matplotlib.pyplot.figimage

matplotlib.pyplot.figimage(X, xo=0, yo=0, alpha=None, norm=None, cmap=None, vmin=None, vmax=None, origin=None, resize=False, **kwargs) [source]

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, yoint The x/y image offset in pixels. alphaNone or float The alpha blending value. normmatplotlib.colors.Normalize A Normalize instance to map the luminance to the interval [0, 1]. cmapstr or matplotlib.colors.Colormap, default: rcParams["image.cmap"] (default: 'viridis') The colormap to use. vmin, vmaxfloat If norm is not given, these values set the data limits for the colormap. origin{'upper', 'lower'}, default: rcParams["image.origin"] (default: 'upper') Indicates where the [0, 0] index of the array is in the upper left or lower left corner of the axes. resizebool 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 (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 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()

Examples using matplotlib.pyplot.figimage