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# -*- coding: utf-8 -*-
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"""Pylab (matplotlib) support utilities."""
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# Copyright (c) IPython Development Team.
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# Distributed under the terms of the Modified BSD License.
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from io import BytesIO
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from binascii import b2a_base64
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from functools import partial
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import warnings
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from IPython.core.display import _pngxy
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from IPython.utils.decorators import flag_calls
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# If user specifies a GUI, that dictates the backend, otherwise we read the
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# user's mpl default from the mpl rc structure
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backends = {
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"tk": "TkAgg",
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"gtk": "GTKAgg",
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"gtk3": "GTK3Agg",
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"gtk4": "GTK4Agg",
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"wx": "WXAgg",
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"qt4": "Qt4Agg",
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"qt5": "Qt5Agg",
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"qt6": "QtAgg",
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"qt": "Qt5Agg",
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"osx": "MacOSX",
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"nbagg": "nbAgg",
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"notebook": "nbAgg",
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"agg": "agg",
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"svg": "svg",
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"pdf": "pdf",
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"ps": "ps",
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"inline": "module://matplotlib_inline.backend_inline",
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"ipympl": "module://ipympl.backend_nbagg",
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"widget": "module://ipympl.backend_nbagg",
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}
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# We also need a reverse backends2guis mapping that will properly choose which
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# GUI support to activate based on the desired matplotlib backend. For the
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# most part it's just a reverse of the above dict, but we also need to add a
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# few others that map to the same GUI manually:
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backend2gui = dict(zip(backends.values(), backends.keys()))
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# In the reverse mapping, there are a few extra valid matplotlib backends that
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# map to the same GUI support
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backend2gui["GTK"] = backend2gui["GTKCairo"] = "gtk"
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backend2gui["GTK3Cairo"] = "gtk3"
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backend2gui["GTK4Cairo"] = "gtk4"
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backend2gui["WX"] = "wx"
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backend2gui["CocoaAgg"] = "osx"
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# There needs to be a hysteresis here as the new QtAgg Matplotlib backend
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# supports either Qt5 or Qt6 and the IPython qt event loop support Qt4, Qt5,
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# and Qt6.
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backend2gui["QtAgg"] = "qt"
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backend2gui["Qt4Agg"] = "qt"
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backend2gui["Qt5Agg"] = "qt"
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# And some backends that don't need GUI integration
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del backend2gui["nbAgg"]
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del backend2gui["agg"]
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del backend2gui["svg"]
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del backend2gui["pdf"]
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del backend2gui["ps"]
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del backend2gui["module://matplotlib_inline.backend_inline"]
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del backend2gui["module://ipympl.backend_nbagg"]
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#-----------------------------------------------------------------------------
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# Matplotlib utilities
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#-----------------------------------------------------------------------------
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def getfigs(*fig_nums):
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"""Get a list of matplotlib figures by figure numbers.
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If no arguments are given, all available figures are returned. If the
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argument list contains references to invalid figures, a warning is printed
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but the function continues pasting further figures.
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Parameters
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----------
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figs : tuple
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A tuple of ints giving the figure numbers of the figures to return.
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"""
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from matplotlib._pylab_helpers import Gcf
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if not fig_nums:
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fig_managers = Gcf.get_all_fig_managers()
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return [fm.canvas.figure for fm in fig_managers]
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else:
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figs = []
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for num in fig_nums:
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f = Gcf.figs.get(num)
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if f is None:
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print('Warning: figure %s not available.' % num)
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else:
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figs.append(f.canvas.figure)
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return figs
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def figsize(sizex, sizey):
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"""Set the default figure size to be [sizex, sizey].
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This is just an easy to remember, convenience wrapper that sets::
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matplotlib.rcParams['figure.figsize'] = [sizex, sizey]
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"""
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import matplotlib
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matplotlib.rcParams['figure.figsize'] = [sizex, sizey]
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def print_figure(fig, fmt="png", bbox_inches="tight", base64=False, **kwargs):
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"""Print a figure to an image, and return the resulting file data
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Returned data will be bytes unless ``fmt='svg'``,
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in which case it will be unicode.
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Any keyword args are passed to fig.canvas.print_figure,
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such as ``quality`` or ``bbox_inches``.
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If `base64` is True, return base64-encoded str instead of raw bytes
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for binary-encoded image formats
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.. versionadded:: 7.29
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base64 argument
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"""
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# When there's an empty figure, we shouldn't return anything, otherwise we
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# get big blank areas in the qt console.
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if not fig.axes and not fig.lines:
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return
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dpi = fig.dpi
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if fmt == 'retina':
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dpi = dpi * 2
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fmt = 'png'
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# build keyword args
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kw = {
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"format":fmt,
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"facecolor":fig.get_facecolor(),
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"edgecolor":fig.get_edgecolor(),
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"dpi":dpi,
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"bbox_inches":bbox_inches,
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}
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# **kwargs get higher priority
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kw.update(kwargs)
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bytes_io = BytesIO()
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if fig.canvas is None:
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from matplotlib.backend_bases import FigureCanvasBase
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FigureCanvasBase(fig)
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fig.canvas.print_figure(bytes_io, **kw)
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data = bytes_io.getvalue()
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if fmt == 'svg':
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data = data.decode('utf-8')
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elif base64:
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data = b2a_base64(data).decode("ascii")
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return data
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def retina_figure(fig, base64=False, **kwargs):
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"""format a figure as a pixel-doubled (retina) PNG
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If `base64` is True, return base64-encoded str instead of raw bytes
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for binary-encoded image formats
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.. versionadded:: 7.29
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base64 argument
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"""
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pngdata = print_figure(fig, fmt="retina", base64=False, **kwargs)
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# Make sure that retina_figure acts just like print_figure and returns
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# None when the figure is empty.
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if pngdata is None:
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return
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w, h = _pngxy(pngdata)
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metadata = {"width": w//2, "height":h//2}
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if base64:
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pngdata = b2a_base64(pngdata).decode("ascii")
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return pngdata, metadata
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# We need a little factory function here to create the closure where
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# safe_execfile can live.
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def mpl_runner(safe_execfile):
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"""Factory to return a matplotlib-enabled runner for %run.
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Parameters
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----------
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safe_execfile : function
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This must be a function with the same interface as the
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:meth:`safe_execfile` method of IPython.
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Returns
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-------
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A function suitable for use as the ``runner`` argument of the %run magic
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function.
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"""
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def mpl_execfile(fname,*where,**kw):
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"""matplotlib-aware wrapper around safe_execfile.
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Its interface is identical to that of the :func:`execfile` builtin.
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This is ultimately a call to execfile(), but wrapped in safeties to
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properly handle interactive rendering."""
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import matplotlib
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import matplotlib.pyplot as plt
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#print '*** Matplotlib runner ***' # dbg
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# turn off rendering until end of script
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is_interactive = matplotlib.rcParams['interactive']
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matplotlib.interactive(False)
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safe_execfile(fname,*where,**kw)
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matplotlib.interactive(is_interactive)
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# make rendering call now, if the user tried to do it
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if plt.draw_if_interactive.called:
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plt.draw()
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plt.draw_if_interactive.called = False
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# re-draw everything that is stale
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try:
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da = plt.draw_all
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except AttributeError:
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pass
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else:
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da()
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return mpl_execfile
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def _reshow_nbagg_figure(fig):
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"""reshow an nbagg figure"""
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try:
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reshow = fig.canvas.manager.reshow
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except AttributeError:
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raise NotImplementedError()
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else:
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reshow()
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def select_figure_formats(shell, formats, **kwargs):
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"""Select figure formats for the inline backend.
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Parameters
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==========
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shell : InteractiveShell
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The main IPython instance.
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formats : str or set
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One or a set of figure formats to enable: 'png', 'retina', 'jpeg', 'svg', 'pdf'.
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**kwargs : any
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Extra keyword arguments to be passed to fig.canvas.print_figure.
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"""
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import matplotlib
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from matplotlib.figure import Figure
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svg_formatter = shell.display_formatter.formatters['image/svg+xml']
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png_formatter = shell.display_formatter.formatters['image/png']
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jpg_formatter = shell.display_formatter.formatters['image/jpeg']
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pdf_formatter = shell.display_formatter.formatters['application/pdf']
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if isinstance(formats, str):
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formats = {formats}
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# cast in case of list / tuple
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formats = set(formats)
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[ f.pop(Figure, None) for f in shell.display_formatter.formatters.values() ]
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mplbackend = matplotlib.get_backend().lower()
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if mplbackend == 'nbagg' or mplbackend == 'module://ipympl.backend_nbagg':
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formatter = shell.display_formatter.ipython_display_formatter
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formatter.for_type(Figure, _reshow_nbagg_figure)
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supported = {'png', 'png2x', 'retina', 'jpg', 'jpeg', 'svg', 'pdf'}
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bad = formats.difference(supported)
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if bad:
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bs = "%s" % ','.join([repr(f) for f in bad])
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gs = "%s" % ','.join([repr(f) for f in supported])
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raise ValueError("supported formats are: %s not %s" % (gs, bs))
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if "png" in formats:
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png_formatter.for_type(
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Figure, partial(print_figure, fmt="png", base64=True, **kwargs)
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)
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if "retina" in formats or "png2x" in formats:
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png_formatter.for_type(Figure, partial(retina_figure, base64=True, **kwargs))
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if "jpg" in formats or "jpeg" in formats:
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jpg_formatter.for_type(
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Figure, partial(print_figure, fmt="jpg", base64=True, **kwargs)
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)
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if "svg" in formats:
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svg_formatter.for_type(Figure, partial(print_figure, fmt="svg", **kwargs))
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if "pdf" in formats:
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pdf_formatter.for_type(
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Figure, partial(print_figure, fmt="pdf", base64=True, **kwargs)
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)
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#-----------------------------------------------------------------------------
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# Code for initializing matplotlib and importing pylab
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#-----------------------------------------------------------------------------
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def find_gui_and_backend(gui=None, gui_select=None):
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"""Given a gui string return the gui and mpl backend.
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Parameters
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----------
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gui : str
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Can be one of ('tk','gtk','wx','qt','qt4','inline','agg').
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gui_select : str
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Can be one of ('tk','gtk','wx','qt','qt4','inline').
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This is any gui already selected by the shell.
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Returns
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-------
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A tuple of (gui, backend) where backend is one of ('TkAgg','GTKAgg',
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'WXAgg','Qt4Agg','module://matplotlib_inline.backend_inline','agg').
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"""
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import matplotlib
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if gui and gui != 'auto':
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# select backend based on requested gui
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backend = backends[gui]
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if gui == 'agg':
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gui = None
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else:
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# We need to read the backend from the original data structure, *not*
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# from mpl.rcParams, since a prior invocation of %matplotlib may have
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# overwritten that.
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# WARNING: this assumes matplotlib 1.1 or newer!!
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backend = matplotlib.rcParamsOrig['backend']
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# In this case, we need to find what the appropriate gui selection call
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# should be for IPython, so we can activate inputhook accordingly
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gui = backend2gui.get(backend, None)
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# If we have already had a gui active, we need it and inline are the
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# ones allowed.
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if gui_select and gui != gui_select:
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gui = gui_select
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backend = backends[gui]
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return gui, backend
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def activate_matplotlib(backend):
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"""Activate the given backend and set interactive to True."""
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import matplotlib
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matplotlib.interactive(True)
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# Matplotlib had a bug where even switch_backend could not force
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# the rcParam to update. This needs to be set *before* the module
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# magic of switch_backend().
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matplotlib.rcParams['backend'] = backend
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# Due to circular imports, pyplot may be only partially initialised
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# when this function runs.
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# So avoid needing matplotlib attribute-lookup to access pyplot.
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from matplotlib import pyplot as plt
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plt.switch_backend(backend)
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plt.show._needmain = False
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# We need to detect at runtime whether show() is called by the user.
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# For this, we wrap it into a decorator which adds a 'called' flag.
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plt.draw_if_interactive = flag_calls(plt.draw_if_interactive)
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def import_pylab(user_ns, import_all=True):
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"""Populate the namespace with pylab-related values.
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Imports matplotlib, pylab, numpy, and everything from pylab and numpy.
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Also imports a few names from IPython (figsize, display, getfigs)
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"""
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# Import numpy as np/pyplot as plt are conventions we're trying to
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# somewhat standardize on. Making them available to users by default
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# will greatly help this.
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s = ("import numpy\n"
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"import matplotlib\n"
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"from matplotlib import pylab, mlab, pyplot\n"
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"np = numpy\n"
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"plt = pyplot\n"
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)
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exec(s, user_ns)
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if import_all:
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s = ("from matplotlib.pylab import *\n"
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"from numpy import *\n")
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exec(s, user_ns)
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# IPython symbols to add
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user_ns['figsize'] = figsize
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from IPython.core.display import display
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# Add display and getfigs to the user's namespace
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user_ns['display'] = display
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user_ns['getfigs'] = getfigs
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def configure_inline_support(shell, backend):
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"""
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.. deprecated:: 7.23
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use `matplotlib_inline.backend_inline.configure_inline_support()`
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Configure an IPython shell object for matplotlib use.
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Parameters
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----------
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shell : InteractiveShell instance
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backend : matplotlib backend
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"""
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warnings.warn(
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"`configure_inline_support` is deprecated since IPython 7.23, directly "
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"use `matplotlib_inline.backend_inline.configure_inline_support()`",
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DeprecationWarning,
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stacklevel=2,
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)
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from matplotlib_inline.backend_inline import configure_inline_support as configure_inline_support_orig
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configure_inline_support_orig(shell, backend)
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