relax SVN archive

Updated the Frame_order.test_auto_analysis system test script.

This now uses the new auto-analysis Optimisation_settings object design.

Created the sobol_setup() method for the frame order auto-analysis.

This is used to correctly handle the new design of the frame_order.sobol_setup user function
consistently throughout the protocol.

Fix for the rigid frame order model for the recent frame_order.sobol_setup user function changes.

For this model, the number of Sobol' points normally is does not exist. This is now correctly
handled.

Converted the frame order auto-analysis to use the new frame_order.sobol_setup user function design.

The auto-analysis Optimisation_settings object has also been modified so that all num_int_pts
arguments and internal structures have been split into the two new sobol_max_points and
sobol_oversample names and objects.

Changed the default oversampling factor from 100 to 1 in the frame_order.sobol_setup user function.

Updated all the lib.frame_order.*.pcs_numeric_int_*() functions for the new Sobol' point algorithm.

The functions now all accept the max_points argument and terminate the loop over the Sobol' points
once the maximum number of points has been reached. The calls to numpy.swapaxes() have also been
removed as this is now pre-performed by the target function initialisation.

Updated the frame order count_sobol_points() function to use the new Sobol_data container.

The Sobol' sequence data generated by the target function is now located at
target_functions.frame_order.sobol_data.

Huge speed up for the generation of the Sobol' sequence data in the frame order target function.

The new Sobol_data class has been created and is instantiated in the module namespace as
target_function.frame_order.sobol_data. This is used to store all of the Sobol' sequence associated
data, including the torsion-tilt angles and all corresponding rotation matrices. When initialising
the target function, if the Sobol_data container holds the data for the same model and same total
number of Sobol' points, then the pre-existing data will be used rather than regenerating all the
data. This can save a huge amount of time.

Updated the frame order count_sobol_points() function to handle the swapped axis order.

Changed the creation of the Sobol' points in the frame order target function.

For increased accuracy of the numerical PCS integration, the first 1000 points of the Sobol'
sequence are now skipped to avoid any bias. For speed, the axis order of the Sobol' torsion-tilt
angles has been swapped so that the numpy.swapaxes() function call is no longer required in the
lib.frame_order.*.pcs_numeric_int_*() functions.