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I am using the MPL widget that comes with QT in the Python(x,y) package. I am attempting to refresh or redraw my plot with new data. The method fig.canvas.draw() refreshes the main plot only. The subplots are where my issue lies. The previous subplots and everything associated with them (axes scale, annotations, etc) are left on the chart. When I refresh, new subplot data are plotted over the old data, creating quite a mess. Everything associated with the main plot gets redrawn correctly. I have tried everything that I know to try, including clf, and cla. How does one refresh subplots with the QT MPL Widget that is included in Python(x,y)?

Here's my code:

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()

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()
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1 回答 1

1

从示例中不清楚如何self.mpl_widget.axes创建。它未使用，如下所述，绘制到轴实例的旧引用可能会导致问题。

因为mpl_widget.axes根本不使用，所以我建议不要在轴上保留参考。那么twinx例子中的使用就不正确了。以下可以工作：

if plot_page == 1:             #Plot 1st Page
    widget = self.mplwidget
if plot_page == 2:          #Plot 2nd Page
    widget = self.mplwidget_3
if plot_page == 3:           #Plot 3rd Page
    widget = self.mplwidget_3
if replot == 1:
    widget.figure.clear()
ax1 = widget.figure.add_subplot(111)
ax2 = ax1.twinx()

...

widget.figure.canvas.draw()

另一个问题是self.mpl_widgetXX.axes分配给plt并在下面的示例plt中用于绘制新数据。由于self.mpl_widgetXX.axes未更新以包含新创建的轴实例之一，因此示例代码绘制到旧轴，因此可能导致问题中描述的效果。您应该只使用ax1andax2进行绘图和刻度设置以及widget.figure访问图形实例。

于 2016-08-20T10:31:21.737 回答