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Merge branch 'master' into pgf_pdf_pages
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‎doc/api/next_api_changes/2018-02-15-AL-deprecations.rst‎

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Deprecations
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````````````
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The following modules are deprecated:
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- :mod:`matplotlib.compat.subprocess`. This was a python 2 workaround, but all the
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functionality can now be found in the python 3 standard library
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:mod:`subprocess`.
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The following functions and classes are deprecated:
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- ``cbook.GetRealpathAndStat`` (which is only a helper for
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``get_realpath_and_stat``),
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- ``cbook.is_numlike`` (use ``isinstance(..., numbers.Number)`` instead),
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- ``mathtext.unichr_safe`` (use ``chr`` instead),
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- ``texmanager.dvipng_hack_alpha``,

‎doc/api/next_api_changes/2018-02-21-AL.rst‎

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``Axes3D.get_xlim``, ``get_ylim`` and ``get_zlim`` now return a tuple
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`````````````````````````````````````````````````````````````````````
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They previously returned an array. Returning a tuple is consistent with the
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behavior for 2D axes.

‎doc/devel/MEP/MEP28.rst‎

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With this approach, #2 depends and #1, and #4 depends on #3.
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There are two possible approaches to #2. The first and most direct would
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be to mirror the new ``transform_in`` and ``tranform_out`` parameters of
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be to mirror the new ``transform_in`` and ``transform_out`` parameters of
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``cbook.boxplot_stats`` in ``Axes.boxplot`` and pass them directly.
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The second approach would be to add ``statfxn`` and ``statfxn_args``
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parameters to ``Axes.boxplot``. Under this implementation, the default
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value of ``statfxn`` would be ``cbook.boxplot_stats``, but users could
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pass their own function. Then ``transform_in`` and ``tranform_out`` would
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pass their own function. Then ``transform_in`` and ``transform_out`` would
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then be passed as elements of the ``statfxn_args`` parameter.
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.. code:: python

‎doc/users/whats_new.rst‎

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@@ -310,11 +310,12 @@ Thus, to force usage of PGI when both bindings are installed, import it first.
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Cairo rendering for Qt and WX canvases
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--------------------------------------
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Cairo rendering for Qt, WX, and Tk canvases
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-------------------------------------------
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The new ``Qt4Cairo``, ``Qt5Cairo``, and ``WXCairo`` backends allow Qt and Wx
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canvases to use Cairo rendering instead of Agg.
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The new ``Qt4Cairo``, ``Qt5Cairo``, ``WXCairo``, and ``TkCairo``
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backends allow Qt, Wx, and Tk canvases to use Cairo rendering instead of
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Agg.
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Added support for QT in new ToolManager

‎examples/event_handling/ginput_manual_clabel_sgskip.py‎

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plt.waitforbuttonpress()
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happy = False
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while not happy:
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while True:
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pts = []
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while len(pts) < 3:
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tellme('Select 3 corners with mouse')
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tellme('Happy? Key click for yes, mouse click for no')
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happy = plt.waitforbuttonpress()
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if plt.waitforbuttonpress():
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break
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# Get rid of fill
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if not happy:
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for p in ph:
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p.remove()
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for p in ph:
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p.remove()
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##################################################
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tellme('Now do a nested zoom, click to begin')
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plt.waitforbuttonpress()
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happy = False
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while not happy:
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while True:
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tellme('Select two corners of zoom, middle mouse button to finish')
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pts = np.asarray(plt.ginput(2, timeout=-1))
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happy = len(pts) < 2
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if happy:
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if len(pts) < 2:
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break
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pts = np.sort(pts, axis=0)

‎examples/tests/backend_driver_sgskip.py‎

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)
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from matplotlib.compat import subprocess
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import subprocess
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def run(arglist):

‎examples/user_interfaces/embedding_in_wx2_sgskip.py‎

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"""
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from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
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from matplotlib.backends.backend_wx import NavigationToolbar2Wx
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from matplotlib.backends.backend_wx import NavigationToolbar2Wx as NavigationToolbar
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from matplotlib.figure import Figure
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import numpy as np
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self.add_toolbar() # comment this out for no toolbar
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def add_toolbar(self):
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self.toolbar = NavigationToolbar2Wx(self.canvas)
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self.toolbar = NavigationToolbar(self.canvas)
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self.toolbar.Realize()
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# By adding toolbar in sizer, we are able to put it at the bottom
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# of the frame - so appearance is closer to GTK version.

‎examples/user_interfaces/embedding_in_wx3_sgskip.py‎

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import matplotlib
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import matplotlib.cm as cm
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import matplotlib.cbook as cbook
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from matplotlib.backends.backend_wxagg import Toolbar, FigureCanvasWxAgg
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from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
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from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg as NavigationToolbar
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from matplotlib.figure import Figure
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import numpy as np
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self.fig = Figure((5, 4), 75)
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self.canvas = FigureCanvasWxAgg(self, -1, self.fig)
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self.toolbar = Toolbar(self.canvas) # matplotlib toolbar
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self.canvas = FigureCanvas(self, -1, self.fig)
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self.toolbar = NavigationToolbar(self.canvas) # matplotlib toolbar
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self.toolbar.Realize()
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# self.toolbar.set_active([0,1])
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‎examples/user_interfaces/embedding_in_wx4_sgskip.py‎

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"""
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from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
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from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg
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from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg as NavigationToolbar
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from matplotlib.backends.backend_wx import _load_bitmap
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from matplotlib.figure import Figure
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class MyNavigationToolbar(NavigationToolbar2WxAgg):
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class MyNavigationToolbar(NavigationToolbar):
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"""
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Extend the default wx toolbar with your own event handlers
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"""
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ON_CUSTOM = wx.NewId()
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def __init__(self, canvas, cankill):
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NavigationToolbar2WxAgg.__init__(self, canvas)
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NavigationToolbar.__init__(self, canvas)
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# for simplicity I'm going to reuse a bitmap from wx, you'll
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# probably want to add your own.

‎examples/user_interfaces/embedding_in_wx5_sgskip.py‎

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from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
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from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg as NavigationToolbar
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class Plot(wx.Panel):
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self.canvas = Canvas(self, -1, self.figure)
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self.toolbar = Toolbar(self.canvas)
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self.canvas = FigureCanvas(self, -1, self.figure)
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self.toolbar = NavigationToolbar(self.canvas)
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self.toolbar.Realize()
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sizer = wx.BoxSizer(wx.VERTICAL)

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