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‎doc/users/whats_new/rcparams.rst

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@@ -15,9 +15,17 @@ Added "figure.titlesize" and "figure.titleweight" keys to rcParams
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Two new keys were added to rcParams to control the default font size and weight
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used by the figure title (as emitted by ``pyplot.suptitle()``).
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``image.composite_image`` added to rcParams
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```````````````````````````````````````````
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Controls whether vector graphics backends (i.e. PDF, PS, and SVG) combine
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multiple images on a set of axes into a single composite image. Saving each
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image individually can be useful if you generate vector graphics files in
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matplotlib and then edit the files further in Inkscape or other programs.
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Added "toolmanager" to "toolbar" possible values
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````````````````````````````````````````````````
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The new value enables the use of ``ToolManager``
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‎doc/users/whats_new/toolmanager.rst

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ToolManager
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-----------
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Federico Ariza wrote the new `matplotlib.backend_managers.ToolManager` that comes as replacement for `NavigationToolbar2`
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`ToolManager` offers a new way of looking at the user interactions with the figures.
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Before we had the `NavigationToolbar2` with its own tools like `zoom/pan/home/save/...` and also we had the shortcuts like
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`yscale/grid/quit/....`
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`Toolmanager` relocate all those actions as `Tools` (located in `matplotlib.backend_tools`), and defines a way to `access/trigger/reconfigure` them.
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The `Toolbars` are replaced for `ToolContainers` that are just GUI interfaces to `trigger` the tools. But don't worry the default backends include a `ToolContainer` called `toolbar`
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.. note::
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For the moment the `ToolManager` is working only with `GTK3` and `Tk` backends.
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Make sure you are using one of those.
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Port for the rest of the backends is comming soon.
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To activate the `ToolManager` include the following at the top of your file:
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>>> matplotlib.rcParams['toolbar'] = 'toolmanager'
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Interact with the ToolContainer
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```````````````````````````````
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The most important feature is the ability to easily reconfigure the ToolContainer (aka toolbar).
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For example, if we want to remove the "forward" button we would just do.
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>>> fig.canvas.manager.toolmanager.remove_tool('forward')
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Now if you want to programmatically trigger the "home" button
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>>> fig.canvas.manager.toolmanager.trigger_tool('home')
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New Tools
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`````````
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It is possible to add new tools to the ToolManager
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A very simple tool that prints "You're awesome" would be::
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from matplotlib.backend_tools import ToolBase
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class AwesomeTool(ToolBase):
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def trigger(self, *args, **kwargs):
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print("You're awesome")
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To add this tool to `ToolManager`
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>>> fig.canvas.manager.toolmanager.add_tool('Awesome', AwesomeTool)
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If we want to add a shortcut ("d") for the tool
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>>> fig.canvas.manager.toolmanager.update_keymap('Awesome', 'd')
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To add it to the toolbar inside the group 'foo'
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>>> fig.canvas.manager.toolbar.add_tool('Awesome', 'foo')
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There is a second class of tools, "Toggleable Tools", this are almost the same as our basic tools, just that belong to a group, and are mutually exclusive inside that group.
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For tools derived from `ToolToggleBase` there are two basic methods `enable` and `disable` that are called automatically whenever it is toggled.
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A full example is located in :ref:`user_interfaces-toolmanager`

‎examples/user_interfaces/toolmanager.py

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'''This example demonstrates how the `matplotlib.backend_bases.NavigationBase`
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class allows to:
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'''This example demonstrates how to:
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* Modify the Toolbar
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* Create tools
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* Add tools
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* Remove tools
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Using `matplotlib.backend_managers.ToolManager`
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'''
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‎lib/matplotlib/backend_bases.py

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"""
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Base class for all tool containers, e.g. toolbars.
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Attributes
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Attributes
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----------
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toolmanager : `ToolManager` object that holds the tools that
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this `ToolContainer` wants to communicate with.

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