Oct 31, 2023 · Oct 19, 2023 · Oct 19, 2023 · Oct 26, 2023 · Oct 31, 2023 · Oct 21, 2023
diff --git a/galleries/users_explain/figure/figure_intro.rst b/galleries/users_explain/figure/figure_intro.rst
 ..seealso::
 :ref:`interactive_figures`.

 ..note::

   If you only need to use the classic notebook (i.e. ``notebook<7``),
   you can use:

   ..sourcecode::ipython

   %matplotlib notebook

 Standalone scripts and interactive use
 --------------------------------------

diff --git a/galleries/users_explain/figure/interactive.rst b/galleries/users_explain/figure/interactive.rst
 `.pyplot.subplots`
    Creates a new `.Figure` and fills it with a grid of `~.axes.Axes`

 `.pyplot` has a notion of "The Current Figure" which can be accessed
 through `.pyplot.gcf` and a notion of "The Current Axes" accessed
 through `.pyplot.gca`.  Almost all of the functions in `.pyplot` pass
 through the current `.Figure` / `~.axes.Axes` (or create one) as
 appropriate.
 `.pyplot.gcf`
    Get the current `.Figure`. If there is current no figure on the pyplot figure
    stack, a new figure is created

 `.pyplot.gca`
    Get the current `~.axes.Axes`. If there is current no Axes on the Figure,
    a new one is created

 Almost all of the functions in `.pyplot` pass through the current `.Figure` / `~.axes.Axes`
 (or create one) as appropriate.

 Matplotlib keeps a reference to all of the open figures
 created via `pyplot.figure` or `pyplot.subplots` so that the figures will not be garbage
 .. seealso::

   For more discussion of Matplotlib's event system and integrated event loops:

   - :ref:`interactive_figures_and_eventloops`
   - :ref:`event-handling`


 .. warning::

   Using `.Figure.show` it is possible to display a figure on
   Using `.Figure.show`, it is possible to display a figure on
   the screen without starting the event loop and without being in
   interactive mode.  This may work (depending on the GUI toolkit) but
   will likely result in a non-responsive figure.
 .. image:: ../../../_static/toolbar.png

 All figure windows come with a navigation toolbar, which can be used
 to navigate through the data set.  Here is a description of each of
 the buttons at the bottom of the toolbar
 to navigate through the data set.

 .. image:: ../../../../lib/matplotlib/mpl-data/images/home_large.png

 .. image:: ../../../../lib/matplotlib/mpl-data/images/forward_large.png

 The ``Home``, ``Forward`` and ``Back`` buttons
    These areakin to a web browser's home, forward and back controls.
    These aresimilar to a web browser's home, forward and back controls.
    ``Forward`` and ``Back`` are used to navigate back and forth between
    previously defined views.  They have no meaning unless you have already
    navigated somewhere else using the pan and zoom buttons.  This is analogous
    to trying to click ``Back`` on your web browser before visiting a
    new page or ``Forward`` before you have gone back to a page --
    nothing happens.  ``Home`` always takes you to the
    first, default view of your data. Again, all of these buttons should
    feel very familiar to any user of a web browser.
    nothing happens.  ``Home`` takes you to the
    first, default view of your data.

 .. image:: ../../../../lib/matplotlib/mpl-data/images/move_large.png

 The ``Pan/Zoom`` button
    This button has two modes: pan and zoom.  Click thetoolbar button
    This button has two modes: pan and zoom.  Click the``Pan/Zoom`` button
    to activate panning and zooming, then put your mouse somewhere
    over an axes.  Press the left mouse button and hold it to pan the
    figure, dragging it to a new position.  When you release it, the
    the right mouse button to zoom, dragging it to a new position.
    The x axis will be zoomed in proportionately to the rightward
    movement and zoomed out proportionately to the leftward movement.
    The same is true for the y axis and up/down motions.  The point under your
    mouse when you begin the zoom remains stationary, allowing you to
    The same is true for the y axis and up/down motions (up zooms in, down zooms out).
 The point under yourmouse when you begin the zoom remains stationary, allowing you to
    zoom in or out around that point as much as you wish.  You can use the
    modifier keys 'x', 'y' or 'CONTROL' to constrain the zoom to the x
    axis, the y axis, or aspect ratio preserve, respectively.

 .. image:: ../../../../lib/matplotlib/mpl-data/images/zoom_to_rect_large.png

 The ``Zoom-to-rectangle`` button
    Click this toolbar button to activate this mode.  Put your mouse somewhere
    over an axes and press a mouse button.  Define a rectangular region by
 The ``Zoom-to-Rectangle`` button
    Put your mouse somewhere over an axes and press a mouse button.  Define a rectangular region by
    dragging the mouse while holding the button to a new location.  When using
    the left mouse button, the axes view limits will be zoomed to the defined
    region.  When using the right mouse button, the axes view limits will be
 .. image:: ../../../../lib/matplotlib/mpl-data/images/subplots_large.png

 The ``Subplot-configuration`` button
    Use thistool to configure the appearance of the subplot:
 you can stretch or compress the left, right, top, or bottom
    Use thisbutton to configure the appearance of the subplot.
 You can stretch or compress the left, right, top, or bottom
    side of the subplot, or the space between the rows or
    space between the columns.

   >>> plt.ion()
   >>>

 however this does not ensure that the event hook is properly installed
 However, this does not ensure that the event hook is properly installed
 and your figures may not be responsive.  Please consult the
 documentation of your GUI toolkit for details.

 Jupyter Notebooks / JupyterLab
 ------------------------------

 .. note::

   To get the interactive functionality described here, you must be
   using an interactive backend.  The default backend in notebooks,
   the inline backend, is not.  `~ipykernel.pylab.backend_inline`
   renders the figure once and inserts a static image into the
   notebook when the cell is executed.  Because the images are static, they
   cannot be panned / zoomed, take user input, or be updated from other
   cells.

 To get interactive figures in the 'classic' notebook or Jupyter lab,
 use the `ipympl <https://matplotlib.org/ipympl>`__ backend
 (must be installed separately) which uses the **ipywidget** framework.

 to select and enable it.

 If you only need to use the classic notebook, you can use
 If you only need to use the classic notebook (i.e. ``notebook<7``), you can use

 .. sourcecode:: ipython

 which uses the `.backend_nbagg` backend provided by Matplotlib;
 however, nbagg does not work in Jupyter Lab.

 .. note::

   To get the interactive functionality described here, you must be
   using an interactive backend.  The default backend in notebooks,
   the inline backend, is not.  `~ipykernel.pylab.backend_inline`
   renders the figure once and inserts a static image into the
   notebook when the cell is executed.  Because the images are static, they
   cannot be panned / zoomed, take user input, or be updated from other
   cells.

 GUIs + Jupyter
 ^^^^^^^^^^^^^^
Original file line number	Diff line number	Diff line change
Expand Up		@@ -73,6 +73,15 @@ other than the default "inline" backend, you will likely need to use an ipython
		..seealso::
		:ref:`interactive_figures`.

		..note::

		If you only need to use the classic notebook (i.e. ``notebook<7``),
		you can use:

		..sourcecode::ipython

Copy link Member jklymakOct 21, 2023 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. This is empty Copy link ContributorAuthor mattymo30Oct 26, 2023 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Updated this similar to what's inside`figure_intro.rst`
		%matplotlib notebook

		Standalone scripts and interactive use
		--------------------------------------

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -36,11 +36,16 @@ that include interactive tools, a toolbar, a tool-tip, and
		`.pyplot.subplots`
		Creates a new `.Figure` and fills it with a grid of `~.axes.Axes`

		`.pyplot` has a notion of "The Current Figure" which can be accessed
		through `.pyplot.gcf` and a notion of "The Current Axes" accessed
		through `.pyplot.gca`. Almost all of the functions in `.pyplot` pass
		through the current `.Figure` / `~.axes.Axes` (or create one) as
		appropriate.
		`.pyplot.gcf`
		Get the current `.Figure`. If there is current no figure on the pyplot figure
		stack, a new figure is created

		`.pyplot.gca`
		Get the current `~.axes.Axes`. If there is current no Axes on the Figure,
		a new one is created

		Almost all of the functions in `.pyplot` pass through the current `.Figure` / `~.axes.Axes`
		(or create one) as appropriate.

		Matplotlib keeps a reference to all of the open figures
		created via `pyplot.figure` or `pyplot.subplots` so that the figures will not be garbage
Expand All		@@ -51,7 +56,6 @@ collected. `.Figure`\s can be closed and deregistered from `.pyplot` individuall
		.. seealso::

		For more discussion of Matplotlib's event system and integrated event loops:

		- :ref:`interactive_figures_and_eventloops`
		- :ref:`event-handling`

Expand DownExpand Up		@@ -189,7 +193,7 @@ the GUI main loop in some other way.

		.. warning::

		Using `.Figure.show` it is possible to display a figure on
		Using `.Figure.show`, it is possible to display a figure on
		the screen without starting the event loop and without being in
		interactive mode. This may work (depending on the GUI toolkit) but
		will likely result in a non-responsive figure.
Expand All		@@ -211,8 +215,7 @@ Interactive navigation
		.. image:: ../../../_static/toolbar.png

		All figure windows come with a navigation toolbar, which can be used
		to navigate through the data set. Here is a description of each of
		the buttons at the bottom of the toolbar
		to navigate through the data set.

		.. image:: ../../../../lib/matplotlib/mpl-data/images/home_large.png

Expand All		@@ -221,20 +224,19 @@ the buttons at the bottom of the toolbar
		.. image:: ../../../../lib/matplotlib/mpl-data/images/forward_large.png

		The ``Home``, ``Forward`` and ``Back`` buttons
		These areakin to a web browser's home, forward and back controls.
		These aresimilar to a web browser's home, forward and back controls.
		``Forward`` and ``Back`` are used to navigate back and forth between
		previously defined views. They have no meaning unless you have already
		navigated somewhere else using the pan and zoom buttons. This is analogous
		to trying to click ``Back`` on your web browser before visiting a
		new page or ``Forward`` before you have gone back to a page --
		nothing happens. ``Home`` always takes you to the
		first, default view of your data. Again, all of these buttons should
		feel very familiar to any user of a web browser.
		nothing happens. ``Home`` takes you to the
		first, default view of your data.

		.. image:: ../../../../lib/matplotlib/mpl-data/images/move_large.png

		The ``Pan/Zoom`` button
		This button has two modes: pan and zoom. Click thetoolbar button
		This button has two modes: pan and zoom. Click the``Pan/Zoom`` button
		to activate panning and zooming, then put your mouse somewhere
		over an axes. Press the left mouse button and hold it to pan the
		figure, dragging it to a new position. When you release it, the
Expand All		@@ -244,8 +246,8 @@ The ``Pan/Zoom`` button
		the right mouse button to zoom, dragging it to a new position.
		The x axis will be zoomed in proportionately to the rightward
		movement and zoomed out proportionately to the leftward movement.
		The same is true for the y axis and up/down motions. The point under your
		mouse when you begin the zoom remains stationary, allowing you to
		The same is true for the y axis and up/down motions (up zooms in, down zooms out).
		The point under yourmouse when you begin the zoom remains stationary, allowing you to
		zoom in or out around that point as much as you wish. You can use the
		modifier keys 'x', 'y' or 'CONTROL' to constrain the zoom to the x
		axis, the y axis, or aspect ratio preserve, respectively.
Expand All		@@ -257,9 +259,8 @@ The ``Pan/Zoom`` button

		.. image:: ../../../../lib/matplotlib/mpl-data/images/zoom_to_rect_large.png

		The ``Zoom-to-rectangle`` button
		Click this toolbar button to activate this mode. Put your mouse somewhere
		over an axes and press a mouse button. Define a rectangular region by
		The ``Zoom-to-Rectangle`` button
		Put your mouse somewhere over an axes and press a mouse button. Define a rectangular region by
		dragging the mouse while holding the button to a new location. When using
		the left mouse button, the axes view limits will be zoomed to the defined
		region. When using the right mouse button, the axes view limits will be
Expand All		@@ -268,8 +269,8 @@ The ``Zoom-to-rectangle`` button
		.. image:: ../../../../lib/matplotlib/mpl-data/images/subplots_large.png

		The ``Subplot-configuration`` button
		Use thistool to configure the appearance of the subplot:
		you can stretch or compress the left, right, top, or bottom
		Use thisbutton to configure the appearance of the subplot.
		You can stretch or compress the left, right, top, or bottom
		side of the subplot, or the space between the rows or
		space between the columns.

Expand DownExpand Up		@@ -325,7 +326,7 @@ Interactive mode works in the default Python prompt:
		>>> plt.ion()
		>>>

		however this does not ensure that the event hook is properly installed
		However, this does not ensure that the event hook is properly installed
		and your figures may not be responsive. Please consult the
		documentation of your GUI toolkit for details.

Expand All		@@ -335,16 +336,6 @@ documentation of your GUI toolkit for details.
		Jupyter Notebooks / JupyterLab
		------------------------------

		.. note::

		To get the interactive functionality described here, you must be
		using an interactive backend. The default backend in notebooks,
		the inline backend, is not. `~ipykernel.pylab.backend_inline`
		renders the figure once and inserts a static image into the
		notebook when the cell is executed. Because the images are static, they
		cannot be panned / zoomed, take user input, or be updated from other
		cells.

		To get interactive figures in the 'classic' notebook or Jupyter lab,
		use the `ipympl <https://matplotlib.org/ipympl>`__ backend
		(must be installed separately) which uses the ipywidget framework.
Expand All		@@ -356,7 +347,7 @@ If ``ipympl`` is installed use the magic:

		to select and enable it.

		If you only need to use the classic notebook, you can use
		If you only need to use the classic notebook (i.e. ``notebook<7``), you can use

		.. sourcecode:: ipython

Expand All		@@ -365,6 +356,16 @@ If you only need to use the classic notebook, you can use
		which uses the `.backend_nbagg` backend provided by Matplotlib;
		however, nbagg does not work in Jupyter Lab.

		.. note::
Copy link Member jklymakOct 21, 2023 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. I'd say this section could still be improved a lot, but no need to do it in this PR if you don't have ideas about fixing it. Copy link ContributorAuthor mattymo30Oct 26, 2023 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Currently don't have any ideas on improving this section, but I can definitely put some thought into it and make a new PR for it later?

		To get the interactive functionality described here, you must be
		using an interactive backend. The default backend in notebooks,
		the inline backend, is not. `~ipykernel.pylab.backend_inline`
		renders the figure once and inserts a static image into the
		notebook when the cell is executed. Because the images are static, they
		cannot be panned / zoomed, take user input, or be updated from other
		cells.

		GUIs + Jupyter
		^^^^^^^^^^^^^^

Expand Down