Python pyplot.waitforbuttonpress方法代碼示例

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def explore_random_examples(self, dataset_split):
        """
        Visualize random examples for dataset exploration purposes
        
        Parameters
        ----------
        dataset_split: str
            Dataset split, can be either 'train' or 'test'

        Returns
        -------
        None
        """
        if self.initialized:
            subplots = plt.subplots(nrows=1, ncols=2)
            for i in np.random.permutation(SmallNORBDataset.n_examples):
                self.data[dataset_split][i].show(subplots)
                plt.waitforbuttonpress()
                plt.cla() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def drawing_loop(self, drawing_pipe):
        # start the matplotlib plotting
        self.init_ui()

        while self.running.is_set():
            exec_time = time()
            # get any data from the polling loop
            updts = None
            while drawing_pipe.poll():
                data_from_plant = drawing_pipe.recv()
                if data_from_plant is None:
                    self.running.clear()
                    break

                # get the visuzlization updates from the latest state
                state, t = data_from_plant
                updts = self.update(state, t)
                self.update_canvas(updts)

            # sleep to guarantee the desired frame rate
            exec_time = time() - exec_time
            plt.waitforbuttonpress(max(self.dt-exec_time, 1e-9))
        self.close() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
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) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
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() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
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() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def imshow(inps, title=None):
    """Imshow for Tensor."""
    subwindows = len(inps)
    for idx, (inp, name) in enumerate(zip(inps, title)):
        inp = inp.numpy().transpose((1, 2, 0))
        ax = plt.subplot(1, subwindows, idx+1)
        ax.axis('off')
        plt.imshow(inp)
        ax.set_title(name)
        # plt.pause(0.001)
    plt.show()
    # plt.waitforbuttonpress(-1) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def update_canvas(self, updts):
        if updts is not None:
            # update the drawing from the plant state
            self.fig.canvas.restore_region(self.bg)
            for artist in updts:
                self.ax.draw_artist(artist)
            self.fig.canvas.update()
            # sleep to guarantee the desired frame rate
            exec_time = time() - self.exec_time
            plt.waitforbuttonpress(max(self.dt-exec_time, 1e-9))
        self.exec_time = time() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
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() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def show_data_info(self):
        print("訓練樣本數：%s" %  str(self.sample_amount))
        print("訓練集輸入值行列數：%s" %  str(self.train_X.shape))
        print("訓練集輸出值行列數：%s" % str(self.train_Y.shape))
        print("分類種類數：%s" % str(self.classification.shape))

        self.sample_amount

        plt.imshow(self.train_X[0])  # 非貓示例
        # plt.waitforbuttonpress()
        plt.imshow(self.train_X[27])  # 貓示例
        # plt.waitforbuttonpress()

        return self 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def visualize(self, image, state, segmentation=None):
        self.ax.cla()
        self.ax.imshow(image)
        if segmentation is not None:
            self.ax.imshow(segmentation, alpha=0.5)

        if isinstance(state, (OrderedDict, dict)):
            boxes = [v for k, v in state.items()]
        else:
            boxes = (state,)

        for i, box in enumerate(boxes, start=1):
            col = _tracker_disp_colors[i]
            col = [float(c) / 255.0 for c in col]
            rect = patches.Rectangle((box[0], box[1]), box[2], box[3], linewidth=1, edgecolor=col, facecolor='none')
            self.ax.add_patch(rect)

        if getattr(self, 'gt_state', None) is not None:
            gt_state = self.gt_state
            rect = patches.Rectangle((gt_state[0], gt_state[1]), gt_state[2], gt_state[3], linewidth=1, edgecolor='g', facecolor='none')
            self.ax.add_patch(rect)
        self.ax.set_axis_off()
        self.ax.axis('equal')
        draw_figure(self.fig)

        if self.pause_mode:
            keypress = False
            while not keypress:
                keypress = plt.waitforbuttonpress() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def hold_plot():
        print('Press any key to exit...')
        plt.ioff()
        plt.waitforbuttonpress()
        plt.close() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def waitforbuttonpress():
    plt.waitforbuttonpress(timeout=1) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def plot_single(img, title=''):
    plt.figure()
    plt.title(title)
    plt.imshow(img, cmap='gray')
    plt.waitforbuttonpress() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
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() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import waitforbuttonpress [as 別名]
def draw_rec_prec(rec, prec, mrec, mprec, class_name, ap):
    """
     Draw plot
    """
    plt.plot(rec, prec, '-o')
    # add a new penultimate point to the list (mrec[-2], 0.0)
    # since the last line segment (and respective area) do not affect the AP value
    area_under_curve_x = mrec[:-1] + [mrec[-2]] + [mrec[-1]]
    area_under_curve_y = mprec[:-1] + [0.0] + [mprec[-1]]
    plt.fill_between(area_under_curve_x, 0, area_under_curve_y, alpha=0.2, edgecolor='r')
    # set window title
    fig = plt.gcf() # gcf - get current figure
    fig.canvas.set_window_title('AP ' + class_name)
    # set plot title
    plt.title('class: ' + class_name + ' AP = {}%'.format(ap*100))
    #plt.suptitle('This is a somewhat long figure title', fontsize=16)
    # set axis titles
    plt.xlabel('Recall')
    plt.ylabel('Precision')
    # optional - set axes
    axes = plt.gca() # gca - get current axes
    axes.set_xlim([0.0,1.0])
    axes.set_ylim([0.0,1.05]) # .05 to give some extra space
    # Alternative option -> wait for button to be pressed
    #while not plt.waitforbuttonpress(): pass # wait for key display
    # Alternative option -> normal display
    #plt.show()
    # save the plot
    rec_prec_plot_path = os.path.join('result','classes')
    os.makedirs(rec_prec_plot_path, exist_ok=True)
    fig.savefig(os.path.join(rec_prec_plot_path, class_name + ".png"))
    plt.cla() # clear axes for next plot