relax SVN archive

Small speed up for all of the frame order models.

The PCS averaging in the quasi-random numerical integration functions now uses the multiply() and
divide() numpy methods to eliminate a loop over the alignments. For this, a new dimension over the
spins was added to the PCS constant calculated in the target function __init__() method. In one
test of the pseudo-ellipse, the time dropped from 191 seconds to 172.

Replaced target function for model ns_cpmg_2site_expanded, to use higher dimensional numpy array structures.

That makes the model much faster.

I cannot get system test: Relax_disp.test_cpmg_synthetic_dx_map_points
to pass.

-------
File "/Users/tlinnet/software/disp_spin_speed/test_suite/system_tests/relax_disp.py", line 1671, in test_cpmg_synthetic_dx_map_points
self.assertEqual(res_file[i], lines[i])
AssertionError: '0.76981 3.9169 0.41353 1\n' != '0.0098838 1.4654 18.661 1\n'
-------

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 ns_cpmg_2site_expanded.

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 ns_cpmg_2site_expanded, 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.
k_AB and k_BA is also now calculated here.

Documentation is also fixed.

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

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.