relax SVN archive

Added several tests to: test_estimate_r2eff_error, to compare different output from algorithms.

task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.

Fix to systemtest test_estimate_r2eff_error(), to first delete the old error estimations.

task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.

Added back-end to estimate R2eff errors.

task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.

Modified systemtest Relax_disp.test_estimate_r2eff() to first do a Grid Search, then minimise and then estimate the errors for R2eff and i0.

task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.

Added method to automatically perform error analysis on peak heights.

task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.

Added front-end to the new user function relax_disp.r2eff_err_estimate(), which will estimate the R2eff errors
from a pipe and spins with optimised values of R2eff and i0.

The co-variance matrix can be calculated from the optimised parameters, and the Jacobian.

Big care should be taken not to directly trust these results, since the errors are quite different compared to the Monte-Carlo simulations.

This implementation, will reach the exact same error estimation as scipy.optimize.leastsq.

But with much better control over the data, and insight into the calculations.

task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.

Removed the user function to estimate the R2eff values and errors with scipy.optimize.leastsq.

With the newly implemented Jacobian and Hessian of the exponential decay function, the front-end to
scipy.optimize.leastsq does not serve a purpose.

This is because minfx is now as fast as scipy.optimize.leastsq, and can estimate the errors from the
Jacobian to the exact same numbers as scipy.optimize.leastsq.

In addition to that, the covariance can be calculated by QR decomposition.
This adds additional feature for checking for a singular matrix.

The back-end wilÃl still be kept in place for the coming tim, but could be removed later.

task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting.

Merged revisions 25344 via svnmerge from
svn+ssh://bugman@.../svn/relax/trunk

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r25344 | bugman | 2014-08-27 18:56:05 +0200 (Wed, 27 Aug 2014) | 6 lines

Clean up of the declarations in the target_functions.relax_fit C module.

The Python list objects are now declared at the start of the functions, and then PyList_New() is
called later on. This allows the code to compile on certain Windows systems.
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Clean up of the declarations in the target_functions.relax_fit C module.

The Python list objects are now declared at the start of the functions, and then PyList_New() is
called later on. This allows the code to compile on certain Windows systems.

Merged revisions 25337-25341 via svnmerge from
svn+ssh://bugman@.../svn/relax/trunk

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r25337 | tlinnet | 2014-08-27 14:23:41 +0200 (Wed, 27 Aug 2014) | 12 lines

By using minfx, and the reported Jacobian, it is now possible to get the exact same error estimation as scipy.optimize.leastsq.

The fatal error was to set the weighting matrix with diagonal elements as the error.
There weights are 1/errors**2.

There is though some un-answered questions left.

The Jacobian used, is the direct derivative of the function.

It is not the chi2 derivative Jacobian.

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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r25338 | tlinnet | 2014-08-27 17:16:04 +0200 (Wed, 27 Aug 2014) | 3 lines

Fixed naming of functions, to better represent what they do in module of estimating R2eff.

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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r25339 | tlinnet | 2014-08-27 17:16:07 +0200 (Wed, 27 Aug 2014) | 5 lines

Implemented the Jacobian of exponential function in Python Code.

This now also gets the same error as leastsq and C code.

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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r25340 | tlinnet | 2014-08-27 17:16:09 +0200 (Wed, 27 Aug 2014) | 3 lines

Tried to implement a safety test for linearly-dependent columns in the co-variance matrix.

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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r25341 | bugman | 2014-08-27 17:40:27 +0200 (Wed, 27 Aug 2014) | 6 lines

Fixes for the relax_disp.r2eff_estimate user function documentation.

This is to allow the relax manual to compile again as the original documentation was causing LaTeX
failures.
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