def splot(axes="<STR_LIT>", smoothing=<NUM_LIT>, degree=<NUM_LIT:5>, presmoothing=<NUM_LIT:0>, plot=True, spline_class=spline_single, interactive=True, show_derivative=<NUM_LIT:1>):
if   axes=="<STR_LIT>": axes = _pylab.gca()<EOL>xlabel = axes.xaxis.label.get_text()<EOL>ylabel = axes.yaxis.label.get_text()<EOL>xdata = axes.get_lines()[<NUM_LIT:0>].get_xdata()<EOL>ydata = axes.get_lines()[<NUM_LIT:0>].get_ydata()<EOL>if interactive:<EOL><INDENT>return splinteractive(xdata, ydata, smoothing, degree, presmoothing, spline_class, xlabel, ylabel)<EOL><DEDENT>else:<EOL><INDENT>return spline_class(xdata, ydata, smoothing, degree, presmoothing, plot, xlabel, ylabel)<EOL><DEDENT>
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?