relax SVN archive

Fix for also storing 'r1_fit' to cdp even though it is set to False.

bug #22541(https://gna.org/bugs/?22541): The R1 fit flag does not work in the GUI.

Improved systemtest test_bug_negative_intensities_cpmg, by counting number of R2eff points.

Spin 4, which has one negative intensity, is expected to have one less R2eff point.

This makes sure, that all CPMG data set can be loaded and analysed, even if some peaks are very weak
are fluctuating with error level.

Added more print out information, when log(I / I_ref) is negative, and raising errors.

This can help the user track back information to the error more easily.

Modified systemtest test_estimate_r2eff_err_methods, to check all Jacobian methods are correctly implemented.

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

Modified module to estimate R2eff errors, to use the C-code Jacobian.

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

Added a script and log for calculating the exponential curve parameter errors via bootstrapping.

This uses the data at http://thread.gmane.org/gmane.science.nmr.relax.devel/6807/focus=6840 and
calculates the parameter errors via bootstrapping. As the parameters at the minimum are the exact
parameter values, bootstrapping and Monte Carlo simulation converge and hence this is a true error
estimate. 200,000 simulations where used, so the parameter errors are extremely accurate.

Added a script and log for calculating the numerical covariance matrix for an exponential curve.

This uses the data at http://thread.gmane.org/gmane.science.nmr.relax.devel/6807/focus=6840 and
calculates the covariance matrix via the Jacobian calculated using the numdifftools.Jacobian object
construct and obtain the matrix, both at the minimum and at a point away from the minimum. The
covariance is calculated as inv(J^T.W.J).

Created two unit tests showing the target_functions.relax_fit.jacobian_chi2() function is correct.

This compares the calculated chi-squared Jacobian to the numerically integrated values from the
test_suite/shared_data/curve_fitting/numeric_topology/jacobian_chi2.py script.

Fix for the chi-squared Jacobian numerical approximation script.

The function was modified to that a list of chi-squared elements are returned, i.e. the sum part of
the chi-squared equation has been removed.

Added a script and log for calculating the numerical chi-squared Jacobian for an exponential curve.

This uses the data at http://thread.gmane.org/gmane.science.nmr.relax.devel/6807/focus=6840 and
calculates the chi-squared Jacobian using the numdifftools.Jacobian object construct and obtain the
matrix, both at the minimum and at a point away from the minimum. The values will be used to
construct a unit test to check the C module implementation.