如何刷新嵌入在PyQt4 Widget中的Matplotlib图中的子图

Question

之前有人建议我用fig.canvas.draw（）来刷新我的数据。它在主要情节上运作良好，但我也有图表中包含的子图。子图正在重新绘制，但是旧的子图以及轴和其他项目不会被清除。当我重新绘制时，有谁知道如何摆脱旧的子情节曲线和其他项目？

def mpl_plot(self, plot_page, replot = 0):  #Data stored in lists  

    if plot_page == 1:             #Plot 1st Page                        
        plt = self.mplwidget.axes                                
        fig = self.mplwidget.figure #Add a figure           

    if plot_page == 2:          #Plot 2nd Page
        plt = self.mplwidget_2.axes 
        fig = self.mplwidget_2.figure    #Add a figure

    if plot_page == 3:           #Plot 3rd Page
        plt = self.mplwidget_3.axes 
        fig = self.mplwidget_3.figure    #Add a figure    

    if replot == 1:

        #self.mplwidget_2.figure.clear()          

        print replot

    par1 = fig.add_subplot(111)
    par2 = fig.add_subplot(111)      


    #Add Axes
    ax1 = par1.twinx()        
    ax2 = par2.twinx() 



    impeller = str(self.comboBox_impellers.currentText())  #Get Impeller
    fac_curves = self.mpl_factory_specs(impeller)    
    fac_lift = fac_curves[0]        
    fac_power = fac_curves[1]
    fac_flow = fac_curves[2]
    fac_eff = fac_curves[3]        
    fac_max_eff = fac_curves[4]
    fac_max_eff_bpd = fac_curves[5]
    fac_ranges = self.mpl_factory_ranges()
    min_range = fac_ranges[0]
    max_range = fac_ranges[1]
    #bep = fac_ranges[2]
    #Plot Chart
    plt.hold(False)    #Has to be included for  multiple curves
    #Plot Factory Pressure
    plt.plot(fac_flow, fac_lift, 'b', linestyle = "dashed", linewidth = 1)



    #Plot Factory Power
    ax1.plot(fac_flow, fac_power, 'r', linestyle = "dashed", linewidth = 1)       
    ax2.plot(fac_flow, fac_eff, 'g', linestyle = "dashed", linewidth = 1)


    #Move spines
    ax2.spines["right"].set_position(("outward", 25))
    self.make_patch_spines_invisible(ax2)
    ax2.spines["right"].set_visible(True)  
    #Plot x axis minor tick marks
    minorLocatorx = AutoMinorLocator()        
    ax1.xaxis.set_minor_locator(minorLocatorx)
    ax1.tick_params(which='both', width= 0.5)
    ax1.tick_params(which='major', length=7)
    ax1.tick_params(which='minor', length=4, color='k')

    #Plot y axis minor tick marks
    minorLocatory = AutoMinorLocator()
    plt.yaxis.set_minor_locator(minorLocatory)
    plt.tick_params(which='both', width= 0.5)
    plt.tick_params(which='major', length=7)
    plt.tick_params(which='minor', length=4, color='k')
    #Make Border of Chart White


    #Plot Grid        
    plt.grid(b=True, which='both', color='k', linestyle='-') 

    #set shaded Area 
    plt.axvspan(min_range, max_range, facecolor='#9BE2FA', alpha=0.5)    #Yellow rectangular shaded area

    #Set Vertical Lines
    plt.axvline(fac_max_eff_bpd, color = '#69767A')

    #BEP MARKER   *** Can change marker style if needed
    bep = fac_max_eff * 0.90     #bep is 90% of maximum efficiency point

    bep_corrected = bep * 0.90   # We knock off another 10% to place the arrow correctly on chart

    ax2.annotate('BEP', xy=(fac_max_eff_bpd, bep_corrected), xycoords='data',   #Subtract 2.5 shows up correctly on chart
            xytext=(-50, 30), textcoords='offset points',
            bbox=dict(boxstyle="round", fc="0.8"),
            arrowprops=dict(arrowstyle="-|>",
                            shrinkA=0, shrinkB=10,
                            connectionstyle="angle,angleA=0,angleB=90,rad=10"),
                    )
    #Set Scales         
    plt.set_ylim(0,max(fac_lift) + (max(fac_lift) * 0.40))    #Pressure 
    #plt.set_xlim(0,max(fac_flow))

    ax1.set_ylim(0,max(fac_power) + (max(fac_power) * 0.40))     #Power
    ax2.set_ylim(0,max(fac_eff) + (max(fac_eff) * 0.40))    #Effiency


    # Set Axes Colors
    plt.tick_params(axis='y', colors='b')
    ax1.tick_params(axis='y', colors='r')
    ax2.tick_params(axis='y', colors='g')

    # Set Chart Labels        
    plt.set_xlabel("BPD")
    plt.set_ylabel("Feet" , color = 'b')

    #To redraw plot


    fig.canvas.draw()