The numerical derivative is computed as the numerical differential of the mu(E) spectrum divided by the numerical differential of the energy array. Smoothing happens as explained above. Justw atch the lines that get printed to the buffer when you click the plot buttons. - B. Ravel
I wonder if that's the right way to go for data that, for instance, might have gaps or changes in step size. What I do in my code is run a cubic spline through the data, with the abscissa as is, then take the derivative of that spline. Thus, if the data is smooth enough to be locally approximated by a cubic, the derivative will come out smooth regardless of how it's tabulated. I'm not sure that's the case with Bruce's algorithm. Is the 'numerical differential' the difference E(i+1)-E(i) or (1/2)*(E(i+1)-E(i-1)) or some form that's intended to approximate dE(i)/di (i= point index)? It's not clear to me whether it's any more correct to do smoothing before or after differentiating. You can take the red pill or the blue pill :-) mam