relax SVN archive

Bug fix for the lib.frame_order.pseudo_ellipse.tmax_pseudo_ellipse_array() function.

The problem was that when theta_x or theta_y were zero, the floating point value of 0.0 would be
returned. This is the incorrect behaviour as the returned value must be an array matching the
dimensions of the phi angle array argument.

Created the Frame_order.test_pseudo_ellipse_zero_cone_angle system test.

This is to catch for a bug in optimisation when the cone_theta_x is set to zero in the
pseudo-ellipse models.

Fix for the RelaxError raised by the frame_order.select_model user function.

This is the error if the model name is incorrect.

Fix for the axis permutation protocol in the frame order auto-analysis.

If a results file was found for one of the permutations, a return from the function would occur.
The result is that the other permutations would not be loaded or optimised.

Modified the pivot position checking in specific_analyses.frame_order.data.generate_pivot().

Now the pivot is shifted to be within the limits shrunk by 100 Angstrom. This allows any PDB
representation created by the frame_order.pdb_model user function to be within the PDB limits.

Modified the Frame_order.test_frame_order_pdb_model_failed_pivot system test.

This is to show that the frame_order.pdb_model user function fails if the pivot is close to but
still within the PDB coordinate limits.

Further improved the plotting of data in repeated analysis.

Task #7826 (https://gna.org/task/index.php?7826): Write an python class for the repeated analysis of dispersion data.

Implemented a correlation plot for R2eff values to be plotted for different pipes. This has the R2eff/R2eff_err plotted, which is the best way to represent this data.

Task #7826 (https://gna.org/task/index.php?7826): Write an python class for the repeated analysis of dispersion data.

Fix for a bug introduced in the auto analysis of relax_fit.

A variable was called, before it was set.

Improved the plotting of correlation plot for intensity. Now the intensity to error is plotted, which is the correct measure of this data.

Task #7826 (https://gna.org/task/index.php?7826): Write an python class for the repeated analysis of dispersion data.