我们从Python开源项目中，提取了以下23个代码示例，用于说明如何使用matplotlib.pyplot.get_current_fig_manager()。
def plot_network(image, model, label=None): layer_names = [l.name for l in model.layers if isinstance(l,Conv2D)] n_conv = len(layer_names) n_axes = n_conv prediction = model.predict(np.expand_dims(image,0)) mng = plt.get_current_fig_manager() mng.full_screen_toggle() fig, [axlist1, axlist2] = plt.subplots(2,n_conv) diagnosis = ["negative", "positive"] for j in range(n_conv): plot_heatmap(image, model, layer_names[j],"abnormal",axlist1[j]) # axlist1[j].set_xlabel(layer_names[j] + "ab") for j in range(n_conv): plot_heatmap(image, model, layer_names[j],"normal",axlist2[j],cmap=plt.cm.inferno) fig.suptitle("Prediction: {}, {}".format(prediction,label)) fig.show()
def createGraph(): global colors, pos # common.g=nx.DiGraph() # directed graph, instead of nx.Graph() common.g = nx.Graph() # undirected, for oligopoly project colors = {} pos = {} common.g_labels = {} common.g_edge_labels = {} # copy the address of the labels of the edges # setting Figure 1 (the switch of the control between Figure 1 and Figure 2 # is managed in oActions.py if not common.IPython or common.graphicStatus == "PythonViaTerminal": # the or is about ipython running in a terminal plt.figure(1) mngr1 = plt.get_current_fig_manager() # NB, after figure() mngr1.window.wm_geometry("+650+0") mngr1.set_window_title("Links Entrepreneurs - Workers") # searching tools
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)
def draw_loop(): """ Draw the graph in a loop """ global G plt.ion() # mng = plt.get_current_fig_manager() # mng.resize(*mng.window.maxsize()) plt.draw() for line in fileinput.input(): if output(line): plt.clf() nx.draw(G) plt.draw()
def plot(self): """ Plots result """ mng = plt.get_current_fig_manager() # Open directly in full window if mpl.get_backend() == 'Qt4Agg': # 'Qt4' backend mng.window.showMaximized() elif mpl.get_backend() == 'WxAgg': # 'WxAgg' backend mng.frame.Maximize(True) elif mpl.get_backend() == 'TKAgg': # 'TKAgg' backend mng.frame.Maximize(True) plt.show(all) # Show all plots
def phase1_plot_setup(): # Set up a 1x2 plot f, (ax1, ax2) = plt.subplots(1,2) f.suptitle('Phase 1 - Rise Times', fontsize=18, fontweight='bold') # Choose a colour palette and font size/style colours = sns.color_palette("muted") sns.set_context('poster') # Maximise the plotting window plot_backend = matplotlib.get_backend() mng = plt.get_current_fig_manager() if plot_backend == 'TkAgg': mng.resize(*mng.window.maxsize()) elif plot_backend == 'wxAgg': mng.frame.Maximize(True) elif plot_backend == 'Qt4Agg': mng.window.showMaximized() return f, ax1, ax2
def phase2_plot_setup(): # Set up a 1x1 plot f, ax1 = plt.subplots(1,1) f.suptitle('Phase 2 - Line Width', fontsize=18, fontweight='bold') # Choose a colour palette and font size/style colours = sns.color_palette("muted") sns.set_context('poster') # Maximise the plotting window plot_backend = matplotlib.get_backend() mng = plt.get_current_fig_manager() if plot_backend == 'TkAgg': mng.resize(*mng.window.maxsize()) elif plot_backend == 'wxAgg': mng.frame.Maximize(True) elif plot_backend == 'Qt4Agg': mng.window.showMaximized() return f, ax1
def plot_fits_for_user_confirmation(self, image): """ Ask user to check if all fits are correct. Clicking on a fit removes it from the results. """ _imshow_style = dict(origin='lower', interpolation='none', cmap=plt.cm.gray) fig_manager = plt.get_current_fig_manager() fig_manager.window.showMaximized() plt.clf() plt.cla() plt.imshow(image, **_imshow_style) for i in UserCheckFits.stored_fits.index: circle = plt.Circle((UserCheckFits.stored_fits.loc[i].x, UserCheckFits.stored_fits.loc[i].y), radius=UserCheckFits.stored_fits.loc[i].r, fc='None', ec='b', ls='solid', lw=0.3, label=i) # Enable picking circle.set_picker(10) plt.gca().add_patch(circle) plt.gca().annotate(i, (UserCheckFits.stored_fits.loc[i].x, UserCheckFits.stored_fits.loc[i].y), color='b', weight='normal', size=8, ha='center', va='center') plt.gca().set_title('Please check the result.' + ' Click on a circle to toggle removal.' + ' Close to confirm.') plt.gcf().canvas.mpl_connect('pick_event', self.on_pick) plt.show(block=True)
def make_image(sequence, epoch, name='_output_'): """plot drawing with separated strokes""" strokes = np.split(sequence, np.where(sequence[:,2]>0)[0]+1) fig = plt.figure() ax1 = fig.add_subplot(111) for s in strokes: plt.plot(s[:,0],-s[:,1]) canvas = plt.get_current_fig_manager().canvas canvas.draw() pil_image = PIL.Image.frombytes('RGB', canvas.get_width_height(), canvas.tostring_rgb()) name = str(epoch)+name+'.jpg' pil_image.save(name,"JPEG") plt.close("all")
def on_press(self, event): # At first gets the toolbar-button-pressed-info and checks if # no toolbar-button is pressed (zooming or shifting/moving) # So zooming/shifting can be done without drawing a new rectangle toolbar = plt.get_current_fig_manager().toolbar if toolbar.mode == '': # If the mouse is INSIDE the plot if event.inaxes is self.ax1: # Enables drawing self.draw = 1 # Gets the y-coordinate, where the mouse it located self.y0 = event.ydata # On mouse button release
def on_press(self, event): # If not the left mouse-button is clicked if event.button != 1: return # At first gets the toolbar-button-pressed-info and checks if # no toolbar-button is pressed (zooming or shifting/moving) # So zooming/shifting can be done without drawing a new rectangle toolbar = plt.get_current_fig_manager().toolbar if toolbar.mode == '': # If the mouse is INSIDE the first plot if event.inaxes is self.ax1: # Enables drawing self.draw = 1 # Gets the coordinates, where the mouse it located self.x0 = event.xdata self.y0 = event.ydata # If mouse in second plot if event.inaxes is self.ax2: # Enables drawing just of the x-coord (y=mag is static) self.draw = 1 self.x0 = event.xdata if event.inaxes is self.ax3: # Enables drawing just of the x-coord (y=mag is static) # This x-value of this graph is the actual y-center-value self.draw = 1 self.y0 = event.xdata # On mouse button release
def plot_alignment_errors(errors_position, rmse_pose, errors_orientation, rmse_orientation, blocking=True): assert np.array_equal(errors_position.shape, errors_orientation.shape) num_error_values = errors_position.shape[0] title_position = 1.05 fig = plt.figure() a1 = fig.add_subplot(2, 1, 1) fig.suptitle("Alignment Evaluation", fontsize='24') a1.set_title( "Red = Position Error Norm [m] - Black = RMSE", y=title_position) plt.plot(errors_position, c='r') plt.plot(rmse_pose * np.ones((num_error_values, 1)), c='k') a2 = fig.add_subplot(2, 1, 2) a2.set_title( "Red = Absolute Orientation Error [Degrees] - Black = RMSE", y=title_position) plt.plot(errors_orientation, c='r') plt.plot(rmse_orientation * np.ones((num_error_values, 1)), c='k') if plt.get_backend() == 'TkAgg': mng = plt.get_current_fig_manager() max_size = mng.window.maxsize() max_size = (max_size[0], max_size[1] * 0.45) mng.resize(*max_size) fig.tight_layout() plt.subplots_adjust(left=0.025, right=0.975, top=0.8, bottom=0.05) plt.show(block=blocking)
def setAttr(x,y,title): #x and y are integer numbers; title a string mngr=plt.get_current_fig_manager() mngr.window.wm_geometry("+"+str(x)+"+"+str(y)) mngr.set_window_title(title) #---------------------------------------- # running in a Python IDE (recognized: IDLE or Spyder)
def __call__(self, in_file, save=False): self.file = in_file self.fig, self.ax = plt.subplots() # read data and get its wavelength solution ccd = CCDData.read(self.file, unit=u.adu) wcs_reader = ReadWavelengthSolution(header=ccd.header, data=ccd.data) wavelength, intensity = wcs_reader() manager = plt.get_current_fig_manager() manager.window.showMaximized() plt.title('{:s}\n{:s}'.format(self.file, ccd.header['OBJECT'])) self.ax.plot(wavelength, intensity, color='k', label='Data') self.ax.axvline(6562.8, color='r') self.ax.set_xlim((wavelength[0], wavelength[-1])) self.ax.set_ylabel('Intensity (ADU)') self.ax.set_xlabel('Wavelength (Angstrom)') plt.legend(loc='best') plt.subplots_adjust(left=0.05, right=0.99, top=0.96, bottom=0.04, hspace=0.17, wspace=0.11) # plt.tight_layout() if not save: self.fig.canvas.mpl_connect('key_press_event', self.key_pressed) plt.show() # else: # output = re.sub('.fits', '.png', self.file) # plt.savefig(output, dpi=600)
def _ignore(self, e): # https://scipy.github.io/old-wiki/pages/Cookbook/Matplotlib/Interactive_Plotting.html#Handling_click_events_while_zoomed # But we don't do `not e.inaxes` because that one is only set when the mouse moves, meaning # when we switch the frame, it will not be `inaxes` as long as we don't move the mouse! return plt.get_current_fig_manager().toolbar.mode != '' # Annoyingly large amount of code for just a circle around the mouse cursor!
def __init__(self, *args, **kwargs): super(NuPICPlotOutput, self).__init__(*args, **kwargs) # Turn matplotlib interactive mode on. plt.ion() self.dates = [] self.convertedDates = [] self.value = [] self.rawValue = [] self.allValues = [] self.allRawValues = [] self.predicted = [] self.anomalyScore = [] self.anomalyLikelihood = [] self.actualLine = None self.rawLine = None self.predictedLine = None self.anomalyScoreLine = None self.anomalyLikelihoodLine = None self.linesInitialized = False self._chartHighlights = [] fig = plt.figure(figsize=(16, 10)) gs = gridspec.GridSpec(2, 1, height_ratios=[3, 1]) self._mainGraph = fig.add_subplot(gs[0, 0]) plt.title(self.name) plt.ylabel('Value') plt.xlabel('Date') self._anomalyGraph = fig.add_subplot(gs[1]) plt.ylabel('Percentage') plt.xlabel('Date') # Maximizes window mng = plt.get_current_fig_manager() mng.resize(800, 600) plt.tight_layout()
def show(self, voxel_ind=0, names=None, maps_to_show=None, to_file=None, block=True, maximize=False, show_trace=True, nmr_bins=20, window_title=None, show_sliders=True, fit_gaussian=True, figure_options=None, sample_indices=None): """Show the samples per voxel. Args: voxel_ind (int): the voxel to show the samples from. names (dict): A list of names for the different maps. Use as ``{map_name: display_name}`` that is, the key is the name of the map in the volumes dictionary and the display name is the string that will be used as title for that map. maps_to_show (:class:`list`): A list of maps to show. The items in this list must correspond to the keys in the volumes dictionary. to_file (string, optional, default None): If to_file is not None it is supposed to be a filename where the image will be saved. If not set to None, nothing will be displayed, the results will directly be saved. Already existing items will be overwritten. 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 show_trace (boolean): if we show the trace of each map or not nmr_bins (dict or int): either a single value or one per map name show_sliders (boolean): if we show the slider or not fit_gaussian (boolean): if we fit and show a normal distribution (Gaussian) to the histogram or not window_title (str): the title of the window. If None, the default title is used figure_options (dict) options for the figure sample_indices (list): the list of sample indices to use """ figure_options = figure_options or {'figsize': (18, 16)} self._figure = plt.figure(**figure_options) if names: self.names = names if maps_to_show: self.maps_to_show = maps_to_show self.voxel_ind = voxel_ind self._nmr_bins = nmr_bins or self._nmr_bins self._show_trace = show_trace self.show_sliders = show_sliders self._fit_gaussian = fit_gaussian self._sample_indices = sample_indices self._setup() 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 to_file: plt.savefig(to_file) plt.close() else: plt.draw() if block: plt.show(True)
def __init__(self, reference_dir): self.cleaned_list = [] reference_data = ReferenceData(reference_dir) file_list = glob.glob(os.path.join(reference_dir, '*fits')) for lfile in file_list: self.fig, self.ax = plt.subplots() ccd = CCDData.read(lfile, unit=u.adu) read_wavelength = ReadWavelengthSolution(ccd.header, ccd.data) wavelength, intensity = read_wavelength() self.line_list = reference_data.get_line_list_by_name( ccd.header['OBJECT']) file_name = lfile.split('/')[-1] pickle_file_name = re.sub('.fits', '_list.pkl', file_name) manager = plt.get_current_fig_manager() manager.window.showMaximized() if os.path.isfile(pickle_file_name): with open(pickle_file_name, 'rb') as pickled_file: line_list = pickle.load(pickled_file) for ref_line in line_list: self.ax.axvline(ref_line, color='r', alpha=1) else: for ref_line in self.line_list: self.ax.axvline(ref_line, color='r', alpha=.4) self.ax.set_title(file_name) self.ax.plot(wavelength, intensity, color='k') self.ax.set_xlabel('Wavelength (Angstrom)') self.ax.set_ylabel('Intensity (ADU)') self.ax.set_xlim((wavelength[0], wavelength[-1])) self.fig.canvas.mpl_connect('button_press_event', self.on_click) plt.show() if self.cleaned_list != []: with open(pickle_file_name, 'wb') as list_file: pickle.dump(self.cleaned_list, list_file, protocol=pickle.HIGHEST_PROTOCOL)
def _plot_raw_onkey(event, params): """Interpret key presses""" import matplotlib.pyplot as plt if event.key == 'escape': plt.close(params['fig']) elif event.key == 'down': params['ch_start'] += params['n_channels'] _channels_changed(params, len(params['info']['ch_names'])) elif event.key == 'up': params['ch_start'] -= params['n_channels'] _channels_changed(params, len(params['info']['ch_names'])) elif event.key == 'right': value = params['t_start'] + params['duration'] _plot_raw_time(value, params) params['update_fun']() params['plot_fun']() elif event.key == 'left': value = params['t_start'] - params['duration'] _plot_raw_time(value, params) params['update_fun']() params['plot_fun']() elif event.key in ['+', '=']: params['scale_factor'] *= 1.1 params['plot_fun']() elif event.key == '-': params['scale_factor'] /= 1.1 params['plot_fun']() elif event.key == 'pageup': n_channels = params['n_channels'] + 1 _setup_browser_offsets(params, n_channels) _channels_changed(params, len(params['info']['ch_names'])) elif event.key == 'pagedown': n_channels = params['n_channels'] - 1 if n_channels == 0: return _setup_browser_offsets(params, n_channels) if len(params['lines']) > n_channels: # remove line from view params['lines'][n_channels].set_xdata([]) params['lines'][n_channels].set_ydata([]) _channels_changed(params, len(params['info']['ch_names'])) elif event.key == 'home': duration = params['duration'] - 1.0 if duration <= 0: return params['duration'] = duration params['hsel_patch'].set_width(params['duration']) params['update_fun']() params['plot_fun']() elif event.key == 'end': duration = params['duration'] + 1.0 if duration > params['raw'].times[-1]: duration = params['raw'].times[-1] params['duration'] = duration params['hsel_patch'].set_width(params['duration']) params['update_fun']() params['plot_fun']() elif event.key == '?': _onclick_help(event, params) elif event.key == 'f11': mng = plt.get_current_fig_manager() mng.full_screen_toggle()
def replace_segment(self): # print "Segment ", str(self._iter), " smoothed" old_dur = self._vertex2[0] - self._vertex1[0] new_dur = self._s[-1,0] - self._s[0,0] if new_dur < old_dur: if (self._plot_demo): if (self._plotIndex == -1): # plt.close('all') self._plotIndex = 0 # plt.figure() f, self._axarr = plt.subplots(2,2) self._axarr[0,0].plot(self._traj[:,0],self._traj[:,1:8]) self._axarr[0,0].set_title('Iterations = 0') # print "replacing segment" self._traj = np.delete(self._traj,range(int(self._ind1),int(self._ind2+1)),0) self._traj[self._ind1:,0] += new_dur - old_dur self._traj = np.insert(self._traj,self._ind1,self._s,0) if (self._plot_demo): if self._plotIndex == 0: self._axarr[0,1].plot(self._traj[:,0],self._traj[:,1:8]) title = "Iterations = " + str(self._plotIndex+1) self._axarr[0,1].set_title(title) self._plotIndex = 1 # plt.show(block=False) # raw_input('Press enter to continue...') elif self._plotIndex == 1: print('check 1') self._axarr[1,0].plot(self._traj[:,0],self._traj[:,1:8]) title = "Iterations = " + str(self._plotIndex+1) self._axarr[1,0].set_title(title) self._plotIndex = 2 print ('check 2') # plt.show(block=False) elif self._plotIndex == 2: print ('check 3') self._axarr[1,1].plot(self._traj[:,0],self._traj[:,1:8]) title = "Iterations = " + str(self._plotIndex+1) self._axarr[1,1].set_title(title) self._plotIndex = 3 plt.show(block=False) wm = plt.get_current_fig_manager() wm.window.wm_geometry("800x500+1000+0") raw_input('Press enter to continue...') else: self._iter -=1 if self._iter < 30: print "smoothing next segment" self._iter += 1 self.smooth_path() else: print "sent to publish" self.publish_traj() self._executing = False
def replace_segment(self): # print "Segment ", str(self._iter), " smoothed" old_dur = self._vertex2[0] - self._vertex1[0] new_dur = self._s[-1,0] - self._s[0,0] if new_dur < old_dur: if (self._plot_demo): if (self._plotIndex == -1): # plt.close('all') self._plotIndex = 0 f, self._axarr = plt.subplots(2,2) self._axarr[0,0].plot(self._traj[:,0],self._traj[:,1:8]) self._axarr[0,0].set_title('Iterations = 0') # print "replacing segment" self._traj = np.delete(self._traj,range(int(self._ind1),int(self._ind2+1)),0) self._traj[self._ind1:,0] += new_dur - old_dur self._traj = np.insert(self._traj,self._ind1,self._s,0) if (self._plot_demo): if self._plotIndex == 0: self._axarr[0,1].plot(self._traj[:,0],self._traj[:,1:8]) title = "Iterations = " + str(self._plotIndex+1) self._axarr[0,1].set_title(title) self._plotIndex = 1 # plt.show(block=False) # raw_input('Press enter to continue...') elif self._plotIndex == 1: print('check 1') self._axarr[1,0].plot(self._traj[:,0],self._traj[:,1:8]) title = "Iterations = " + str(self._plotIndex+1) self._axarr[1,0].set_title(title) self._plotIndex = 2 print ('check 2') # plt.show(block=False) elif self._plotIndex == 2: print ('check 3') self._axarr[1,1].plot(self._traj[:,0],self._traj[:,1:8]) title = "Iterations = " + str(self._plotIndex+1) self._axarr[1,1].set_title(title) self._plotIndex = 3 plt.show(block=False) wm = plt.get_current_fig_manager() wm.window.wm_geometry("800x500+1000+0") raw_input('Press enter to continue...') else: self._iter -=1 if self._iter < 30: print "smoothing next segment" self._iter += 1 self.smooth_path() else: print "sent to publish" self.publish_traj() self._executing = False
