relax SVN archive

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.

Added Monte Carlo and Bootstrap simulation support for the RDC and PCS Q factor calculations.

The pipe_control.rdc.q_factors() and pipe_control.pcs.q_factors() functions have been modified to
support Monte Carlo and Bootstrap simulations. The sim_index argument has been added to allow the Q
factor for the given simulation number to be calculated. All of the Q factor data structures in the
base data pipe now have *_sim equivalents for permanently storing the simulation values. For the
simulation values, all the warnings have been silenced.

Added a missing call to monte_carlo.initial_values in the N_state_model.test_absolute_T system test.

This fixes the commit of r27854, showing that there is not a problem with the Monte Carlo simulations.

Added Monte Carlo simulations to the N_state_model.test_absolute_T system test.

This is to demonstrate a failure of the simulations in certain N-state model setups.

Added 'NMR dynamics' as a meta keyword for all of http://www.nmr-relax.com/ .

Added sample data and analysis script, that will eventually show that there is not much differentce in the sample statistics used for comparing the output of two
very similar datasets.

This is a multiple comparison test with many t tests at once, where the familywise error is controlled by the Holm method.
Even if the values are very equal, and within the standard deviation, this procedure will reject up to 20% of the null hypothesis.

This is not deemed as a suitable method.

Bug #23644 /https://gna.org/bugs/?23644): monte_carlo.error_analysis() does not update the mean value/expectation value from simulations.