Python FigureCanvasTkAgg.copy_from_bbox方法代码示例

# 需要导入模块: from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg [as 别名]
# 或者: from matplotlib.backends.backend_tkagg.FigureCanvasTkAgg import copy_from_bbox [as 别名]
def Plotting(queue):
    
    while queue.get() != "Start Plotting Process":
        wait = "Waiting"
    
    timeNow = datetime.time(datetime.now())
    time = timeNow.minute + (timeNow.second + timeNow.microsecond/1000000.0)/60.0
    lastX = time
    lastY = 90250
    connect = True
    step = 0
    x=[]
    y=[]
    
    mode = "24-Hour-Plot"
    
    root = tk.Tk()
    root.wm_title("PyAmaseis v1.0")
    root.iconbitmap(r'icons/icon.ico')
    root.wm_state('zoomed')
    
    graphHeightConst = 2500
    
    fig = plt.figure(figsize=(15,10))
    fig.set_tight_layout(0.4)
    
    ax = fig.add_subplot(1,1,1)
    ax.set_xlim(0,60)
    ax.set_ylim(30250,92750)
    ax.set_xlabel('Time(minutes)')
    
    xAxis = [0,60]
    yAxis = [30250,92750]
    
    y1 = (np.arange(min(yAxis), max(yAxis)+1,graphHeightConst))
    y2 = calculateYAxisLabels()
    
    ax.set_xticks(np.arange(min(xAxis), max(xAxis)+1,1))
    plt.yticks(y1, y2)
    ax.yaxis.grid(color = '#0000FF' )
    ax.set_axisbelow(True)
    line, = ax.plot(x, y, color='k')
    canvas = FigureCanvasTkAgg(fig, master=root)

    canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=1)
    label = tk.Label(text="")
    label.pack()
    background = canvas.copy_from_bbox(ax.bbox)
    canvas.draw()

    root.after(0, plotData,queue, fig, ax, canvas, label, root, lastY, lastX, connect, background, line, mode)
    
    root.mainloop()

# 需要导入模块: from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg [as 别名]
# 或者: from matplotlib.backends.backend_tkagg.FigureCanvasTkAgg import copy_from_bbox [as 别名]

#.........这里部分代码省略.........
        if subplot.get_autoscaley_on():
            subplot.relim()
            subplot.autoscale_view(scalex=False, scaley=True)
        self.canvas.draw()

    def setDoAutoscale(self, doAutoscale, subplotInd=0):
        """Turn autoscaling on or off for the specified subplot
        
        You can also turn off autoscaling by calling setYLimits.
        """
        doAutoscale = bool(doAutoscale)
        subplot = self.subplotArr[subplotInd]
        subplot.set_ylim(auto=doAutoscale)
        if doAutoscale:
            subplot.relim()
            subplot.autoscale_view(scalex=False, scaley=True)
    
    def setYLimits(self, minY, maxY, subplotInd=0):
        """Set y limits for the specified subplot and disable autoscaling.
        
        Note: if you want to autoscale with a minimum range, use showY.
        """
        self.subplotArr[subplotInd].set_ylim(minY, maxY, auto=False)
    
    def showY(self, y0, y1=None, subplotInd=0):
        """Specify one or two values to always show in the y range.
        
        Inputs:
        - subplotInd: index of subplot
        - y0: first y value to show
        - y1: second y value to show; None to omit

        Warning: setYLimits overrides this method (but the values are remembered in case you turn
        autoscaling back on).
        """
        subplot = self.subplotArr[subplotInd]
        yMin, yMax = subplot.get_ylim()
        
        if y1 is not None:
            yList = [y0, y1]
        else:
            yList = [y0]
        doRescale = False
        for y in yList:
            subplot.axhline(y, linestyle=" ")
            if subplot.get_autoscaley_on() and numpy.isfinite(y) and not (yMin <= y <= yMax):
                doRescale = True
        if doRescale:
            subplot.relim()
            subplot.autoscale_view(scalex=False, scaley=True)

    def _handleDrawEvent(self, event=None):
        """Handle draw event
        """
#         print "handleDrawEvent"
        for subplot in self.subplotArr:
            subplot._scwBackground = self.canvas.copy_from_bbox(subplot.bbox)
            for line in subplot._scwLines:
                subplot.draw_artist(line.line2d)
            self.canvas.blit(subplot.bbox)
    
    def _handleMap(self, evt):
        """Handle map event (widget made visible)
        """
        self._isVisible = True
        self._handleDrawEvent()
        self._updateTimeAxis()
    
    def _handleUnmap(self, evt):
        """Handle unmap event (widget made not visible)
        """
        self._isVisible = False
    
    def _updateTimeAxis(self):
        """Update the time axis; calls itself
        """
        tMax = time.time() + self.updateInterval
        tMin = tMax - self._timeRange
        minMplDays = self._cnvTimeFunc(tMin)
        maxMplDays = self._cnvTimeFunc(tMax)
        
        self._purgeCounter = (self._purgeCounter + 1) % self._maxPurgeCounter
        doPurge = self._purgeCounter == 0

        if doPurge:
            for subplot in self.subplotArr:
                for line in subplot._scwLines:
                    line._purgeOldData(minMplDays)
        
        if self._isVisible or self._isFirst:
            for subplot in self.subplotArr:
                subplot.set_xlim(minMplDays, maxMplDays)
                if doPurge:
                    if subplot.get_autoscaley_on():
                        # since data is being purged the y limits may have changed
                        subplot.relim()
                        subplot.autoscale_view(scalex=False, scaley=True)
            self._isFirst = False
            self.canvas.draw()
        self._timeAxisTimer.start(self.updateInterval, self._updateTimeAxis)

# 需要导入模块: from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg [as 别名]
# 或者: from matplotlib.backends.backend_tkagg.FigureCanvasTkAgg import copy_from_bbox [as 别名]

#.........这里部分代码省略.........
        self.var_func.set(self.function_list[0])
        
        
       
       
        self.MotorMenu = OptionMenu(self.buttonframe,self.var_func, *self.function_list, command = self.init_function)
        self.MotorMenu.grid(row = 3,column =1,sticky = W)
        
        self.normalization_constant = 1
        self.scale_list = []
        self.var_list = []
        
        self.fig = Figure(figsize=(5,3))
        self.ax1  = self.fig.add_subplot(111)
        dataplot = self.ax1.plot(arange(2800,3605,5),zeros((161,)),animated = True)[0]#(ax = self.ax1).lines[-1]
        
        guessplot = self.ax1.plot(arange(2800,3605,5),zeros((161,)),animated = True)[0]
        
        
        self.canvas = FigureCanvasTkAgg(self.fig,master = self.plotframe)
        
        self.canvas.show()
        
        
        self.canvas._tkcanvas.pack(side=TOP, fill = BOTH,expand =True)
        
        
        self.toolbar = NavigationToolbar2TkAgg(self.canvas, self.plotframe)
        self.toolbar.update()
        self.toolbar.pack(side= BOTTOM, fill = BOTH,expand =True)#,expand = True)#fill=BOTH)#, expand=1)
        
        self.canvas.draw()
        self.canvas.show()
        self.background = self.canvas.copy_from_bbox(self.ax1.bbox)
            
         
        self.reference = numpy.ndarray((161,))
        self.reference[:] = 1
        self.reference_name  = ''
        self.guess = list()

        self.name = ['']
        if ramanspectrum is None:
            self.a = pandas.Series(zeros(161),arange(2800,3605,5))
        else:
            self.a = copy(ramanspectrum)
            print self.a
           
            self.t.insert(END,'data multiplied by'+str(1/max(self.a)))
            self.a[:]/=max(self.a.values)
            
        self.startfreq_text = Entry(self.buttonframe,width = 5)
        self.startfreq = min(array(self.a.index))
        self.startfreq_text.insert(END,str(self.startfreq))
        self.startfreq_text.bind("<Return>", self.update_limits)
        self.startfreq_text.grid(row = 0 , column =1,sticky = W)
        
        
        self.endfreq_text = Entry(self.buttonframe,width = 5)
        self.endfreq = max(array(self.a.index))
        self.endfreq_text.insert(END,str(self.endfreq))
        self.endfreq_text.bind("<Return>", self.update_limits)
        self.endfreq_text.grid(row = 1 , column =1,sticky = W)
        
        if self.init_function('OneLorentzian') == -1:
            self.t.insert(END, 'error initializing fit function')

# 需要导入模块: from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg [as 别名]
# 或者: from matplotlib.backends.backend_tkagg.FigureCanvasTkAgg import copy_from_bbox [as 别名]
class MultichannelPlot(matplotlib.figure.Figure):
    def __init__(self, master, row=0, column=0, rowspan=5, columnspan=5, width=5, height=3, update_prot="blit"):
        matplotlib.figure.Figure.__init__(self, figsize=(width, height))
        self.update_prot = update_prot
        self.frame = Frame(master=master)
        self.frame.config(bd=5)

        self.frame.grid(row=row, column=column, padx=5, pady=5)
        self.channel_list = []
        self.array_list = []
        self.color_list = ["r", "b", "g", "c", "m", "y", "k"]

        self.a = self.add_subplot(MultichannelAxis(self, 111))

        self.canvas = FigureCanvasTkAgg(self, master=self.frame)
        self.canvas.show()

        self.canvas._tkcanvas.pack(side=TOP, fill=BOTH, expand=True)

        self.toolbar = NavigationToolbar2TkAgg(self.canvas, self.frame)
        self.toolbar.update()
        self.toolbar.pack(side=BOTTOM, fill=BOTH, expand=True)  # ,expand = True)#fill=BOTH)#, expand=1)
        self.canvas.draw()
        self.background = self.canvas.copy_from_bbox(self.a.bbox)

        return None

    def AddChannel(self, spec_array, channel_type, color=None):

        if color == None or color == "":
            self.a.add_line(Channel([], [], self, spec_array, channel_type, color=self.color_list[0]))
            self.color_list.append(self.color_list[0])
            del (self.color_list[0])

        else:
            self.a.add_line(Channel([], [], self, spec_array, channel_type, color=color))
        # self.Update()
        self.Redraw()
        return self.a.lines[-1]

    def RemoveChannel(self, channel):
        self.a.lines.remove(channel)
        self.Redraw()

        return 0

    def SetChannelColor(self, channel, clr):
        if clr != "":
            channel.color = clr

        else:
            channel.color = self.color_list[0]
            self.color_list.append(self.color_list[0])
            del (self.color_list[0])

        return 0

    def ShowChannel(self, channel):
        channel.set_visible(True)

        self.Update()
        return 0

    def HideChannel(self, channel):
        channel.set_visible(False)
        self.Update()
        return 0

    def Redraw(self):

        self.a.relim()
        self.a.autoscale_view(tight=False)

        self.canvas.draw()
        self.canvas.restore_region(self.background)
        for line in self.a.lines:
            self.a.draw_artist(line)

        self.canvas.blit(self.a.bbox)

        return 0

    def SaveFigure(self, filename):

        self.f_copy = self.a
        self.f_copy.savefig("a.png")

        return 0

    def Update(self):
        if self.update_prot == "draw":
            self.canvas.draw()
            return 0

        (lower_y_lim, upper_y_lim) = self.a.get_ylim()
        (lower_x_lim, upper_x_lim) = self.a.get_xlim()
        scaley_bool = False
        scalex_bool = False
        scaley_down_bool = True

#.........这里部分代码省略.........