Author: bugman Date: Fri Jan 13 04:25:38 2006 New Revision: 2330 URL: http://svn.gna.org/viewcvs/relax?rev=2330&view=rev Log: Relaxation curve fitting and error analysis is now fully functional! The ability to execute Monte Carlo simulations has been added, as well as Grace plotting capabilities. Now all parts of relaxation curve fitting data analysis are functional. However, the 'dfunc()' and 'd2func()' C functions have not be implemented and therefore only simplex minimisation without constraints is supported. The standard deviation in the relaxation curve fitting C module is now a Python array rather than a double. The data structure called 'intensities' has been changed to 'values' so that the 'maths_fns/c_chi2.c' chi-squared function is made more generic. In the common functions of 'specific_fns/base_class.py', the 'set_error()', 'sim_init_values()', 'sim_return_param()', and 'sim_return_selected()' functions have been added for Monte Carlo simulation functionality. The function 'sim_pack_data()' which was moved from 'specific_fns/model_free.py' to 'specific_fns/base_class.py' has been returned as it is not generalisable. A few bugs have been removed from 'specific_fns/relax_fit.py'. In the function 'assemble_param_vector()', Monte Carlo simulations are now properly supported. The 'create_mc_data()' function has also been improved. The function 'set_error()' has been removed from the file. This function was a relic as the origin of 'specific_fns/relax_fit.py' was from 'specific_fns/noe.py'. It hides the function of the same name in 'specific_fns/base_class.py' and hence causes Monte Carlo simulations to fail. The functions 'read_columnar_results()', 'write()', 'write_columnar_line()', and 'write_columnar_results()' have been deleted out of 'specific_fns/relax_fit.py'. These too were relics from the file's origin from 'specific_fns/noe.py'. The calculation of the peak intensity errors has been modified. The docstring in 'prompt/relax_fit.py' has been rewritten and significantly improved. Now if all spectra have been replicated, each relaxation time point will have its own error (which is averaged across all residues). If there are time points with only a single spectrum, then the standard deviations are averaged for all time points. In the data analysis chapter of the manual, the section on relaxation curve fitting has been half completed. Modified: 1.1/docs/latex/data_analysis.tex 1.1/docs/latex/docstring.tex 1.1/docs/relax.pdf 1.1/maths_fns/c_chi2.c 1.1/maths_fns/relax_fit.c 1.1/maths_fns/relax_fit.h 1.1/prompt/relax_fit.py 1.1/sample_scripts/relax_fit.py 1.1/specific_fns/base_class.py 1.1/specific_fns/model_free.py 1.1/specific_fns/relax_fit.py 1.1/specific_fns/specific_setup.py