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# Demo BboxImage

    import matplotlib.pyplot as plt
    import numpy as np
    from matplotlib.image import BboxImage
    from matplotlib.transforms import Bbox, TransformedBbox

    if __name__ == "__main__":

        fig = plt.figure(1)
        ax = plt.subplot(121)

        txt = ax.text(0.5, 0.5, "test", size=30, ha="center", color="w")
        kwargs = dict()

        bbox_image = BboxImage(txt.get_window_extent,
                               norm=None,
                               origin=None,
                               clip_on=False,
                               **kwargs
                               )
        a = np.arange(256).reshape(1, 256)/256.
        bbox_image.set_data(a)
        ax.add_artist(bbox_image)

        ax = plt.subplot(122)
        a = np.linspace(0, 1, 256).reshape(1, -1)
        a = np.vstack((a, a))

        maps = sorted(
            m for m in plt.cm.cmap_d
            if not m.endswith("_r") and  # Skip reversed colormaps.
            not m.startswith(('spectral', 'Vega'))  # Skip deprecated colormaps.
        )

        #fig.subplots_adjust(top=0.99, bottom=0.01, left=0.2, right=0.99)

        ncol = 2
        nrow = len(maps)//ncol + 1

        xpad_fraction = 0.3
        dx = 1./(ncol + xpad_fraction*(ncol - 1))

        ypad_fraction = 0.3
        dy = 1./(nrow + ypad_fraction*(nrow - 1))

        for i, m in enumerate(maps):
            ix, iy = divmod(i, nrow)
            #plt.figimage(a, 10, i*10, cmap=plt.get_cmap(m), origin='lower')
            bbox0 = Bbox.from_bounds(ix*dx*(1 + xpad_fraction),
                                     1. - iy*dy*(1 + ypad_fraction) - dy,
                                     dx, dy)
            bbox = TransformedBbox(bbox0, ax.transAxes)

            bbox_image = BboxImage(bbox,
                                   cmap=plt.get_cmap(m),
                                   norm=None,
                                   origin=None,
                                   **kwargs
                                   )

            bbox_image.set_data(a)
            ax.add_artist(bbox_image)

        plt.draw()
        plt.show()

Total running time of the script: ( 0 minutes 0.309 seconds)

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