Python matplotlib.widgets.Button() Examples

def __init__(self, rect, wtype, *args, **kwargs):
        """
        Creates a matplotlib.widgets widget
        :param rect: The rectangle of the position [left, bottom, width, height] in relative figure coordinates
        :param wtype: A type from matplotlib.widgets, eg. Button, Slider, TextBox, RadioButtons
        :param args: Positional arguments passed to the widget
        :param kwargs: Keyword arguments passed to the widget and events used for the widget
                       eg. if wtype is Slider, on_changed=f can be used as keyword argument

        """
        self.ax = plt.axes(rect)
        events = {}
        for k in list(kwargs.keys()):
            if k.startswith('on_'):
                events[k] = kwargs.pop(k)
        self.object = wtype(self.ax, *args, **kwargs)
        for k in events:
            if hasattr(self.object, k):
                getattr(self.object, k)(events[k]) 

def add_navigation(self, user_next_callback=None,
                       user_quit_callback=None):
        """Navigation elements"""

        ax_bt_quit = self.fig.add_axes(cfg.position_quit_button,
                              facecolor=cfg.color_quit_axis, aspect='equal')
        ax_bt_next = self.fig.add_axes(cfg.position_next_button,
                              facecolor=cfg.color_quit_axis, aspect='equal')
        self.bt_quit = Button(ax_bt_quit, 'Quit', hovercolor='red')
        self.bt_next = Button(ax_bt_next, 'Next', hovercolor='xkcd:greenish')
        #
        self.bt_quit.label.set_color(cfg.color_navig_text)
        self.bt_next.label.set_color(cfg.color_navig_text)
        # new impl to take control of blocking behav of plt.show()
        if user_next_callback is not None and user_quit_callback is not None:
            self.bt_next.on_clicked(user_next_callback)
            self.bt_quit.on_clicked(user_quit_callback)
        else:
            # previous impl - gives no control over blocking plt.show()
            self.bt_quit.on_clicked(self.builtin_quit)
            self.bt_next.on_clicked(self.builtin_next) 

def create_button(idx_feature):
    """ function to built button groups for one feature """
    x, y, w, h = get_loc_control(idx_feature)

    plt.text(x+w/2, y+h/2+0.01, feature_name[idx_feature], horizontalalignment='center',
             transform=plt.gcf().transFigure)

    ax_neg = plt.axes((x + w / 8, y, w / 4, h / 2))
    b_neg = widgets.Button(ax_neg, '-', hovercolor='0.1')
    b_neg.on_clicked(lambda event:
                     callback.modify_along_feature(event, idx_feature, step_size=-1 * step_size))

    ax_pos = plt.axes((x + w *5/8, y, w / 4, h / 2))
    b_pos = widgets.Button(ax_pos, '+', hovercolor='0.1')
    b_pos.on_clicked(lambda event:
                     callback.modify_along_feature(event, idx_feature, step_size=+1 * step_size))

    ax_lock = plt.axes((x + w * 3/8, y, w / 4, h / 2))
    b_lock = widgets.CheckButtons(ax_lock, ['L'], [False])
    b_lock.on_clicked(lambda event:
                      callback.set_feature_lock(event, idx_feature))
    return b_neg, b_pos, b_lock 

def toggle(self, ax=None):
        """Creates a play/pause button to start/stop the animation

        Parameters
        ----------
        ax : matplotlib.axes.Axes, optional
            The matplotlib axes to attach the button to.
        """
        if ax is None:
            adjust_plot = {'bottom': .2}
            rect = [.78, .03, .1, .07]

            plt.subplots_adjust(**adjust_plot)
            self.button_ax = plt.axes(rect)
        else:
            self.button_ax = ax

        self.button = Button(self.button_ax, "Pause")
        self.button.label2 = self.button_ax.text(
            0.5, 0.5, 'Play',
            verticalalignment='center',
            horizontalalignment='center',
            transform=self.button_ax.transAxes
        )
        self.button.label2.set_visible(False)

        def pause(event):
            if self._pause:
                self.animation.event_source.start()
                self.button.label.set_visible(True)
                self.button.label2.set_visible(False)
            else:
                self.animation.event_source.stop()
                self.button.label.set_visible(False)
                self.button.label2.set_visible(True)
            self.fig.canvas.draw()
            self._pause ^= True
        self.button.on_clicked(pause) 

def __init__(self,porttype):
		self.porttype = porttype
		self.results = []
	
#def GUIfit(porttype,f_data,z_data_raw):
#	'''
#	GUI based fitting process enabeling cutting the data and manually setting the delay
#	It employs the Matplotlib widgets
#	return f1, f2 and delay, which should be employed for the real fitting
#	'''
#	if porttype=='direct':
#		p = reflection_port(f_data=f_data,z_data_raw=z_data_raw)
#	elif porttype =='notch':
#		p = notch_port(f_data=f_data,z_data_raw=z_data_raw)
#	else:
#		warnings.warn('Not supported!')
#		return None
#	import matplotlib.pyplot as plt
#	from matplotlib.widgets import Slider, Button, RadioButtons
#	#plt.style.use('ggplot')
#	fig, axes = plt.subplots(nrows=2,ncols=2)
#	
#	return f1,f2,delay 

def make_buttons(self):
        ax_add_btn = plt.axes([0.7, 0.02, 0.1, 0.04])
        ax_finish_btn = plt.axes([0.81, 0.02, 0.1, 0.04])
        btn_finish = Button(ax_finish_btn, 'Finish')
        btn_finish.on_clicked(self.finish)
        btn_add = Button(ax_add_btn, 'New ROI')
        btn_add.on_clicked(self.add)
        plt.show(block=True) 

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) 

def _initialize_buttons(self):
        self._buttons = {}
        for key, action in self._actions.items():
            if action.axis_pos is None:
                continue
            
            button_name = '%s\n(%s)' % (action.name, action.kb)
            if ROS_ENABLED and action.pb:
                ps3_buttons = [config['inverted_ps3_button'][i] for i in action.pb]
                button_name += '\n(%s)' % ',\n'.join(ps3_buttons)

            self._buttons[key] = Button(self._axarr[action.axis_pos], button_name)
            self._buttons[key].on_clicked(action.func) 

def __init__(self, setup):
        """
        Creates the GUI

        :param setup: A spotpy setup
        """
        self.fig = plt.figure(type(setup).__name__)
        self.ax = plt.axes([0.05, 0.1, 0.65, 0.85])
        self.button_run = Widget([0.75, 0.01, 0.1, 0.03], Button, 'Simulate', on_clicked=self.run)
        self.button_clear = Widget([0.87, 0.01, 0.1, 0.03], Button, 'Clear plot', on_clicked=self.clear)
        self.parameter_values = {}
        self.setup = setup
        self.sliders = self._make_widgets()
        self.lines = []
        self.clear() 

def __run__(self):
        # create the welcome window
        run_type = None
        t = tkinter.Toplevel(self.root)
        t.resizable(False,False)
        frame = ttk.Frame(t, padding="3 3 12 12")
        frame.grid(column=0, row=0, sticky=(tkinter.N, tkinter.W, tkinter.E, tkinter.S))
        frame.columnconfigure(0, weight=1)
        frame.rowconfigure(0, weight=1)
        ttk.Label(frame,text="Welcome to Marmot.").grid(column=1,row=1)
        def setup(require_gold_standard):
            # this will determine the whole run mode from here on in
            self.require_gold_standard = require_gold_standard
            self.subjects = self.__image_select__(require_gold_standard)
            # if r == "a":
            #     self.subjects = self.project.__get_retired_subjects__(1,True)
            #     self.run_mode = "a"
            # else:
            #     # when we want to explore subjects which don't have gold standard
            #     # basically creating some as we go
            #     # False => read in all subjects, not just those with gold standard annotations
            #     # todo - takes a while in read in all subjects. Better way?
            #     self.subjects = self.project.__get_retired_subjects__(1,False)
            #     self.run_mode = "b"
            random.shuffle(self.subjects)

            self.__thumbnail_display__()
            self.__add_buttons__()

            t.destroy()

        ttk.Button(frame, text="Explore results using existing expert annotations", command = lambda : setup(True)).grid(column=1, row=2)
        ttk.Button(frame, text="Explore and create gold standard on the fly", command = lambda : setup(False)).grid(column=1, row=3)

        t.lift(self.root)

        # self.outputButtons()
        self.root.mainloop() 

def __thumbnail_display__(self):
        # destroy any previously existing thumbnails - for when we're flipping through pages
        for thumb_index in range(len(self.thumbnails)-1,-1,-1):
            old_thumb = self.thumbnails.pop(thumb_index)
            old_thumb.destroy()

        for ii,subject_id in enumerate(self.subjects[9*self.page_index:9+9*self.page_index]):
            # do we already have a thumb for this file?
            thumb_path = DIR_THUMBS+str(subject_id)+".jpg"
            if not os.path.exists(thumb_path):
                self.__create_thumb__(subject_id)

            render_image = ImageTk.PhotoImage(file=thumb_path)

            but = ttk.Button(self.root, image=render_image)
            but.grid(column=ii/3+1, row=(1+ii)%3,sticky=tkinter.W)

            # the interaction with the subject will depend on whether we have gold standard data for it or not
            # if not, the user will need to create some
            if self.require_gold_standard:
                assert False
                # but.bind('<Button-1>', lambda event,t=thumb_path: self.(t) if self.run_mode == "a" else self.__create_gold_standard__(t))
            else:
                but.bind('<Button-1>', lambda event,t=thumb_path: self.__create_gold_standard__(t))

            self.thumbnails.append(but)

            # sigh - I hate having to do this
            # MUST keep - otherwise garbage collection in Python will remove it
            self.links.append(render_image)

        # todo - this window is not actually popping up
        # determine which of the subjects we are interested in have actually been processed
        # we may need to do some additional aggregation
        aggregated_subjects = self.project.__get_aggregated_subjects__(-1)

        not_aggregated = [s for s in self.subjects[:self.step_size] if s not in aggregated_subjects]

        # print not_aggregated
        if not_aggregated != []:
            self.project.__aggregate__([-1],self.subjects[:self.step_size]) 

def __add_buttons__(self):
        # for ii,thumbfile in enumerate(thumbfiles[:3]):

        ttk.Button(self.root, text="<--", command=self.__decrement__).grid(column=2, row=4)
        ttk.Button(self.root, text="-->", command=self.__increment__).grid(column=2, row=5)
        # ttk.Button(self.root, text="Threshold Plot", command=self.__calculate__).grid(column=1, row=5)
        # ttk.Button(self.root, text="Re-aggregate", command=self.__reaggregate__).grid(column=1, row=6)
        ttk.Button(self.root, text="ROC estimate", command=self.__roc_estimate__).grid(column=1, row=6) 

def show(self):
        self.fig = plt.figure()
        ax = self.fig.add_subplot(111)
        ax.axis("off")
        lo = np.nanmin(self.xy, axis=0)
        hi = np.nanmax(self.xy, axis=0)
        center = (hi + lo) / 2
        w, h = hi - lo
        ampl = 1.3
        w *= ampl
        h *= ampl
        ax.set_xlim(center[0] - w / 2, center[0] + w / 2)
        ax.set_ylim(center[1] - h / 2, center[1] + h / 2)
        ax.imshow(self.image)
        ax.scatter(*self.xy.T, s=self.cfg["dotsize"] ** 2)
        ax.add_collection(self.lines)
        ax.invert_yaxis()

        self.lasso = LassoSelector(ax, onselect=self.on_select)
        ax_clear = self.fig.add_axes([0.85, 0.55, 0.1, 0.1])
        ax_export = self.fig.add_axes([0.85, 0.45, 0.1, 0.1])
        self.clear_button = Button(ax_clear, "Clear")
        self.clear_button.on_clicked(self.clear)
        self.export_button = Button(ax_export, "Export")
        self.export_button.on_clicked(self.export)
        self.fig.canvas.mpl_connect("pick_event", self.on_pick)
        plt.show() 

def draw_empty_plot(self, ax):
        h, = ax.plot([], [], '.', markersize=50)
        self.button = Button(plt.axes([0.7, 0.01, 0.1, 0.05]), 'Zero')
        self.button.on_clicked(self.clicked)
        return h, 

def draw_empty_plot(self, ax):
        ax_pause = plt.axes([0.81, 0.005, 0.1, 0.075])
        self.pause_button = Button(ax_pause, 'Pause')
        self.pause_button.on_clicked(self.pause)
        return [] 

def getManualRegistrationError(visual, heightmap, image_scale, pc):
    upper_left_enu = pc.ulENU()
    lower_right_enu = pc.lrENU()
    upper_left_latlon = pc.enuToLatLon(*upper_left_enu)
    lower_right_latlon = pc.enuToLatLon(*lower_right_enu)
    # Order is South, West, North, East
    result = OSMTGC.getOSMData(lower_right_latlon[0], upper_left_latlon[1], upper_left_latlon[0], lower_right_latlon[1])

    # TODO Scale, Sharpen, and Increase Local Constrast for these images to get potentially easier results?
    image_dict = {}
    image_dict["Visible"] = visual
    image_dict["Visible Golf"] = None
    image_dict["Heightmap"] = heightmap
    image_dict["Heightmap Golf"] = None

    fig, ax = plt.subplots()
    plt.title('Move Slider and Press Apply.  Close Window When Happy With Alignment')

    axcolor = 'green'
    plt.subplots_adjust(left=0.3, bottom=0.25)

    axx = plt.axes([0.25, 0.15, 0.65, 0.03], facecolor=axcolor)
    axy = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
    sx = Slider(axx, 'West/East', -10.0, 10.0, valinit=0.0)
    sy = Slider(axy, 'South/North', -10.0, 10.0, valinit=0.0)

    applyax = plt.axes([0.8, 0.025, 0.1, 0.04])
    button = Button(applyax, 'Apply', color=axcolor, hovercolor='0.975')

    rax = plt.axes([0.05, 0.7, 0.15, 0.15], facecolor=axcolor)
    radio = RadioButtons(rax, image_dict.keys())
    update_image = partial(drawNewImage, ax, image_dict)
    radio.on_clicked(update_image)

    new_offset = partial(drawNewLocation, ax, image_dict, result, image_scale, radio, sx, sy, 1)
    button.on_clicked(new_offset)

    drawNewLocation(ax, image_dict, result, image_scale, radio, None, None, None, None)

    plt.show()

    return (sx.val, sy.val) 

def __init__(self, load_path, save_path=None):
        # init manipulator
        self.savepath = save_path
        self.filepaths = self._load_paths(load_path)  # load all scans filepaths in path
        self.fileindex = 0
        self.manipulator = scan_manipulator()
        self.manipulator.load_target_scan(self.filepaths[self.fileindex])
        self.hist_state = True
        self.inject_coords = []
        self.remove_coords = []

        # init plot
        self.eq = histEq(self.manipulator.scan)
        self.slices, self.cols, self.rows = self.manipulator.scan.shape
        self.ind = self.slices // 2
        self.pause_start = 0
        self.fig, self.ax = plt.subplots(1, 1, dpi=100)
        self.fig.suptitle('CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning\nTool by Yisroel Mirsky', fontsize=14, fontweight='bold')
        plt.subplots_adjust(bottom=0.2)
        self.ani_direction = 'down'
        self.animation = None
        self.animation_state = True
        self.plot()
        self.ax.set_title(os.path.split(self.filepaths[self.fileindex])[-1]) #filename


        # register click/scroll events
        self.action_state = 'inject' #default state
        self.fig.canvas.mpl_connect('button_press_event', self.onclick)
        self.fig.canvas.mpl_connect('scroll_event', self.onscroll)

        # register buttons
        axanim = plt.axes([0.1, 0.21, 0.2, 0.075])
        self.banim = Button(axanim, 'Toggle Animation')
        self.banim.on_clicked(self.toggle_animation)

        axinj = plt.axes([0.1, 0.05, 0.1, 0.075])
        axrem = plt.axes([0.21, 0.05, 0.1, 0.075])
        self.binj = Button(axinj, 'Inject')
        self.binj.on_clicked(self.inj_on)
        self.brem = Button(axrem, 'Remove')
        self.brem.on_clicked(self.rem_on)

        axhist = plt.axes([0.35, 0.05, 0.2, 0.075])
        self.bhist = Button(axhist, 'Toggle HistEQ')
        self.bhist.on_clicked(self.hist)

        axprev = plt.axes([0.59, 0.05, 0.1, 0.075])
        axsave = plt.axes([0.7, 0.05, 0.1, 0.075])
        axnext = plt.axes([0.81, 0.05, 0.1, 0.075])
        self.bnext = Button(axnext, 'Next')
        self.bnext.on_clicked(self.next)
        self.bprev = Button(axprev, 'Previous')
        self.bprev.on_clicked(self.prev)
        self.bsave = Button(axsave, 'Save')
        self.bsave.on_clicked(self.save)
        self.maximize_window()
        self.update()
        plt.show() 

def draw_bbox(video):
    import matplotlib.pyplot as plt
    from matplotlib.widgets import RectangleSelector, Button

    clip = cv2.VideoCapture(video)
    if not clip.isOpened():
        print("Video could not be opened. Skipping...")
        return

    success = False
    # Read the video until a frame is successfully read
    while not success:
        success, frame = clip.read()

    bbox = [0, 0, frame.shape[1], frame.shape[0]]

    def line_select_callback(eclick, erelease):
        bbox[:2] = int(eclick.xdata), int(eclick.ydata)  # x1, y1
        bbox[2:] = int(erelease.xdata), int(erelease.ydata)  # x2, y2

    def validate_crop(*args):
        fig.canvas.stop_event_loop()

    def display_help(*args):
        print(
            "1. Use left click to select the region of interest. A red box will be drawn around the selected region. \n\n2. Use the corner points to expand the box and center to move the box around the image. \n\n3. Click "
        )

    fig = plt.figure()
    ax = fig.add_subplot(111)
    ax.imshow(frame[:, :, ::-1])
    ax_help = fig.add_axes([0.9, 0.2, 0.1, 0.1])
    ax_save = fig.add_axes([0.9, 0.1, 0.1, 0.1])
    crop_button = Button(ax_save, "Crop")
    crop_button.on_clicked(validate_crop)
    help_button = Button(ax_help, "Help")
    help_button.on_clicked(display_help)

    rs = RectangleSelector(
        ax,
        line_select_callback,
        drawtype="box",
        minspanx=5,
        minspany=5,
        interactive=True,
        spancoords="pixels",
        rectprops=dict(facecolor="red", edgecolor="black", alpha=0.3, fill=True),
    )
    plt.show()

    # import platform
    # if platform.system() == "Darwin":  # for OSX use WXAgg
    #    fig.canvas.start_event_loop(timeout=-1)
    # else:
    fig.canvas.start_event_loop(timeout=-1)  # just tested on Ubuntu I also need this.
    #    #fig.canvas.stop_event_loop()

    plt.close(fig)
    return bbox 

def show_progress(self):
        self.monitor_file = self.log_dir + '/monitor.csv'

        # Read progress file
        if not self.read_monitor_file():
            print('Progress data is missing')
            sys.exit(1)

        # Initialize graph
        plt.rcdefaults()
        plt.rcParams['font.size'] = 6
        plt.rcParams['lines.linewidth'] = 1.0
        plt.rcParams['legend.loc'] = 'lower right'

        self.fig = plt.figure(1, figsize=(16, 10))

        # Show widgets
        axcolor = 'lightgoldenrodyellow'
        self.axprogress = self.fig.add_axes([0.15, 0.10, 0.70, 0.15], facecolor=axcolor)
        self.axslider = self.fig.add_axes([0.15, 0.04, 0.70, 0.02], facecolor=axcolor)
        axfirst = self.fig.add_axes([0.15, 0.01, 0.03, 0.02])
        axlast = self.fig.add_axes([0.82, 0.01, 0.03, 0.02])
        axprev = self.fig.add_axes([0.46, 0.01, 0.03, 0.02])
        axnext = self.fig.add_axes([0.51, 0.01, 0.03, 0.02])

        # Slider is drawn in plot_progress()

        # First/Last button
        self.button_first = Button(axfirst, 'First', color=axcolor, hovercolor='0.975')
        self.button_first.on_clicked(self.first_episode_num)
        self.button_last = Button(axlast, 'Last', color=axcolor, hovercolor='0.975')
        self.button_last.on_clicked(self.last_episode_num)

        # Next/Prev button
        self.button_prev = Button(axprev, 'Prev', color=axcolor, hovercolor='0.975')
        self.button_prev.on_clicked(self.prev_episode_num)
        self.button_next = Button(axnext, 'Next', color=axcolor, hovercolor='0.975')
        self.button_next.on_clicked(self.next_episode_num)

        # Timer
        self.timer = self.fig.canvas.new_timer(interval=1000)
        self.timer.add_callback(self.check_update)
        self.timer.start()

        # Progress data
        self.axprogress.set_xmargin(0)
        self.axprogress.set_xlabel('Episodes')
        self.axprogress.set_ylabel('Reward')
        self.axprogress.grid(True)
        self.plot_progress()

        # Plot latest episode
        self.update_episode(self.num_episodes - 1)

        plt.show()