relax SVN archive

Fixes for the relaxation curve-fitting grid search.

The parameters which are not set are no longer defaulting to 0.0. This means that the parameter
vector will sometimes contain NaN values, but this is important for the correct operation of the new
minimise.grid_search user function backend.

The minimise.grid_search user function can now properly handle preset values of NaN.

This occurs when the parameter vector contains values of None due to the parameter not being set and
then the Python list being converted to a numpy array. The value of NaN is now caught and the
parameter is no longer identified as being preset.

Updated the _print_model_title_spin() specific API common method.

This now accepts the prefix argument and adds this to the title.

Implemented the J(w) mapping analysis get_param_names() API method.

This simply returns the hardcoded list of 3 parameters of the model, and allows the
minimise.calculate user function to operate.

Converted the relaxation dispersion analysis to the new grid bounds and scaling factor design.

The parameter object now registers the grid bounds and scaling factors for all of the dispersion
parameters. This includes the functions dw_lower(), dwH_lower(), pA_lower() and i0_upper() in the
specific_analyses.relax_disp.parameter_object module for calculating some of these values.

The specific_analyses.relax_disp.parameters.assemble_scaling_matrix() function has been deleted as
this is now provided by the upstream code in pipe_control.minimise. And the API methods
grid_search() and minimise() has been modified to accept the list of scaling matrices.

As the grid bounds and increments are now handled by the upstream pipe_control.minimise.grid_setup()
function, the specific_analyses.relax_disp.optimisation.grid_search_setup() function was redundant
and was deleted.

The specific_analyses.relax_disp.parameters.get_param_names() function was also modified with the
full argument added, to allow either the base parameter names or an augmented form with the
dictionary key for presenting to the user to be returned.

Importantly to allow the changes to be operational, the model_loop() API method was redesigned so
that, for the R2eff base model, the individual spins rather than spin clusters will be looped over.
This allows the specific_analyses.relax_disp.optimisation.minimise_r2eff() function to continue to
operate correctly.

Fix for the skipping of preset parameters in the grid search.

Dictionary and list type parameters are now handled correctly.

Small change to the table printed out during the minimise.grid_search setup.

Increased the amount of user feedback for the minimise.grid_search user function.

Now a comment for each parameter is included in the printed grid search setup table. This includes
if the lower or upper bounds, or both, have been supplied by the user and if a preset value has been
used instead.

Major change to the grid search user function.

The minimise.grid_search user function now accepts the skip_preset flag. When True, the grid search
will skip any parameters with a preset value. This allows the user to set parameters via the
value.set user function and then have these parameters skipped in the grid search.

The new skip_preset argument is passed into the pipe_control.minimise.grid_setup() function in the
backend. This then sets both the grid lower and upper bounds to the preset parameter value and sets
the number of increments to 1 for that parameter so that it is essentially skipped in the grid
search.

Shifted the constraints boolean argument to the end of the grid_search() function argument list.