code: def splot(axes="gca", smoothing=5000, degree=5, presmoothing=0, plot=True, spline_class=spline_single, interactive=True, show_derivative=1):
      
  
      if   axes=="gca": axes = _pylab.gca()
  
      xlabel = axes.xaxis.label.get_text()
      ylabel = axes.yaxis.label.get_text()
      
      xdata = axes.get_lines()[0].get_xdata()
      ydata = axes.get_lines()[0].get_ydata()
  
      if interactive:
          return splinteractive(xdata, ydata, smoothing, degree, presmoothing, spline_class, xlabel, ylabel)
      else:
          return spline_class(xdata, ydata, smoothing, degree, presmoothing, plot, xlabel, ylabel)
docs: gets the data from the plot and feeds it into splint
      returns an instance of spline_single
  
      axes="gca"                  which axes to get the data from.
      smoothing=5000              spline_single smoothing parameter
      presmoothing=0              spline_single data presmoothing factor (nearest neighbor)
      plot=True                   should we plot the result?
      spline_class=spline_single  which data class to use?
      interactive=False           should we spline fit interactively or just make a spline_single?