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install zmq.qui fixes problems with using ipython --pylab gtk
install zmq.qui fixes problems with using ipython --pylab gtk

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pylabtools.py
299 lines | 10.1 KiB | text/x-python | PythonLexer
# -*- coding: utf-8 -*-
"""Pylab (matplotlib) support utilities.
Authors
-------
* Fernando Perez.
* Brian Granger
"""
#-----------------------------------------------------------------------------
# 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
#-----------------------------------------------------------------------------
from cStringIO import StringIO
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'}
#-----------------------------------------------------------------------------
# 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)
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 figure_to_svg(fig):
"""Convert a figure to svg 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:
return
fc = fig.get_facecolor()
ec = fig.get_edgecolor()
fig.set_facecolor('white')
fig.set_edgecolor('white')
try:
string_io = StringIO()
fig.canvas.print_figure(string_io, format='svg')
svg = string_io.getvalue()
finally:
fig.set_facecolor(fc)
fig.set_edgecolor(ec)
return svg
# 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
#-----------------------------------------------------------------------------
# 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:
# 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
g2b = backends # maps gui names to mpl backend names
b2g = dict(zip(g2b.values(), g2b.keys())) # reverse dict
gui = b2g.get(backend, None)
return gui, backend
def activate_matplotlib(backend):
"""Activate the given backend and set interactive to True."""
import matplotlib
if backend.startswith('module://'):
# Work around bug in matplotlib: matplotlib.use converts the
# backend_id to lowercase even if a module name is specified!
matplotlib.rcParams['backend'] = backend
else:
matplotlib.use(backend)
matplotlib.interactive(True)
# This must be imported last in the matplotlib series, after
# backend/interactivity choices have been made
import matplotlib.pylab as pylab
# XXX For now leave this commented out, but depending on discussions with
# mpl-dev, we may be able to allow interactive switching...
#import matplotlib.pyplot
#matplotlib.pyplot.switch_backend(backend)
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, backend, import_all=True, shell=None):
"""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 shell is not None:
exec s in shell.user_ns_hidden
# 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.
if backend == backends['inline']:
from IPython.zmq.pylab.backend_inline import flush_svg
from matplotlib import pyplot
shell.register_post_execute(flush_svg)
# 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. This is configurable via Global.pylab_inline_rc,
# or rather it will be once the zmq kernel is hooked up to
# the config system.
default_rc = {
'figure.figsize': (6.0,4.0),
# 12pt labels get cutoff on 6x4 logplots, so use 10pt.
'font.size': 10,
# 10pt still needs a little more room on the xlabel:
'figure.subplot.bottom' : .125
}
rc = getattr(shell.config.Global, 'pylab_inline_rc', default_rc)
pyplot.rcParams.update(rc)
shell.config.Global.pylab_inline_rc = rc
# Add 'figsize' to pyplot and to the user's namespace
user_ns['figsize'] = pyplot.figsize = figsize
shell.user_ns_hidden['figsize'] = figsize
# The old pastefig function has been replaced by display
# Always add this svg formatter so display works.
from IPython.core.display import display, display_svg
svg_formatter = shell.display_formatter.formatters['image/svg+xml']
svg_formatter.for_type_by_name(
'matplotlib.figure','Figure',figure_to_svg
)
# Add display and display_png to the user's namespace
user_ns['display'] = display
shell.user_ns_hidden['display'] = display
user_ns['display_svg'] = display_svg
shell.user_ns_hidden['display_svg'] = display_svg
user_ns['getfigs'] = getfigs
shell.user_ns_hidden['getfigs'] = getfigs
if import_all:
s = ("from matplotlib.pylab import *\n"
"from numpy import *\n")
exec s in user_ns
if shell is not None:
exec s in shell.user_ns_hidden
def pylab_activate(user_ns, gui=None, import_all=True):
"""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, backend)
print """
Welcome to pylab, a matplotlib-based Python environment [backend: %s].
For more information, type 'help(pylab)'.""" % backend
return gui