matplotlib.backend_managers

class matplotlib.backend_managers.ToolEvent(name, sender, tool, data=None) [source]

Bases: object

Event for tool manipulation (add/remove).

class matplotlib.backend_managers.ToolManager(figure=None) [source]

Bases: object

Manager for actions triggered by user interactions (key press, toolbar clicks, ...) on a Figure.

Attributes:
figureFigure

Figure that holds the canvas.

keypresslockLockDraw

LockDraw object to know if the canvas key_press_event is locked.

messagelockLockDraw

LockDraw object to know if the message is available to write.

property active_toggle

Currently toggled tools.

add_tool(self, name, tool, *args, **kwargs) [source]

Add tool to ToolManager.

If successful, adds a new event tool_trigger_{name} where {name} is the name of the tool; the event is fired every time the tool is triggered.

Parameters:
namestr

Name of the tool, treated as the ID, has to be unique.

toolclass_like, i.e. str or type

Reference to find the class of the Tool to added.

See also

matplotlib.backend_tools.ToolBase
The base class for tools.

Notes

args and kwargs get passed directly to the tools constructor.

property canvas

Canvas managed by FigureManager.

property figure

Figure that holds the canvas.

get_tool(self, name, warn=True) [source]

Return the tool object with the given name.

For convenience, this passes tool objects through.

Parameters:
namestr or ToolBase

Name of the tool, or the tool itself.

warnbool, default: True

Whether a warning should be emitted it no tool with the given name exists.

Returns:
ToolBase or None

The tool or None if no tool with the given name exists.

get_tool_keymap(self, name) [source]

Return the keymap associated with the specified tool.

Parameters:
namestr

Name of the Tool.

Returns:
list of str

List of keys associated with the tool.

message_event(self, message, sender=None) [source]

Emit a ToolManagerMessageEvent.

remove_tool(self, name) [source]

Remove tool named name.

Parameters:
namestr

Name of the tool.

set_figure(self, figure, update_tools=True) [source]

Bind the given figure to the tools.

Parameters:
figureFigure
update_toolsbool, default: True

Force tools to update figure.

toolmanager_connect(self, s, func) [source]

Connect event with string s to func.

Parameters:
sstr

The name of the event. The following events are recognized:

  • 'tool_message_event'
  • 'tool_removed_event'
  • 'tool_added_event'

For every tool added a new event is created

  • 'tool_trigger_TOOLNAME', where TOOLNAME is the id of the tool.
funccallable

Callback function for the toolmanager event with signature:

def func(event: ToolEvent) -> Any
Returns:
cid

The callback id for the connection. This can be used in toolmanager_disconnect.

toolmanager_disconnect(self, cid) [source]

Disconnect callback id cid.

Example usage:

cid = toolmanager.toolmanager_connect('tool_trigger_zoom', onpress)
#...later
toolmanager.toolmanager_disconnect(cid)
property tools

A dict mapping tool name -> controlled tool.

trigger_tool(self, name, sender=None, canvasevent=None, data=None) [source]

Trigger a tool and emit the tool_trigger_{name} event.

Parameters:
namestr

Name of the tool.

senderobject

Object that wishes to trigger the tool.

canvaseventEvent

Original Canvas event or None.

dataobject

Extra data to pass to the tool when triggering.

update_keymap(self, name, key, *args) [source]

Set the keymap to associate with the specified tool.

Parameters:
namestr

Name of the Tool.

keysstr or list of str

Keys to associate with the tool.

class matplotlib.backend_managers.ToolManagerMessageEvent(name, sender, message) [source]

Bases: object

Event carrying messages from toolmanager.

Messages usually get displayed to the user by the toolbar.

class matplotlib.backend_managers.ToolTriggerEvent(name, sender, tool, canvasevent=None, data=None) [source]

Bases: matplotlib.backend_managers.ToolEvent

Event to inform that a tool has been triggered.

© 2012–2018 Matplotlib Development Team. All rights reserved.
Licensed under the Matplotlib License Agreement.
https://matplotlib.org/3.3.3/api/backend_managers_api.html