Changes

* Manually created the relax_disp user functions. This is equivalent to [https://gna.org/users/semor Seb's ] commit for the prompt.relax_disp module. The equivalent changes to the user_functions.relax_disp were hand edited. Added functions to select the experiment type and mathematical model used. These functions allow the user to select the experiment type (cpmg or r1rho) as well as the mathematical model to fit the data (fast or slow).

* Activated Monte Carlo simulations for the relaxation dispersion analysis. This required a bit of work. The key parts were renaming _block_loop() to the API method model_loop() as that is exactly what the model_loop() method is supposed to do, converting a bunch of API common spin-based methods to handle dispersion clustering, and to modify existing methods from [https://gna.org/users/semor Seb's ] original branch to handle the base_data_loop() method. The following methods have been added or modified. _back_calc(): This method has been modified to handle clustering and the returning of peak intensities from only one exponential curve. _exp_curve_index_from_key(): This new method is used to convert exponential curve key into the corresponding index. _intensity_key(): This new method is for converting an exponential curve key and relaxation time into the corresponding intensity key. create_mc_data(): This method is now functional and handles the data from the base_data_loop() method. return_error(): This method now handles the data from the base_data_loop() method. set_selected_sim(): This new method has been modified from the common _set_selected_sim_spin() method but modified for the model_loop() method. sim_pack_data(): This method now handles the data from the base_data_loop() method. sim_return_param(): This new method has been modified from the common _sim_return_param_spin() method to suit the model_loop(). sim_return_selected(): This new method has been modified from the common _sim_return_selected_spin() method again to suit the model_loop().