relax SVN archive

The structure.pca user function now creates graphs of the PC projections.

This includes PC1 vs. PC2, PC2 vs. PC3, etc.

Modified the assemble_structural_coordinates() method to return more information.

This is from the pipe_control.structure.main module. The 'lists' boolean argument is now accepted
which will cause the function to additionally return the object ID list per molecule, the model
number list per molecule, and the molecule name list per molecule.

Added the 'format' and 'dir' arguments to the structure.pca user function.

This is to the front and back ends.

The PCA values and vectors, and the per structure projections are now being stored.

This is in the structure.pca user function backend in the pipe_control.structure.main module.

The PCA analysis function in the relax library is now returning data.

This includes the PCA values and vectors, and the per structure projections.

The PCA analysis in the relax library now calculates the per structure projections along the PCs.

Implemented the SVD algorithm for the PCA analysis in the relax library.

This simply calls numpy.linalg.svd().

Added the 'algorithm' and 'num_modes' arguments to the structure.pca user function.

These are passed all the way into the relax library backend.

Partial implemented of the PCA analysis in the relax library.

This is for the new structure.pca user function. The lib.structure.pca module has been created, and
the pca_analysis() function created to calculate the structure covariance matrix, via the
covariance() function, and then calculate the eigenvalues and eigenvectors of the covariance matrix,
sorting them and truncating to the desired number of PCA modes.

Basic implementation of the structure.pca user function back end.

This is the new pca() function of the pipe_control.structure.main module. It simply performs some
checks, assembles the atomic coordinates, and the passes control to the relax library pca_analysis()
function of the currently unimplemented lib.structure.pca module.