For further reference:
     # https://github.com/ipython/ipython/issues/1612
     # https://github.com/matplotlib/matplotlib/issues/835
     
     if not hasattr(fig, 'show'):
         # Queue up `fig` for display
         fig.show = lambda *a: display(fig)
 
     # If matplotlib was manually set to non-interactive mode, this function
     # should be a no-op (otherwise we'll generate duplicate plots, since a user
     # who set ioff() manually expects to make separate draw/show calls).
     if not matplotlib.is_interactive():
         return
 
     # ensure current figure will be drawn, and each subsequent call
     # of draw_if_interactive() moves the active figure to ensure it is
     # drawn last
     try:
         show._to_draw.remove(fig)
     except ValueError:
         # ensure it only appears in the draw list once
         pass
     # Queue up the figure for drawing in next show() call
     show._to_draw.append(fig)
     show._draw_called = True
 
 
 def flush_figures():
     """Send all figures that changed
 
     This is meant to be called automatically and will call show() if, during
     prior code execution, there had been any calls to draw_if_interactive.
     
     This function is meant to be used as a post_execute callback in IPython,
     so user-caused errors are handled with showtraceback() instead of being
     allowed to raise.  If this function is not called from within IPython,
     then these exceptions will raise.
     """
     if not show._draw_called:
         return
     
     if InlineBackend.instance().close_figures:
         # ignore the tracking, just draw and close all figures
         try:
             return show(True)
         except Exception as e:
             # safely show traceback if in IPython, else raise
             try:
                 get_ipython
             except NameError:
                 raise e
             else:
                 get_ipython().showtraceback()
                 return
     try:
         # exclude any figures that were closed:
         active = set([fm.canvas.figure for fm in Gcf.get_all_fig_managers()])
         for fig in [ fig for fig in show._to_draw if fig in active ]:
             try:
                 display(fig)
             except Exception as e:
                 # safely show traceback if in IPython, else raise
                 try:
                     get_ipython
                 except NameError:
                     raise e
                 else:
                     get_ipython().showtraceback()
                     break
     finally:
         # clear flags for next round
         show._to_draw = []
         show._draw_called = False
 
 
 # Changes to matplotlib in version 1.2 requires a mpl backend to supply a default
 # figurecanvas. This is set here to a Agg canvas
 # See https://github.com/matplotlib/matplotlib/pull/1125
 FigureCanvas = FigureCanvasAgg