svn+ssh://bugman@.../svn/relax/trunk
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r25230 | tlinnet | 2014-08-25 01:08:48 +0200 (Mon, 25 Aug 2014) | 3 lines
Moved the target function for minimisation of exponential fit into the target functions folder.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25231 | tlinnet | 2014-08-25 01:08:50 +0200 (Mon, 25 Aug 2014) | 3 lines
Implemented initial systemtest Relax_disp.test_estimate_r2eff for setting up the new user function to estimate R2eff and errors by scipy.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25232 | tlinnet | 2014-08-25 01:08:53 +0200 (Mon, 25 Aug 2014) | 3 lines
Added front end user function relax_disp.r2eff_estimate() to estimate R2eff and errors by exponential curve fitting in scipy.optimize.leastsq.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25233 | tlinnet | 2014-08-25 01:08:55 +0200 (Mon, 25 Aug 2014) | 3 lines
Modified check for model, to accept model as input, for error printing.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25234 | tlinnet | 2014-08-25 01:08:57 +0200 (Mon, 25 Aug 2014) | 3 lines
Implemented back end for estimating r2eff and errors by exponential curve fitting with scipy.optimize.leastsq.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25235 | tlinnet | 2014-08-25 01:08:58 +0200 (Mon, 25 Aug 2014) | 5 lines
Documentation fix for new exponential target function.
Also added new function to estimate R2eff and i0 parameters, before minimisation.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25236 | tlinnet | 2014-08-25 01:09:00 +0200 (Mon, 25 Aug 2014) | 3 lines
Small changes to verification scripts, to use chi2 function and use the scaling matrix correct.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25237 | tlinnet | 2014-08-25 01:09:02 +0200 (Mon, 25 Aug 2014) | 6 lines
Split up of systemtest test_r1rho_kjaergaard_missing_r1, into a verification part.
This is to test the new r2eff estimation, which should get the parameter values, as a
this 2000 monto carlo simulation.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25238 | tlinnet | 2014-08-25 01:32:13 +0200 (Mon, 25 Aug 2014) | 56 lines
Modified systemtest Relax_disp.test_estimate_r2eff.
This is to compare against errors simulated with 2000 MC.
The paramaters are comparable, but not equal.
Mostly, it seems that the errors from scipy.optimize.leastsq, are twice as high than the Monte Carlo simulations.
This affect model fitting, and the calculated chi2 value.
Left column is 2000 Monte Carlo, right column is scipy.optimize.leastsq.
Optimised parameters for spin: 52V @N
Model: No Rex
Parameter: r1 Value: 1.46138806 - 1.46328102
Parameter: r2 Value: 11.48392438 - 11.48040934
Parameter: chi2 Value: 848.42015672 - 3363.95829122
Model: DPL94
Parameter: r1 Value: 1.44845743 - 1.45019848
Parameter: r2 Value: 10.15688373 - 10.16304892
Parameter: phi_ex Value: 0.07599563 - 0.07561937
Parameter: kex Value: 4460.43707304 - 4419.03906628
Parameter: chi2 Value: 179.47041255 - 710.24767560
Model: TP02
Parameter: r1 Value: 1.54354392 - 1.54352369
Parameter: r2 Value: 9.72654895 - 9.72772727
Parameter: pA Value: 0.88827039 - 0.88807488
Parameter: dw Value: 1.08875836 - 1.08765645
Parameter: kex Value: 4921.28597928 - 4904.70134941
Parameter: chi2 Value: 29.33882481 - 114.47142772
Model: TAP03
Parameter: r1 Value: 1.54356410 - 1.54354368
Parameter: r2 Value: 9.72641885 - 9.72759371
Parameter: pA Value: 0.88828925 - 0.88809317
Parameter: dw Value: 1.08837248 - 1.08726695
Parameter: kex Value: 4926.42974479 - 4909.86896567
Parameter: chi2 Value: 29.29050624 - 114.27987534
Model: MP05
Parameter: r1 Value: 1.54356415 - 1.54354372
Parameter: r2 Value: 9.72641730 - 9.72759220
Parameter: pA Value: 0.88828927 - 0.88809322
Parameter: dw Value: 1.08837250 - 1.08726707
Parameter: kex Value: 4926.44228958 - 4909.88128236
Parameter: chi2 Value: 29.29054252 - 114.28002272
Model: NS R1rho 2-site
Parameter: r1 Value: 1.41359226 - 1.41321968
Parameter: r2 Value: 9.34531364 - 9.34602793
Parameter: pA Value: 0.94504369 - 0.94496541
Parameter: dw Value: 1.56001843 - 1.55833321
Parameter: kex Value: 5628.66529504 - 5610.20221435
Parameter: chi2 Value: 34.44010458 - 134.14368365
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25239 | tlinnet | 2014-08-25 01:50:58 +0200 (Mon, 25 Aug 2014) | 47 lines
Added systemtest Relax_disp.test_estimate_r2eff_error().
This is to get insight in the error difference between 2000 monto carlo simulations and then scipy.optimize.leastsq.
R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 431.0.
r2eff=8.646/8.646 r2eff_err=0.0348/0.0692 i0=202664.191/202664.191 i0_err=699.6443/712.4201
R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 651.2.
r2eff=10.377/10.377 r2eff_err=0.0403/0.0810 i0=206049.558/206049.558 i0_err=776.4215/782.1833
R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 800.5.
r2eff=10.506/10.506 r2eff_err=0.0440/0.0853 i0=202586.332/202586.332 i0_err=763.9678/758.7052
R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 984.0.
r2eff=10.903/10.903 r2eff_err=0.0476/0.0922 i0=203455.021/203455.021 i0_err=837.8779/828.7280
R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 1341.1.
r2eff=10.684/10.684 r2eff_err=0.0446/0.0853 i0=218670.412/218670.411 i0_err=850.0210/830.9558
R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 1648.5.
r2eff=10.501/10.501 r2eff_err=0.0371/0.0742 i0=206502.512/206502.512 i0_err=794.0523/772.9843
R1rho at 799.8 MHz, for offset=124.247 ppm and dispersion point 1341.1.
r2eff=11.118/11.118 r2eff_err=0.0413/0.0827 i0=216447.241/216447.241 i0_err=784.6562/788.0384
R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point 800.5.
r2eff=7.866/7.866 r2eff_err=0.0347/0.0695 i0=211869.715/211869.715 i0_err=749.2776/763.6930
R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point 1341.1.
r2eff=9.259/9.259 r2eff_err=0.0331/0.0661 i0=217703.151/217703.151 i0_err=682.2137/685.5838
R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point 1648.5.
r2eff=9.565/9.565 r2eff_err=0.0373/0.0745 i0=211988.939/211988.939 i0_err=839.0313/827.0373
R1rho at 799.8 MHz, for offset=142.754 ppm and dispersion point 800.5.
r2eff=3.240/3.240 r2eff_err=0.0127/0.0253 i0=214417.382/214417.382 i0_err=595.8865/613.4378
R1rho at 799.8 MHz, for offset=142.754 ppm and dispersion point 1341.1.
r2eff=5.084/5.084 r2eff_err=0.0177/0.0352 i0=226358.691/226358.691 i0_err=660.5314/655.7670
R1rho at 799.8 MHz, for offset=179.768 ppm and dispersion point 1341.1.
r2eff=2.208/2.208 r2eff_err=0.0091/0.0178 i0=228620.553/228620.553 i0_err=564.8353/560.0873
R1rho at 799.8 MHz, for offset=241.459 ppm and dispersion point 1341.1.
r2eff=1.711/1.711 r2eff_err=0.0077/0.0155 i0=224087.486/224087.486 i0_err=539.4300/546.4217
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25240 | tlinnet | 2014-08-25 12:06:29 +0200 (Mon, 25 Aug 2014) | 3 lines
Add dependency check for scipy.optimize.leastsq.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25241 | tlinnet | 2014-08-25 12:26:21 +0200 (Mon, 25 Aug 2014) | 5 lines
Lowering precision in systemtest Relax_disp.test_r1rho_kjaergaard_missing_r1.
This is R1 estimation with: MODEL_NS_R1RHO_2SITE.
The lowering of precision is due different system precision.
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r25242 | tlinnet | 2014-08-25 12:31:52 +0200 (Mon, 25 Aug 2014) | 1 line
Re-used the dependency check "scipy_module", since leastsq() has been part of Scipy since 2003.
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r25243 | tlinnet | 2014-08-25 13:27:41 +0200 (Mon, 25 Aug 2014) | 8 lines
Moved target function for curve fitting with scipy into specific_analyses.relax_disp.estimate_r2eff.
This will later include the backend specific_analyses.relax_disp.optimisation.estimate_r2eff()
function and the code in the target_functions package.
The code in target_functions.relax_disp_curve_fit is a lot more than just a target function, so it doesn't really belong in this package.
This is also to isolate this experimental feature.
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r25244 | tlinnet | 2014-08-25 13:27:43 +0200 (Mon, 25 Aug 2014) | 5 lines
Isolated all code related to user function:
relax_disp.r2eff_estimate() into independent module file.
All has been isolated to: specific_analyses.relax_disp.estimate_r2eff.
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r25245 | tlinnet | 2014-08-25 15:22:55 +0200 (Mon, 25 Aug 2014) | 3 lines
Split function to minimise with scipy.optimize.leastsq out in estimate_r2eff module.
This is to prepare for implementing with minfx.
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r25246 | tlinnet | 2014-08-25 15:22:57 +0200 (Mon, 25 Aug 2014) | 3 lines
Implemented first try to minimise with minfx in estimate_r2eff() function.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25247 | tlinnet | 2014-08-25 15:27:49 +0200 (Mon, 25 Aug 2014) | 3 lines
Fix for missing imports.
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25248 | tlinnet | 2014-08-25 15:27:51 +0200 (Mon, 25 Aug 2014) | 3 lines
Removal of unnecessary imports in specific_analyses.relax_disp.optimisation().
task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.
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r25249 | bugman | 2014-08-25 15:28:43 +0200 (Mon, 25 Aug 2014) | 14 lines
Implementation of the target_functions.relax_fit.jacobian() function.
This follows from the discussions at http://thread.gmane.org/gmane.science.nmr.relax.devel/6807.
The function will calculate the Jacobian matrix for the exponential curve-fitting module. The
Jacobian can be used to directly calculate the covariance matrix, for example as described at
https://www.gnu.org/software/gsl/manual/html_node/Computing-the-covariance-matrix-of-best-fit-parameters.html.
The Jacobian is calculated using the help of the new exponential_dI() and exponential_dR() functions
in the target_functions/exponential.c file. These calculate the partial derivatives of the
exponential curve with respect to each model parameter separately.
The implementation still needs testing and debugging.
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r25250 | bugman | 2014-08-25 16:09:16 +0200 (Mon, 25 Aug 2014) | 5 lines
Fixes for the new target_functions.relax_fit.jacobian() function.
The Python list of lists is now correctly created and returned.
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r25251 | bugman | 2014-08-25 17:10:57 +0200 (Mon, 25 Aug 2014) | 8 lines
Turned off the optimisation constraints for the 'R2eff' model in the dispersion auto-analysis.
This follows from http://thread.gmane.org/gmane.science.nmr.relax.scm/22977/focus=6829.
This model does not require constraints at all, and the constraints only cause the optimisation to
take 10x longer to complete. Therefore the constraint flag has been set to False for the model.
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