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Posted by edward on August 25, 2014 - 17:57:
Author: bugman
Date: Mon Aug 25 17:57:22 2014
New Revision: 25252

URL: http://svn.gna.org/viewcvs/relax?rev=25252&view=rev
Log:
Merged revisions 25214-25221,25223-25229 via svnmerge from 
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/trunk

........
  r25214 | tlinnet | 2014-08-22 14:48:11 +0200 (Fri, 22 Aug 2014) | 21 lines
  
  Modified following functions:
  
  Time points are now saved at the [ei][mi][oi][di] index level.
  At this index Ãlevelall time points are saved for the R2eff point.
  
  - interpolate_disp()
  To interpolate time points, all time points through the original dispersion 
points di, are
  collected and then made unique. This time list can potentially be the 
largest of all time lists.
  
  - interpolate_offset()
  To interpolate time points, all time points through the original offset 
points, and then dispersion points di, are
  collected and then made unique. This time list can potentially be the 
largest of all time lists.
  
  - plot_disp_curves_to_file()
  To acquire the original relax_times points.
  
  - return_r2eff_arrays()
  To save all time points on the level of [ei][mi][oi][di].
  At this index level, it will be a numpy array list with all time values 
used for fitting.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25215 | tlinnet | 2014-08-22 14:48:18 +0200 (Fri, 22 Aug 2014) | 3 lines
  
  Modified back_calc_r2eff() to accept interpolated timepoints.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25216 | tlinnet | 2014-08-22 14:48:19 +0200 (Fri, 22 Aug 2014) | 3 lines
  
  Modified target function of relax disp, to use the the new list of time 
points, which are of higher dimension.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25217 | tlinnet | 2014-08-22 14:48:21 +0200 (Fri, 22 Aug 2014) | 8 lines
  
  Fix to systemtest Relax_disp.test_r1rho_kjaergaard_missing_r1()
  
  After the relaxation times have been fixed, this model now return 
reasonable chi2 values.
  
  The reported parameters are though quite different from all other models, 
and it seems something may
  still be wrong.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25218 | tlinnet | 2014-08-22 14:53:25 +0200 (Fri, 22 Aug 2014) | 3 lines
  
  Fix for time not extracted for CPMG experiments in target_function-
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25219 | tlinnet | 2014-08-22 15:22:36 +0200 (Fri, 22 Aug 2014) | 3 lines
  
  Fix for interpolating time points, when producing xmgrace files for CPMG 
experiments.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25220 | tlinnet | 2014-08-22 15:22:38 +0200 (Fri, 22 Aug 2014) | 5 lines
  
  Fix for systemtest Relax_disp.test_exp_fit(), where the spin.isotope was 
not set.
  
  The new call to return_r2eff_arrays(), when producing graphs, raise 
RelaxSpinTypeError() if no isotope is set.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25221 | bugman | 2014-08-22 15:50:08 +0200 (Fri, 22 Aug 2014) | 5 lines
  
  Modified the Relax_disp.test_r1rho_kjaergaard_missing_r1 system test to 
pass on 64-bit Linux systems.
  
  The accuracy of the checks of the optimised values have been decreased.
........
  r25223 | tlinnet | 2014-08-22 16:27:19 +0200 (Fri, 22 Aug 2014) | 3 lines
  
  Moved the storing of relax time up before check of missing data in 
return_r2eff_arrays().
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25224 | tlinnet | 2014-08-22 16:27:23 +0200 (Fri, 22 Aug 2014) | 3 lines
  
  Fix for systemtest not adding spin.isotope to setup information.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25225 | tlinnet | 2014-08-22 16:27:25 +0200 (Fri, 22 Aug 2014) | 3 lines
  
  Fix for looping over data indices, where tilt_angles has the si index.
  
  bug #22461(https://gna.org/bugs/?22461): NS R1rho 2-site_fit_r1 has 
extremely high chi2 value in systemtest 
Relax_disp.test_r1rho_kjaergaard_missing_r1.
........
  r25226 | bugman | 2014-08-22 19:00:56 +0200 (Fri, 22 Aug 2014) | 6 lines
  
  Added Nikolai's original Matlab code to the lib.dispersion.ns_r1rho_2site 
module docstring.
  
  This is the code taken directly form the original funNumrho.m file, which 
was the origin of the code
  in this module.
........
  r25227 | tlinnet | 2014-08-22 19:17:19 +0200 (Fri, 22 Aug 2014) | 7 lines
  
  Further extended the profiling script for curve fitting.
  
  Now profiling is in place for the implemented C code method in relax.
  
  A similar code should now be devised for numpy array for comparing.
  
  But this profiling shows that when contraints=True, is slowing down this 
procedure by a factor 10 X !
........
  r25228 | tlinnet | 2014-08-25 01:08:44 +0200 (Mon, 25 Aug 2014) | 12 lines
  
  Further improved the profiling of relax curve fit.
  
  This profiling shows, that Python code is about twice as slow as the C code 
implemented.
  
  But it also shows that optimising with scipy.optimize.leastsq is 20 X 
faster.
  It also gives reasonable error values.
  
  Combining a function for a linear fit to guess the initial values, together
  with scipy optimise, will be an extreme time win for estimating R2eff 
values fast.
  
  A further test would be to use relax Monte-Carlo simulations for say 
1000-2000 iterations,
  and compare to the errors extracted from estimated covariance.
........
  r25229 | tlinnet | 2014-08-25 01:08:46 +0200 (Mon, 25 Aug 2014) | 31 lines
  
  Added verification script, that shows that using scipy.optimize.leastsq 
reaches the exact same parameters as minfx for exponential curve fitting.
  
  The profiling shows that scipy.optimize.leastsq is 10X as fast as using 
minfx (with no linear constraints.)
  scipy.optimize.leastsq is a wrapper around wrapper around MINPACK's lmdif 
and lmder algorithms.
  
  MINPACK is a FORTRAN90 library which solves systems of nonlinear equations, 
or carries out the least squares minimization of the residual of a set of 
linear or nonlinear equations.
  
  The verification script also shows, that a very heavy and time consuming 
monte carlo simulation of 2000 steps, reaches the same
  errors as the errors reported by scipy.optimize.leastsq.
  
  The return from scipy.optimize.leastsq, gives the estimated co-variance.
  Taking the square root of the co-variance corresponds with 2X error 
reported by minfx.
  
  This could be an extremely time saving step, when performing model fitting 
in R1rho, where
  the errors of the R2eff values, are estimited by Monte-Carlo simulations.
  
  The following setup illustrates the problem.
  This was analysed on a: MacBook Pro, 13-inch, Late 2011.
  Witn no multi-core setup.
  
  Script running is:
  test_suite/shared_data/dispersion/Kjaergaard_et_al_2013/2_pre_run_r2eff.py
  
  This script analyses just the R2eff values for 15 residues.
  It estimates the errors of R2eff based on 2000 Monte Carlo simulations.
  For each residues, there is 14 exponential graphs.
  
  The script was broken after 35 simulations.
  This was measured to 20 minutes.
  So 500 simulations would take about 4.8 Hours.
  The R2eff values and errors can by scipy.optimize.leastsq can instead be 
calculated in: 15 residues * 0.02 seconds = 0.3 seconds.
........

Added:
    
branches/frame_order_cleanup/test_suite/shared_data/curve_fitting/profiling/relax_fit.py
      - copied unchanged from r25229, 
trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py
    
branches/frame_order_cleanup/test_suite/shared_data/curve_fitting/profiling/verify_error.py
      - copied unchanged from r25229, 
trunk/test_suite/shared_data/curve_fitting/profiling/verify_error.py
Modified:
    branches/frame_order_cleanup/   (props changed)
    branches/frame_order_cleanup/lib/dispersion/ns_r1rho_2site.py
    branches/frame_order_cleanup/specific_analyses/relax_disp/data.py
    branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py
    branches/frame_order_cleanup/target_functions/relax_disp.py
    
branches/frame_order_cleanup/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py
    branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py
    
branches/frame_order_cleanup/test_suite/system_tests/scripts/relax_disp/exp_fit.py
    
branches/frame_order_cleanup/test_suite/system_tests/scripts/relax_disp/r2eff_calc.py

[This mail would be too long, it was shortened to contain the URLs only.]

Modified: branches/frame_order_cleanup/lib/dispersion/ns_r1rho_2site.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/lib/dispersion/ns_r1rho_2site.py?rev=25252&r1=25251&r2=25252&view=diff

Modified: branches/frame_order_cleanup/specific_analyses/relax_disp/data.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/specific_analyses/relax_disp/data.py?rev=25252&r1=25251&r2=25252&view=diff

Modified: 
branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py?rev=25252&r1=25251&r2=25252&view=diff

Modified: branches/frame_order_cleanup/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/target_functions/relax_disp.py?rev=25252&r1=25251&r2=25252&view=diff

Modified: 
branches/frame_order_cleanup/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py?rev=25252&r1=25251&r2=25252&view=diff

Modified: branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py?rev=25252&r1=25251&r2=25252&view=diff

Modified: 
branches/frame_order_cleanup/test_suite/system_tests/scripts/relax_disp/exp_fit.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/test_suite/system_tests/scripts/relax_disp/exp_fit.py?rev=25252&r1=25251&r2=25252&view=diff

Modified: 
branches/frame_order_cleanup/test_suite/system_tests/scripts/relax_disp/r2eff_calc.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/test_suite/system_tests/scripts/relax_disp/r2eff_calc.py?rev=25252&r1=25251&r2=25252&view=diff




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