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Module « matplotlib.pyplot »

Fonction figure - module matplotlib.pyplot

Signature de la fonction figure

def figure(num: 'int | str | Figure | SubFigure | None' = None, figsize: 'tuple[float, float] | None' = None, dpi: 'float | None' = None, *, facecolor: 'ColorType | None' = None, edgecolor: 'ColorType | None' = None, frameon: 'bool' = True, FigureClass: 'type[Figure]' = <class 'matplotlib.figure.Figure'>, clear: 'bool' = False, **kwargs) -> 'Figure' 

Description

help(matplotlib.pyplot.figure)

Create a new figure, or activate an existing figure.

Parameters
----------
num : int or str or `.Figure` or `.SubFigure`, optional
    A unique identifier for the figure.

    If a figure with that identifier already exists, this figure is made
    active and returned. An integer refers to the ``Figure.number``
    attribute, a string refers to the figure label.

    If there is no figure with the identifier or *num* is not given, a new
    figure is created, made active and returned.  If *num* is an int, it
    will be used for the ``Figure.number`` attribute, otherwise, an
    auto-generated integer value is used (starting at 1 and incremented
    for each new figure). If *num* is a string, the figure label and the
    window title is set to this value.  If num is a ``SubFigure``, its
    parent ``Figure`` is activated.

figsize : (float, float), default: :rc:`figure.figsize`
    Width, height in inches.

dpi : float, default: :rc:`figure.dpi`
    The resolution of the figure in dots-per-inch.

facecolor : :mpltype:`color`, default: :rc:`figure.facecolor`
    The background color.

edgecolor : :mpltype:`color`, default: :rc:`figure.edgecolor`
    The border color.

frameon : bool, default: True
    If False, suppress drawing the figure frame.

FigureClass : subclass of `~matplotlib.figure.Figure`
    If set, an instance of this subclass will be created, rather than a
    plain `.Figure`.

clear : bool, default: False
    If True and the figure already exists, then it is cleared.

layout : {'constrained', 'compressed', 'tight', 'none', `.LayoutEngine`, None}, default: None
    The layout mechanism for positioning of plot elements to avoid
    overlapping Axes decorations (labels, ticks, etc). Note that layout
    managers can measurably slow down figure display.

    - 'constrained': The constrained layout solver adjusts Axes sizes
      to avoid overlapping Axes decorations.  Can handle complex plot
      layouts and colorbars, and is thus recommended.

      See :ref:`constrainedlayout_guide`
      for examples.

    - 'compressed': uses the same algorithm as 'constrained', but
      removes extra space between fixed-aspect-ratio Axes.  Best for
      simple grids of Axes.

    - 'tight': Use the tight layout mechanism. This is a relatively
      simple algorithm that adjusts the subplot parameters so that
      decorations do not overlap. See `.Figure.set_tight_layout` for
      further details.

    - 'none': Do not use a layout engine.

    - A `.LayoutEngine` instance. Builtin layout classes are
      `.ConstrainedLayoutEngine` and `.TightLayoutEngine`, more easily
      accessible by 'constrained' and 'tight'.  Passing an instance
      allows third parties to provide their own layout engine.

    If not given, fall back to using the parameters *tight_layout* and
    *constrained_layout*, including their config defaults
    :rc:`figure.autolayout` and :rc:`figure.constrained_layout.use`.

**kwargs
    Additional keyword arguments are passed to the `.Figure` constructor.

Returns
-------
`~matplotlib.figure.Figure`

Notes
-----
A newly created figure is passed to the `~.FigureCanvasBase.new_manager`
method or the `new_figure_manager` function provided by the current
backend, which install a canvas and a manager on the figure.

Once this is done, :rc:`figure.hooks` are called, one at a time, on the
figure; these hooks allow arbitrary customization of the figure (e.g.,
attaching callbacks) or of associated elements (e.g., modifying the
toolbar).  See :doc:`/gallery/user_interfaces/mplcvd` for an example of
toolbar customization.

If you are creating many figures, make sure you explicitly call
`.pyplot.close` on the figures you are not using, because this will
enable pyplot to properly clean up the memory.

`~matplotlib.rcParams` defines the default values, which can be modified
in the matplotlibrc file.

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