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* Split out the interpolating in specific_analyses.relax_disp.data.plot_disp_curves() into separate function. This is to prepare for a interpolating function for spin-lock offset rather than spin-lock field strength for R<sub>1ρ</sub> models. [https://gna.org/support/?3124 Sr #3124]: Grace graphs production for R* Split out the interpolating in specific_analyses.relax_disp.data.plot_disp_curves() into separate function. This is to prepare for a interpolating function for spin-lock offset rather than spin-lock field strength for R<sub>1ρ</sub> models. [https://gna.org/support/?3124 Sr #3124]: Grace graphs production for R
* Added print out of chi2 to profile script. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Moved the creation of special numpy structures outside target function. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Modified profiling script to calculate correct values when setting up R2eff R<sub>2eff</sub> values. This is to test, that the return of chi2 gets zero. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Removing looping over exp and offset indices in calc_chi2. They are always 0 anyway. This brings a little speed. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* In profiling script, moved up the calculation of values one level. This is to better see the output of the profiling iterations for CR72.py. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Removed the masked replacement if fact is less than 1.0. This is very strange, but otherwise system test: Relax_disp.test_hansen_cpmg_data_missing_auto_analysis would fail. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Removed the slow allclose() function to test if R20A and R20B is equal. It is MUCH faster to just subtract and check sum is not 0.0. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Replaced the temporary variable R2eff R<sub>2eff</sub> with back_calc, and used numpy subtract to speed up. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Made the lib function into a pure numpy array calculation. This requires, that r20a, r20b and dw has same dimension as the dispersion points. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Changes too unit tests, so data is sent to target function in numpy array format. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Used the new class function: get_back_calc(), to get the data in the right structures when interpolating for graphs. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Removed superfluous check, after the returned data is now in right structure. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* Made changes to the dir argument of system test Relax_disp.test_r1rho_kjaergaard. This is to prepare for: [https://gna.org/support/?3124 sr #3124]: Grace graphs production for R<sub>1ρ</sub> analysis with R2eff R<sub>2eff</sub> as function of Omega_eff and [https://gna.org/support/?3138 sr #3138]: Interpolating theta through spin-lock offset [Omega], rather than spin-lock field strength [w1]. This is also to test an expected bug, if R1 is not loaded. [https://gna.org/task/?7807 Task #7807]: Speed-up of dispersion models for clustered analysis.
* The relaxation dispersion target function can now be set up when the optional frqs_H argument is None. This allows the profiling scripts to run.
* More stability fixes for the relaxation dispersion target function initialisation. The target function can now be initialised when the r1 and chemical_shift arguments are None.
* Modified the new print_model_title() specific analysis API method. This now accepts the prefix argument for creating different titles independently of the specific analysis.
* The grid search setup function now uses the prefix argument to the print_model_title() API function. This is simply set to 'Grid search setup:'.
* The relaxation dispersion API now uses the MODEL_R2EFF variable for identifying the [[R2eff ]] model.
* Changes to the minimise.grid_search user function frontend. The Boolean constraints argument has been shifted to the end, and empty lines have been removed.
* Epydoc docstring fixes for the keyword arguments of the pipe_control.minimise module.
* Small change to the table printed out during the minimise.grid_search setup.
* Fix for the skipping of preset parameters in the grid search. Dictionary and list type parameters are now handled correctly.
* Converted the relaxation dispersion analysis to the new grid bounds and scaling factor design. The parameter object now registers the grid bounds and scaling factors for all of the dispersion parameters. This includes the functions dw_lower(), dwH_lower(), pA_lower() and i0_upper() in the specific_analyses.relax_disp.parameter_object module for calculating some of these values. The specific_analyses.relax_disp.parameters.assemble_scaling_matrix() function has been deleted as this is now provided by the upstream code in pipe_control.minimise. And the API methods grid_search() and minimise() has been modified to accept the list of scaling matrices. As the grid bounds and increments are now handled by the upstream pipe_control.minimise.grid_setup() function, the specific_analyses.relax_disp.optimisation.grid_search_setup() function was redundant and was deleted. The specific_analyses.relax_disp.parameters.get_param_names() function was also modified with the full argument added, to allow either the base parameter names or an augmented form with the dictionary key for presenting to the user to be returned. Importantly to allow the changes to be operational, the model_loop() API method was redesigned so that, for the [[R2eff ]] base model, the individual spins rather than spin clusters will be looped over. This allows the specific_analyses.relax_disp.optimisation.minimise_r2eff() function to continue to operate correctly.
* Implemented the J(w) mapping analysis get_param_names() API method. This simply returns the hardcoded list of 3 parameters of the model, and allows the minimise.calculate user function to operate.
* Updated the _print_model_title_spin() specific API common method. This now accepts the prefix argument and adds this to the title.
* Expansion of the 'to do' section of the dispersion chapter of the manual.
* Editing of the 'to do' section of the dispersion chapter of the manual.
* Created the Bruker.test_bug_22411_T1_read_fail system test. This is to catch [https://gna.org/bugs/?22411 bug #22411] as reported by Olena Dobrovolska.
* Fix for system test Relax_disp.test_kteilum_fmpoulsen_makke_check_graphs where minimise has been extended with execute.
