relax SVN archive

Made a summarize function to compare results.

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

Added a unit test for the new lib.statistics.geometric_std() function.

Addition of the file which should have been committed in the last commit (r27863).

Created a simple unit test for the new lib.statistics.geometric_mean() function.

Removed some rubbish text from the new lib.statistics.geometric_*() function docstrings.

Added functions for calculating the geometric mean and standard deviation to the relax library.

These are the geometric_mean() and geometric_std() functions of the lib.statistics module. The
implementation is designed to be fast, using numpy array arithmetic rather than Python loops.

Huge speed up for the Monte Carlo simulations in the N-state model analyses.

This speed up is also for Bootstrap simulations and the frame order analysis. The change affects
the monte_carlo.initial_values user function. The alignment tensor _update_object() method was very
inefficient when updating the Monte Carlo simulation data structures. For each simulation, each of
the alignment tensor data structures were being updated for all simulations. Now only the current
simulations is being updated. This speeds up the user function by many orders of magnitude.

Silenced a warning in the N-state model optimisation if the verbosity is set to zero.

This removes a repetitive warning from the Monte Carlo or Bootstrap simulations.

Removed some accidentally committed debugging printouts.

Added simulation support for the RDC and PCS Q factors in the N-state model analysis.

This is for both Monte Carlo and Bootstrap simulation. The simulation RDC and PCS values, as well
as the simulation back calculated values are now stored via the minimise_bc_data() function of
specific_analyses.n_state_model.optimisation in the respective spin or interatomic data containers.
The analysis specific API methods now send the sim_index value into minimise_bc_data(), as well as
the pipe_control.rdc.q_factors() and pipe_control.pcs.q_factors() functions.