relax SVN archive

Added profiling script for testing the lib/dispersion/cr72.py file.

This script creates the relax datastructures, and issues the call to the target function.

It was discussed in:
http://thread.gmane.org/gmane.science.nmr.relax.devel/6022.

--------

Checked on MacBook Pro
2.4 GHz Intel Core i5
8 GB 1067 Mhz DDR3 RAM.
Python Distribution -- Python 2.7.3 |EPD 7.3-2 (32-bit)|

Timing for:
2 fields
20 dispersion points
iterations of function call: 1000

Timed for simulating 1 or 100 clustered spins.

svn ls "^/tags"

For tag 3.2.2
svn switch ^/tags/3.2.2

1 spin:
ncalls tottime percall cumtime percall filename:lineno(function)
2000 0.168 0.000 0.198 0.000 cr72.py:100(r2eff_CR72)
1000 0.040 0.000 0.280 0.000 relax_disp.py:456(calc_CR72_chi2)
2000 0.028 0.000 0.039 0.000 chi2.py:32(chi2)

100 spins:
ncalls tottime percall cumtime percall filename:lineno(function)
200000 16.810 0.000 19.912 0.000 cr72.py:100(r2eff_CR72)
1000 4.185 0.004 28.518 0.029 relax_disp.py:456(calc_CR72_chi2)
200000 3.018 0.000 4.144 0.000 chi2.py:32(chi2)

For tag 3.2.1
svn switch ^/tags/3.2.1

1 spin:
ncalls tottime percall cumtime percall filename:lineno(function)
2000 0.696 0.000 0.697 0.000 cr72.py:98(r2eff_CR72)
1000 0.038 0.000 0.781 0.001 relax_disp.py:456(calc_CR72_chi2)
2000 0.031 0.000 0.043 0.000 chi2.py:32(chi2)

100 spins:
ncalls tottime percall cumtime percall filename:lineno(function)
200000 75.880 0.000 76.078 0.000 cr72.py:98(r2eff_CR72)
1000 4.201 0.004 85.519 0.086 relax_disp.py:456(calc_CR72_chi2)
200000 3.513 0.000 4.940 0.000 chi2.py:32(chi2)

Expanded the CaM isotropic cone test data frame_order.py optimisation script and added the results.

The optimisation is now implemented as in the auto-analysis, with an iterative increase in accuracy
of the quasi-random numerical integration together with an decrease of the function tolerance cutoff
for optimisation. The accuracy of the initial chi-squared calculation is now much higher. And the
accuracy of the initial grid search and the Monte Carlo simulations is now much lower.

relax version 3.2.2.

This is a major feature and bugfix release. This includes a large speed up of all analytic
relaxation dispersion models, the correct handling of edge case failures in all models of the
dispersion analysis, and a number of fixes for the handling of list-type data in the GUI user
function windows including the fatal GUI crashes on Mac OS X systems.

Merged revisions 23647 via svnmerge from
svn+ssh://bugman@.../svn/relax/trunk

........
r23647 | bugman | 2014-06-05 11:15:40 +0200 (Thu, 05 Jun 2014) | 7 lines

Fix for bug #22033, the inability to use other optimisation algorithms in the dispersion analysis.

This is reported at https://gna.org/bugs/?22033. As mentioned in comment #2, the solution is to
raise a RelaxError explaining that only 'simplex' optimisation is possible for the dispersion
analysis as the gradients are not derived and implemented in relax.
........

Fix for bug #22033, the inability to use other optimisation algorithms in the dispersion analysis.

This is reported at https://gna.org/bugs/?22033. As mentioned in comment #2, the solution is to
raise a RelaxError explaining that only 'simplex' optimisation is possible for the dispersion
analysis as the gradients are not derived and implemented in relax.

Updated the CaM frame order data generation base script to print out more information.

This is for the first axis system so that the same amount of information as the second system is
printed.

Added one more iteration for the zooming optimisation of the frame order auto-analysis.

This is to improve the speed of optimisation when all RDC and PCS data is being used. The previous
iterations where with [100, 1000, 200000] Sobol' integration points and [1e-2, 1e-3, 1e-4] function
tolerances. This has been increased to [100, 1000, 10000, 100000] and [1e-2, 1e-3, 5e-3, 1e-4].
The final number of points has been decreased as that level of accuracy does not appear to be
necessary. These are also only default values that the user can change for themselves.

Expanded the CaM pseudo-ellipse test data frame_order.py optimisation script.

The optimisation is now implemented as in the auto-analysis, with an iterative increase in accuracy
of the quasi-random numerical integration together with an decrease of the function tolerance cutoff
for optimisation. The accuracy of the initial chi-squared calculation is now much higher. And the
accuracy of the initial grid search and the Monte Carlo simulations is now much lower.

The results of the new optimisation are included.

Expanded the CaM rotor test data frame_order.py optimisation script.

The optimisation is now implemented as in the auto-analysis, with an iterative increase in accuracy
of the quasi-random numerical integration together with an decrease of the function tolerance cutoff
for optimisation. The accuracy of the initial chi-squared calculation is now much higher. And the
accuracy of the initial grid search and the Monte Carlo simulations is now much lower.

The results of the new optimisation are included.

Constraints are now implemented in the frame order grid search.

This is useful for the pseudo-elliptic models as the cone theta_x < theta_y constraint halves the
optimisation space.