relax SVN archive

relax version 1.3.0.

This is the first release of the 1.3 development line. In addition to all the capabilities of relax
1.2.10 the new features of this release include the addition of a unit test framework, preliminary
support for PyMOL, the creation of PDB files, the ability to display the diffusion tensor encoded as
a PDB file using PyMOL, the ability to display the distribution of XH bond vectors used in the
analysis via a PDB file, the new user function class 'structure' containing the old user function
'pdb()' which has been split and redesigned, removal of apply(func, args) calls from the
minimisation code, improved spin system selection using Boolean operators, and a few other small
features, bugfixes, and program changes. As the user function names have been and will continue to
be modified please do not expect either the backwards or forwards compatibility of relax scripts
written for the 1.3 relax versions.

Modified the unit test runner to return True if the tests pass and Fail if they fail.

Removed Gary's dummy functions to allow the unit test and test suite to pass.

Bug fix. Fixed a typo committed in the last revision.

Renamed the function 'self._update_object()' to the private function 'self.__update_object()'.

Fix for bug #7979 (https://gna.org/bugs/?7979).

A large number of changes were required. Two private functions 'self.__update_sim_append()' and
'self.__update_sim_set()' have been added to the DiffTensorElement class. These are used to
automatically update the Monte Carlo simulation parameter lists.

The name 'dependencies' is now properly spelt.

The unused Monte Carlo simulation code in the function 'self._update_object()' has been deleted.

The object DiffTensorSimList has been modifed to handle the two new private functions.

Modifications to the DiffTensorSimList object.

The self.__setitem__() function now sets the value and the parent DiffTensorElement is now passed
into the DiffTensorSimList object.

Created the generator function 'dependency_generator()'.

This generator is for looping over the list of target parameters to update when a parameter is set.
It replaces all the self._update_object() calls and simplifies the code. It will also be used for
updating the Monte Carlo simulation data structures.

Modified the diffusion tensor data structure unit test for setting the tm parameter.

Now the spherical diffusion tensor type is initially set.

Small changes to the 'DiffTensorSimList' object.