relax SVN archive

Replaced target function for model IT99, to use higher dimensional numpy array structures.

That makes the model much faster.

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

Fix for sending in r20 and dw as numpy array in unit tests of IT99.

This is after using masks as replacement.

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

Methods to replace math domain errors in model IT99, has been replaced with numpy masks.

number of points has been removed, as the masks utility replaces this.
pB is now moved to be calculated inside. This makes the lib function simpler.

Documentation is also fixed.

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

Added another timing script for RDC and PCS calculation timings.

This time, the calculation for multiple alignments is now being timed. An addition set of methods
for calculating the values via tensor projections have been added. For 5 alignments and 200
vectors, this demonstrates a potential 20x speed up for this part of the RDC/PCS calculation. Most
of this speed up should be obtainable for the numerical PCS integration in the frame order models.

Added a script for timing different ways to calculate PCSs and RDCs for multiple vectors.

This uses the timeit module rather than profile to demonstrate the speed of 7 different ways to
calculate the RDCs or PCSs for an array of vectors using numpy. In the frame order analysis, this
is the bottleneck for the quasi-random numerical integration of the PCS.

The log file shows a potential 1 order of magnitude speed up between the 1st technique, which is
currently used in the frame order analysis, and the 7th and last technique. The first technique
loops over each vector, calculating the PCS. The last expands the PCS/RDC equation of the
projection of the vector into the alignment tensor, and calculates all PCSs simultaneously.

1 digit decrease in parameter check in systemtest: Relax_disp.test_hansen_cpmg_data_to_lm63.

It is unknown, why this has occured.

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

Fix for sending in r20 and phi_ex as numpy array in unit tests of LM63.

This is after using masks as replacement.

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

Fix for replacement of values with mask, when phi_ex is zero.

This can be spin specific.
Systemtest: Relax_disp.test_hansen_cpmg_data_to_lm63 starts to fail:

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

Replaced target function for model LM63, to use higher dimensional numpy array structures.

That makes the model much faster.

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

Fix for sending in number of points in unit tests of model LM63.

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

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