docs: def abu_profile(self,ixaxis='mass',isos=None,ifig=None,fname=None,logy=False,
                      colourblind=False):
          '''
          Plot common abundances as a function of either mass coordiate or radius.
  
          Parameters
          ----------
          ixaxis : string, optional
              'mass',  'logradius' or 'radius'
              The default value is 'mass'
          isos : list, optional
              list of isos to plot, i.e. ['h1','he4','c12'] for MESA or
              ['H-1','He-4','C-12'] for SE output. If None, the code decides
              itself what to plot.
              The default is None.
          ifig : integer or string, optional
              The figure label
              The default value is None
          fname : integer, optional
              What cycle to plot from (if SE output)
              The default value is None
          logy : boolean, optional
              Should y-axis be logarithmic?
              The default value is False
          colourblind : boolean, optional
              do you want to use the colourblind colour palette from the NuGrid
              nuutils module?
          '''
  
          pT=self._classTest()
          # Class-specific things:
          if pT is 'mesa_profile':
              x = self.get(ixaxis)
              if ixaxis is 'radius':
                  x = x*ast.rsun_cm
              if isos is None:
                  isos=['h1','he4','c12','c13','n14','o16','ne20','ne22','mg24','mg25',
                        'al26','si28','si30','s32','s34','cl35','ar36','ar38','cr52',
                        'cr56','fe56','ni56']
              risos=[i for i in isos if i in self.cols]
              abunds = [self.get(riso) for riso in risos]
              names=risos
          elif pT is 'se':
              if fname is None:
                  raise IOError("Please provide the cycle number fname")
              x = self.se.get(fname,ixaxis)
              if isos is None:
                  isos=['H-1','He-4','C-12','C-13','N-14','O-16','Ne-20','Ne-22','Mg-24','Mg-25',
                        'Sl-26','Si-28','Si-30','S-32','S-34','Cl-35','Ar-36','Ar-38','Cr-52',
                        'Cr-56','Fe-56','Ni-56']
              risos=[i for i in isos if i in self.se.isotopes]
              abunds = self.se.get(fname,'iso_massf',risos)
              names=risos
          else:
              raise IOError("Sorry. the density_profile method is not available \
                            for this class")
  
          # Plot-specific things:
          if ixaxis is 'logradius':
              x = np.log10(x)
              xlab='$\log_{10}(r\,/\,{\\rm cm})$'
          elif ixaxis is 'radius':
              x = old_div(x, 1.e8)
              xlab = 'r / Mm'
          else:
              xlab='${\\rm Mass}\,/\,M_\odot$'
  
          if ifig is not None:
              pl.figure(ifig)
          from . import utils as u
          cb = u.colourblind
          lscb = u.linestylecb # colourblind linestyle function
          for i in range(len(risos)):
              if logy:
                  y = np.log10(abunds if len(risos) < 2 else abunds[i])
              else:
                  y = abunds if len(risos) < 2 else abunds[i]
              if colourblind:
                  pl.plot(x,y,ls=lscb(i)[0],marker=lscb(i)[1],
                          color=lscb(i)[2],markevery=u.linestyle(i)[1]*20,
                          label=names[i],mec='None')
              else:
                  pl.plot(x,y,u.linestyle(i)[0],markevery=u.linestyle(i)[1]*20,
                          label=names[i],mec='None')
  
          pl.legend(loc='best').draw_frame(False)
          pl.xlabel(xlab)
          pl.ylabel('$\log(X)$')