@@ -271,7 +271,7 @@ def my_plotter(ax, data1, data2, param_dict):
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# plotting windows pop up when they type commands. Some people run
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# `Jupyter <https://jupyter.org>`_ notebooks and draw inline plots for
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# quick data analysis. Others embed Matplotlib into graphical user
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- # interfaces like wxpython or pygtk to build rich applications. Some
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+ # interfaces like PyQt or PyGObject to build rich applications. Some
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# people use Matplotlib in batch scripts to generate postscript images
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# from numerical simulations, and still others run web application
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# servers to dynamically serve up graphs.
@@ -281,8 +281,8 @@ def my_plotter(ax, data1, data2, param_dict):
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# "frontend" is the user facing code, i.e., the plotting code, whereas the
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# "backend" does all the hard work behind-the-scenes to make the figure.
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# There are two types of backends: user interface backends (for use in
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- # pygtk, wxpython, tkinter, qt4, qt5, or macosx ; also referred to as
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- # "interactive backends") and hardcopy backends to make image files
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+ # PyQt/PySide, PyGObject, Tkinter, wxPython, or macOS/Cocoa) ; also referred to
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+ # as "interactive backends") and hardcopy backends to make image files
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# (PNG, SVG, PDF, PS; also referred to as "non-interactive backends").
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#
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# Selecting a backend
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