relax SVN archive

Reverted r24336 as relax dependency of numpy is now 1.6 where the "einsum" function is available.

The command used was:
svn merge -r24336:r24335 .

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r24336 | tlinnet | 2014-06-27 12:58:22 +0200 (Fri, 27 Jun 2014) | 3 lines

Added to target function that experiment_type_setup() should not be initiated, if numpy.einsum is missing.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.
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Reverted r24339 as relax dependency of numpy is now 1.6 where the "out" argument is available.

The command used was:
svn merge -r24339:r24338 .

.....
r24339 | tlinnet | 2014-06-27 12:58:29 +0200 (Fri, 27 Jun 2014) | 3 lines

Added a list of systemtests to skip, if numpy "out" argument is not available.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.
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Removed some excess empty lines in specific_analyses.api.

Import fix for the N-state model parameter object in the specific API return_parameter_object() function.

Updated the NOE analysis to handle the changes for the minimise.calculate user function.

This now requires the model_loop() and get_param_names() API methods to be implemented. The first
is provided by the API common _model_loop_spin() method and the second simply returns a list of the
single 'noe' parameter.

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.