Classe « Figure »

Méthode matplotlib.figure.Figure.figimage

Signature de la méthode figimage

def figimage(self, X, xo=0, yo=0, alpha=None, norm=None, cmap=None, vmin=None, vmax=None, origin=None, resize=False, **kwargs) 

Description

figimage.__doc__

        Add a non-resampled image to the figure.

        The image is attached to the lower or upper left corner depending on
        *origin*.

        Parameters
        ----------
        X
            The image data. This is an array of one of the following shapes:

            - MxN: luminance (grayscale) values
            - MxNx3: RGB values
            - MxNx4: RGBA values

        xo, yo : int
            The *x*/*y* image offset in pixels.

        alpha : None or float
            The alpha blending value.

        norm : `matplotlib.colors.Normalize`
            A `.Normalize` instance to map the luminance to the
            interval [0, 1].

        cmap : str or `matplotlib.colors.Colormap`, default: :rc:`image.cmap`
            The colormap to use.

        vmin, vmax : float
            If *norm* is not given, these values set the data limits for the
            colormap.

        origin : {'upper', 'lower'}, default: :rc:`image.origin`
            Indicates where the [0, 0] index of the array is in the upper left
            or lower left corner of the axes.

        resize : bool
            If *True*, resize the figure to match the given image size.

        Returns
        -------
        `matplotlib.image.FigureImage`

        Other Parameters
        ----------------
        **kwargs
            Additional kwargs are `.Artist` kwargs passed on to `.FigureImage`.

        Notes
        -----
        figimage complements the Axes image (`~matplotlib.axes.Axes.imshow`)
        which will be resampled to fit the current Axes.  If you want
        a resampled image to fill the entire figure, you can define an
        `~matplotlib.axes.Axes` with extent [0, 0, 1, 1].

        Examples
        --------
        ::

            f = plt.figure()
            nx = int(f.get_figwidth() * f.dpi)
            ny = int(f.get_figheight() * f.dpi)
            data = np.random.random((ny, nx))
            f.figimage(data)
            plt.show()