Load .fig figure form Matlab in python. Error bars make figure look weird

Question

I got a .fig file generated in Matlab and I would like to display it in python environment, or at least retrieve the data. It works well when the original figure does not contain error bars. But when I have error bars then it looks like a staircase. Any ideas on how I could fix it?

The code I have been using is this:

## escape disti time for ions ##

size_f =26
def plotFig(filename,fignr=1):
    from scipy.io import loadmat
    from numpy import size
    from matplotlib.pyplot import plot,figure,xlabel,ylabel,show,clf,xlim,ylim,legend,yticks,xticks
    d = loadmat(filename,squeeze_me=True, struct_as_record=False)
    ax1 = d['hgS_070000'].children
    if size(ax1) > 1:
        legs= ax1[1]
        ax1 = ax1[0]
    else:
        legs=0
    figure(fignr)
    clf()
    #hold(True)
    counter = 0 
    counter1 =0
   # x=np.zeros((1000,1000))
    #y=np.zeros((1000,1000))
    for line in ax1.children:
        if line.type == 'graph2d.lineseries':
            if hasattr(line.properties,'Marker'):
                mark = "%s" % line.properties.Marker
                mark = mark[0]
            else:
                mark = '.'
            if hasattr(line.properties,'LineStyle'):
                linestyle = "%s" % line.properties.LineStyle
            else:
                linestyle = '-'
            if hasattr(line.properties,'Color'):
                r,g,b =  line.properties.Color
            else:
                r = 0
                g = 0
                b = 1
            if hasattr(line.properties,'MarkerSize'):
                marker_size = line.properties.MarkerSize
            else:
                marker_size = 1   
            #if counter1 ==0:
                x = line.properties.XData
                y = line.properties.YData
                #counter1=1
            #else:
                # x1 = line.properties.XData
                # y1 = line.properties.YData
                
            
            if counter ==0:
                x = line.properties.XData
                y = line.properties.YData
                plt.plot(x[y>0],y[y>0],linestyle=linestyle,linewidth=3.0)
                counter=1
            elif counter==1:
                x1 = line.properties.XData
                y1 = line.properties.YData
                #plt.plot(x1[y1>0],y1[y1>0],linestyle=linestyle,linewidth=3.0)
                counter=2
                
            else:
                x = line.properties.XData
                y = line.properties.YData
                plt.plot(x[y>0],y[y>0],linestyle=linestyle,linewidth=4.0,color=[r,g,b])
            
                plt.yscale('log')
                plt.xscale('log')
        elif line.type == 'text':
            if counter < 1:
                xlabel(r'$%s$' % line.properties.String,fontsize =18)
                #xlabel('%s' % line.properties.String,fontsize = 18)
                counter += 1
            elif counter < 2:
                ylabel(r'$%s$' % line.properties.String,fontsize = 18)
               # ylabel('%s' % line.properties.String,fontsize = 18)
                counter += 1    
              
    ylim(1e-7,1e-1)
    #ylim(ax1.properties.YLim)
    xlim((1e-2, 1e3)) 
    plt.rcParams["figure.figsize"] = [10,8]
    plt.tick_params(axis='x',labelsize=size_f)
    plt.tick_params(axis='y',labelsize=size_f)
    plt.ylabel(r'$p(t_{esc})$', fontsize=size_f)
    plt.xlabel(r'$t_{esc} \  [sec]$', fontsize=size_f)
    
    #plt.savefig(r'C:\Users\nikos.000\vlahos\png\escape distr_elec.png', format='png',dpi=300)#,bbox_inches='tight')
    #plt.savefig(r'C:\Users\nikos.000\vlahos\eps\escape_distr_elec.eps', format='eps',dpi=300)#,bbox_inches='tight')
  #### Set tick size ####
    labels = [r'$10^{-2}$', r'$10^{-1}$',r'$10^{0}$',r'$10^{1}$',r'$10^{2}$', r'$10^{3}$']#,r'$10^{2}$',r'$10^{4}$']
    x      =  [1e-2,1e-1,1e0,1e1,1e2,1e3]
    plt.tick_params(axis='x',labelsize=size_f)
    plt.tick_params(axis='y',labelsize=size_f)
    plt.xticks(x, labels)
    labels1 = [r'$10^{-6}$', r'$10^{-4}$', r'$10^{-2}$']
    y      =  [1e-6,1e-4, 1e-2,]
    
    plt.yticks(y, labels1)

    
    if legs:        
        leg_entries = tuple(legs.properties.String)
        py_locs = ['upper center','lower center','right','left','upper right','upper left','lower right','lower left','best']
        MAT_locs=['north','south','east','west','northeast', 'northwest', 'southeast', 'southwest','best']
        Mat2py = dict(zip(MAT_locs,py_locs))
        location = legs.properties.Location
        leg1=legend(leg_entries,loc=Mat2py[location],frameon=False,fontsize=size_f)
        leg1.legendHandles[1].set_color('black')
        #plt.xticks(fontsize=18 )
        #plt.yticks(fontsize=18)
        #### Save figure ####
   

    plt.savefig(r'C:\Users\nikos.000\vlahos\png\escape distr_prot.png', format='png',dpi=300,bbox_inches='tight')
    plt.savefig(r'C:\Users\nikos.000\vlahos\eps\escape_distr_prot.eps', format='eps',dpi=300,bbox_inches='tight')
     
    
    show()
    return 




plotFig(r'C:\Users\nikos.000\neutrons\f5b P=1.fig',fignr=1)

This is how the figure looks:

The original .fig file can be found here:

https://www.dropbox.com/sh/iddxpfvxz85abci/AAAU9p0DM5OYtpI7mE-nLAuga?dl=0