Optimisation for this analysis is not needed as this is a direct calculation. Therefore the J(ω) values are simply calculated with the call:
[firstnumber=31] # Reduced spectral density mapping. minimise.calculate()
The propagation of errors is more complicated. The Monte Carlo simulation framework of relax can be used to propagate the relaxation data errors to the spectral density errors. As this is a direct calculation, this collapses into the standard bootstrapping method. The normal Monte Carlo user functions can be called:
[firstnumber=34] # Monte Carlo simulations (well, bootstrapping as this is a calculation and not a fit!). monte_carlo.setup(number=500) monte_carlo.create_data() minimise.calculate() monte_carlo.error_analysis()
In this case, the monte_carlo.initial_values user function call is not required.