Python pyplot.get_current_fig_manager方法代码示例

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def test_root_locus_zoom(self):
        """Check the zooming functionality of the Root locus plot"""
        system = TransferFunction([1000], [1, 25, 100, 0])
        root_locus(system)
        fig = plt.gcf()
        ax_rlocus = fig.axes[0]

        event = type('test', (object,), {'xdata': 14.7607954359, 'ydata': -35.6171379864, 'inaxes': ax_rlocus.axes})()
        ax_rlocus.set_xlim((-10.813628105112421, 14.760795435937652))
        ax_rlocus.set_ylim((-35.61713798641108, 33.879716621220311))
        plt.get_current_fig_manager().toolbar.mode = 'zoom rect'
        _RLClickDispatcher(event, system, fig, ax_rlocus, '-')

        zoom_x = ax_rlocus.lines[-2].get_data()[0][0:5]
        zoom_y = ax_rlocus.lines[-2].get_data()[1][0:5]
        zoom_y = [abs(y) for y in zoom_y]

        zoom_x_valid = [-5. ,- 4.61281263, - 4.16689986, - 4.04122642, - 3.90736502]
        zoom_y_valid = [0. ,0., 0., 0., 0.]

        assert_array_almost_equal(zoom_x,zoom_x_valid)
        assert_array_almost_equal(zoom_y,zoom_y_valid) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def _RLClickDispatcher(event, sys, fig, ax_rlocus, plotstr, sisotool=False,
                       bode_plot_params=None, tvect=None):
    """Rootlocus plot click dispatcher"""

    # Zoom is handled by specialized callback above, only do gain plot
    if event.inaxes == ax_rlocus.axes and \
       plt.get_current_fig_manager().toolbar.mode not in \
       {'zoom rect', 'pan/zoom'}:

        # if a point is clicked on the rootlocus plot visually emphasize it
        K = _RLFeedbackClicksPoint(event, sys, fig, ax_rlocus, sisotool)
        if sisotool and K is not None:
            _SisotoolUpdate(sys, fig, K, bode_plot_params, tvect)

    # Update the canvas
    fig.canvas.draw() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def main(args):
    """
    Main function for the script
    :param args: parsed command line arguments
    :return: None
    """

    img_file = os.path.join(args.image_path)
    if args.npz_file:
        img = np.load(img_file)
        img = img.squeeze(0).transpose(1, 2, 0)
    else:
        img = np.array(Image.open(img_file))

    # show the image on screen:
    plt.figure().suptitle(args.image_path.split("/")[-1])
    plt.imshow(img)
    mng = plt.get_current_fig_manager()
    mng.resize(*mng.window.maxsize())
    plt.show() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def main(args):
    """
    Main function for the script
    :param args: parsed command line arguments
    :return: None
    """
    # go over the image files in the directory
    for img_file_name in os.listdir(args.images_path):

        img_file = os.path.join(args.images_path, img_file_name)
        if args.npz_files:
            img = np.load(img_file)
            img = img.squeeze(0).transpose(1, 2, 0)
        else:
            img = np.array(Image.open(img_file))

        # show the image on screen:
        plt.figure().suptitle(img_file_name)
        plt.imshow(img)
        mng = plt.get_current_fig_manager()
        mng.resize(*mng.window.maxsize())
        plt.show() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def visualize_stn(data, title):
    input_tensor = data.cpu()
    input_tensor = torch.squeeze(input_tensor)
    input_tensor = input_tensor.detach().numpy()
    N = len(input_tensor)

    fig=plt.figure(num = 2)

    columns = N
    rows = 1
    for i in range(1, columns*rows +1):
        img = input_tensor[i-1]
        fig.add_subplot(rows, columns, i)
        plt.imshow(img, cmap='gray', interpolation='none')

    figManager = plt.get_current_fig_manager()
    figManager.resize(*figManager.window.maxsize())
    # figManager.window.state('zoomed')
    plt.show(block=False)
    # time.sleep(4)
    # plt.close() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def show(self, plot_config, block=True, maximize=False, window_title=None):
        """Show the data contained in this visualizer using the specifics in this function call.

        Args:
            plot_config (mdt.visualization.maps.base.MapPlotConfig): the plot configuration
            block (boolean): If we want to block after calling the plots or not. Set this to False if you
                do not want the routine to block after drawing. In doing so you manually need to block.
            maximize (boolean): if we want to display the window maximized or not
            window_title (str): the title of the window. If None, the default title is used
        """
        Renderer(self._data_info, self._figure, plot_config).render()

        if maximize:
            mng = plt.get_current_fig_manager()
            mng.window.showMaximized()

        if window_title:
            mng = plt.get_current_fig_manager()
            mng.canvas.set_window_title(window_title)

        if block:
            plt.show(True) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def show_pca(self, dest_image, updater):
        colors = ['navy', 'turquoise', 'darkorange']
        if getattr(updater, 'pca', None) is None:
            return dest_image
        pca_discriminator = updater.pca.reshape(3, -1, updater.n_components_pca)

        plt.figure()
        for i, color, in enumerate(colors):
            plt.scatter(pca_discriminator[i, :, 0], pca_discriminator[i, :, 1], color=color, lw=2)
        plt.legend(['fake', 'real', 'anchor'])

        canvas = plt.get_current_fig_manager().canvas
        canvas.draw()
        image = Image.frombytes('RGB', canvas.get_width_height(), canvas.tostring_rgb())
        image = image.resize((self.image_size.width, self.image_size.height), Image.LANCZOS)
        dest_image.paste(image, (self.image_size.width, self.image_size.height))
        plt.close()
        return dest_image 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def show(pts, cells, geo, title=None, full_screen=True):
    import matplotlib.pyplot as plt

    eps = 1.0e-10
    is_inside = geo.dist(pts.T) < eps
    plt.plot(pts[is_inside, 0], pts[is_inside, 1], ".")
    plt.plot(pts[~is_inside, 0], pts[~is_inside, 1], ".", color="r")
    plt.triplot(pts[:, 0], pts[:, 1], cells)
    plt.axis("square")

    if full_screen:
        figManager = plt.get_current_fig_manager()
        try:
            figManager.window.showMaximized()
        except AttributeError:
            # Some backends have no window (e.g., Agg)
            pass

    if title is not None:
        plt.title(title)

    try:
        geo.show(level_set=False)
    except AttributeError:
        pass 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def export_all_contours(contours, img_path):
    counter_img = 0
    counter_label = 0
    batchsz = 100
    print("Processing {:d} images and labels...".format(len(contours)))
    for i, ctr in enumerate(contours):
        img, label = load_contour(ctr, img_path)
        images.append(img)
        labels.append(label)
        #print ctr
        #if "SC-HYP-12" in ctr.__str__():
            #pass
        """
        if i>-1:
            plt.figure()
            mngr = plt.get_current_fig_manager()
            # to put it into the upper left corner for example:
            mngr.window.setGeometry(50, 100, 640, 545)
            plt.suptitle(ctr.__str__() + "  #%d" % i)
            plt.imshow(img * (1-label) + (np.max(img)-img)*(label) )
            #plt.imshow(label)
            plt.show()
            """ 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def animate_slice(slicedata1, slicedata2, index1, index2):
    fig, (ax1, ax2) = plt.subplots(1, 2)
    mngr = plt.get_current_fig_manager()
    # to put it into the upper left corner for example:
    mngr.window.setGeometry(50, 100, 600, 300)

    im1 = ax1.imshow(slicedata1[0], cmap='gist_gray_r')
    im2 = ax2.imshow(slicedata2[0], cmap='gist_gray_r')

    fig.suptitle('patient %d vs %d' % (index1, index2))

    def init():
        im1.set_data(slicedata1[0])
        im2.set_data(slicedata2[0])

    def animate(i):
        im1.set_data(slicedata1[i])
        im2.set_data(slicedata2[i])
        return im1

    anim = animation.FuncAnimation(fig, animate, init_func=init, frames=len(slicedata1), interval=50)

    plt.show() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def prepare(self):
    if self.backend:
      plt.switch_backend(self.backend)
    self.f = plt.figure(figsize=self.window_size)
    self.ax = self.f.add_subplot(111)
    self.lines = []
    for _ in self.labels:
      if self.interp:
        self.lines.append(self.ax.plot([], [])[0])
      else:
        self.lines.append(self.ax.step([], [])[0])
    # Keep only 1/factor points on each line
    self.factor = [1 for i in self.labels]
    # Count to drop exactly 1/factor points, no more and no less
    self.counter = [0 for i in self.labels]
    legend = [y for x, y in self.labels]
    plt.legend(legend, bbox_to_anchor=(-0.03, 1.02, 1.06, .102), loc=3,
               ncol=len(legend), mode="expand", borderaxespad=1)
    plt.xlabel(self.labels[0][0])
    plt.ylabel(self.labels[0][1])
    plt.grid()
    self.axclear = plt.axes([.8,.02,.15,.05])
    self.bclear = Button(self.axclear,'Clear')
    self.bclear.on_clicked(self.clear)

    if self.window_pos:
      mng = plt.get_current_fig_manager()
      mng.window.wm_geometry("+%s+%s" % self.window_pos)
    plt.draw()
    plt.pause(.001) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def visualize(data, fig_num, title):
    input_tensor = data.cpu()
    input_tensor = torch.squeeze(input_tensor)
    in_grid = input_tensor.detach().numpy()

    fig=plt.figure(num = fig_num)
    plt.imshow(in_grid, cmap='gray', interpolation='none')
    plt.title(title)
    figManager = plt.get_current_fig_manager()
    figManager.resize(*figManager.window.maxsize())
    plt.show(block=False)
    # time.sleep(4)
    # plt.close() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def forSecond(frame_number, output_arrays, count_arrays, average_count, returned_frame):

    plt.clf()

    this_colors = []
    labels = []
    sizes = []

    counter = 0

    for eachItem in average_count:
        counter += 1
        labels.append(eachItem + " = " + str(average_count[eachItem]))
        sizes.append(average_count[eachItem])
        this_colors.append(color_index[eachItem])

    global resized

    if (resized == False):
        manager = plt.get_current_fig_manager()
        manager.resize(width=1000, height=500)
        resized = True

    plt.subplot(1, 2, 1)
    plt.title("Second : " + str(frame_number))
    plt.axis("off")
    plt.imshow(returned_frame, interpolation="none")

    plt.subplot(1, 2, 2)
    plt.title("Analysis: " + str(frame_number))
    plt.pie(sizes, labels=labels, colors=this_colors, shadow=True, startangle=140, autopct="%1.1f%%")

    plt.pause(0.01) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def forFrame(frame_number, output_array, output_count, returned_frame):

    plt.clf()

    this_colors = []
    labels = []
    sizes = []

    counter = 0

    for eachItem in output_count:
        counter += 1
        labels.append(eachItem + " = " + str(output_count[eachItem]))
        sizes.append(output_count[eachItem])
        this_colors.append(color_index[eachItem])

    global resized

    if (resized == False):
        manager = plt.get_current_fig_manager()
        manager.resize(width=1000, height=500)
        resized = True

    plt.subplot(1, 2, 1)
    plt.title("Frame : " + str(frame_number))
    plt.axis("off")
    plt.imshow(returned_frame, interpolation="none")

    plt.subplot(1, 2, 2)
    plt.title("Analysis: " + str(frame_number))
    plt.pie(sizes, labels=labels, colors=this_colors, shadow=True, startangle=140, autopct="%1.1f%%")

    plt.pause(0.01) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import get_current_fig_manager [as 别名]
def showMaximize():
    mng = plt.get_current_fig_manager()
    mng.window.state('zoomed')
    plt.show()