Python matplotlib.pyplot 模块，waitforbuttonpress() 实例源码

def demo_cmd(description="load and align images in a directory",
             path=None, frame=5, grid=(3, 10), tform=AffineTransform):
    """load and align images in a directory, animating the process

    Parameters
    ----------
    see rasl_arg_parser

    """
    parser = rasl_arg_parser(description=description, path=path, frame=frame,
                             grid=grid, tform=tform)
    args = parser.parse_args()
    Image = load_images(args.path)
    if len(Image) < np.prod(args.grid):
        raise ValueError("Only {} images, specify a smaller --grid than {}"\
                         .format(len(Image), args.grid))
    T = [args.tform().inset(image.shape, args.frame)
         for image in Image]
    _ = rasl(Image, T, stop_delta=args.stop, show=args.grid)
    print("click the image to exit")
    plt.waitforbuttonpress()

def plot_single(img, title=''):
    plt.figure()
    plt.title(title)
    plt.imshow(img, cmap='gray')
    plt.waitforbuttonpress()

def plot_multiple(imgs, main_title='', titles=''):
    num_img = len(imgs)
    rows = (num_img + 1) / 2
    plt.figure()
    plt.title(main_title)
    f, axarr = plt.subplots(rows, 2)
    for i, (img, title) in enumerate(zip(imgs, titles)):
        axarr[i/2, i%2].imshow(img.astype(np.uint8), cmap='gray')
        axarr[i/2, i%2].set_title(title)
    plt.waitforbuttonpress()

def hold_plot():
        print('Press any key to exit...')
        plt.ioff()
        plt.waitforbuttonpress()
        plt.close()

def __call__(self, data):
        """
        View the images in data

        :param tuple data: Data with images at imgcols.
        :return: unchanged input data
        :rtype: tuple
        """
        for imgcol, ax in zip(self.imgcols, self.axes):
            ax.clear()
            img = np.squeeze(data[imgcol])  # remove single-dim axis, e.g. MxNx1
            ax.imshow(img, **self.imargs)
            ax.figure.canvas.draw()
        plt.waitforbuttonpress(timeout=self.pause)  # or plt.pause(self.pause)
        return data

def __call__(self, data):
        """
        View the image and its annotation

        :param tuple data: Data with image at imgcol and annotation at annocol.
        :return: unchanged input data
        :rtype: tuple
        """
        img = np.squeeze(data[self.imgcol])
        ax = self.axes
        ax.clear()
        ax.imshow(img, interpolation=self.interpolation)
        labelcol = 0.7
        for acol in self.annocols:
            annos = data[acol]
            if isinstance(annos, (list, tuple)):
                for anno in iu.annotation2pltpatch(annos, **self._shapeprops()):
                    ax.add_patch(anno)
            else:
                fs = ax.get_window_extent().height / 22
                p = img.shape[0] / 6
                x, y = p / 2, p * labelcol
                labelcol += 1
                ax.text(x, y, str(annos),
                        color=self._textprop('edgecolor'),
                        backgroundcolor=self._textprop('backgroundcolor'),
                        size=fs, family='monospace')
        ax.figure.canvas.draw()
        plt.waitforbuttonpress(timeout=self.pause)  # or plt.pause(self.pause)
        return data

def visualize(dom, states_xy, pred_traj):
    fig, ax = plt.subplots()
    implot = plt.imshow(dom, cmap="Greys_r")
    ax.plot(states_xy[:,0], states_xy[:,1], c='b', label='Optimal Path')
    ax.plot(pred_traj[:,0], pred_traj[:,1], '-X', c='r', label='Predicted Path')
    ax.plot(states_xy[0,0], states_xy[0,1], '-o', label='Start')
    ax.plot(states_xy[-1,0], states_xy[-1,1], '-s', label='Goal')
    legend = ax.legend(loc='upper right', shadow=False)
    for label in legend.get_texts():
        label.set_fontsize('x-small') # the legend text size
    for label in legend.get_lines():
        label.set_linewidth(0.5)  # the legend line width
    plt.draw()
    plt.waitforbuttonpress(0)
    plt.close(fig)

def sitk_show(nda, title=None, margin=0.0, dpi=40):
    figsize = (1 + margin) * nda.shape[0] / dpi, (1 + margin) * nda.shape[1] / dpi

    extent = (0, nda.shape[1], nda.shape[0], 0)
    fig = plt.figure(figsize=figsize, dpi=dpi)
    ax = fig.add_axes([margin, margin, 1 - 2*margin, 1 - 2*margin])

    plt.set_cmap("gray")
    for k in range(0,nda.shape[2]):
        print "printing slice "+str(k)
        ax.imshow(np.squeeze(nda[:,:,k]),extent=extent,interpolation=None)
        plt.draw()
        plt.pause(0.1)
        #plt.waitforbuttonpress()