relax SVN archive

Fix for the Frame_order.test_cam_double_rotor_large_angle* system tests.

The system test script was pointing to the wrong data directory.

The second torsion angle is now printed out for the frame order system tests.

This is in the system test class mesg_opt_debug() method and allows for better debugging of the
double rotor models.

Attempt at implementing the 2nd degree frame order matrix for the double rotor model.

This is required for the RDC.

Added proper support for the double rotor frame order models to the system test scripts.

This is for the CaM synthetic data. The base script can now handle the current parameterisation of
the double rotor model with a single pivot, an eigenframe, and the second pivot defined by a
displacement along the z-axis. The scripts for the double_rotor and double_rotor_large_angle data
sets have been changed to use this parameterisation as well.

Small fix for the large angle CaM double rotor frame order model synthetic test data.

The way the rotation angle was calculated was slightly out due to integer truncation. The integers
are now converted to floats in the generate_distribution.py script and all of the PCS and RDC data
averaged over ~20 million states has been recalculated.

Added matrix_power to the init file in lib/dispersion.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

First try to implement function that will calculate the matrix exponential by striding through data.

Interestingly, it does not work. Theses systemtests will fail.
test_hansen_cpmg_data_to_ns_cpmg_2site_3D
test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

Initiated lengthy profiling script, that shows that doing square numpy matrix_power on strided data, can speed up the calculation by factor 1.5.

The profiling script can quicly be turned into a unit test, and includes small helper functions to calculate how to stride through the data.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

Implemented a dependency check for numpy einsum, so relax can still start.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

Added the full optimisation results for the 2nd free rotor isotropic cone frame order model.

This is for the CaM test data using the new frame_order.py optimisation script.