如何刷新使用Python（x，y）QT设计器Matplotlib Widget创建的子图？

Question

我正在使用Python（x，y）包中的QT附带的MPL小部件。我正试图刷新或重新绘制新的数据。方法fig.canvas.draw（）仅刷新主图。小区是我的问题所在。之前的小插曲和与它们相关的所有内容（轴标尺，注释等）都留在了图表上。当我刷新时，新的子图数据被绘制在旧数据上，造成相当的混乱。与主图相关的所有内容都可以正确重绘。我尝试了我所知道的所有尝试，包括clf和cla。如何用Python（x，y）中包含的QT MPL Widget刷新子图？

这里是我的代码：

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() 

Answer 1

从如何创建self.mpl_widget.axes目前尚不清楚的例子。它不被使用，并且如下所述，绘制轴实例的旧参考可能导致问题。

由于mpl_widget.axes根本没有使用，我建议不要在轴上保留一个参考。然后在示例中使用twinx是不正确的。下面可以工作：

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，并进一步在下面的例子中plt用于绘制新的数据。因为self.mpl_widgetXX.axes未更新为包含新创建的轴实例之一，示例代码将绘制到旧轴，因此可能会导致问题中所述的效果。 您应该只使用ax1和ax2进行绘图和打勾设置，并使用widget.figure来访问图形实例。