有谁知道如何摆脱Matplotlib阴谋左边的黑色'y'轴？

Question

将所有'y'轴移动到子图后，我得到一个不需要的轴。这是左边的黑色。有谁知道如何摆脱它？我敢肯定，当我打电话给我时，它已经被绘制出来了，但我不知道如何摆脱它。

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


    if plot_page == 1:    #Plot 1st Page       
     #plt0 = self.mplwidget.axes         
     fig = self.mplwidget.figure #Add a figure    


    if plot_page == 2:   #Plot 2nd Page 
     #plt0 = self.mplwidget_2.axes 
     fig = self.mplwidget_2.figure #Add a figure 


    if plot_page == 3:   #Plot 3rd Page 
     #plt0 = self.mplwidget_3.axes 
     fig = self.mplwidget_3.figure #Add a figure 

    #Clears Figure if data is roplotted 

    if replot == 1: 
     fig.clf() 

    par0 = fig.add_subplot(111) 
    par1 = fig.add_subplot(111) 
    par2 = fig.add_subplot(111) 

    #Add Axes 
    plt = par0.twinx() 
    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] 

    #Plot Chart 
    plt.hold(True)  
    plt.plot(fac_flow, fac_lift, 'b', linestyle = "dashed", linewidth = 1)   

    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 
    fig.set_facecolor('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 

    plt.yaxis.tick_left() 
    # 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.yaxis.set_label_position("left") 
    plt.set_xlabel("BPD") 
    plt.set_ylabel("Feet" , color = 'b') 

    #ax1.set_ylabel("BHP", color = 'r') 
    #ax1.set_ylabel("Effiency", color = 'g') 

    # Set tight layout  
    fig.set_tight_layout   

    # Since we moved Feet Axis to subplot, extra unneeded axis was created. This Removes it 


    # Refresh 
    fig.canvas.update() 
    fig.canvas.draw() 

Answer 1

那么它看起来像你有三个y轴，参照你想不被显示的一个，你可以尝试添加：

ax.yaxis.set_tick_params(labelsize=0, length=0, which='major') 

只作无形标签和蜱虫。我想这是你想要去的？