Version history
IDAP 1.0
 Functions from Global Optimization toolbox are included as minimization algorithms. Their options may be set through corresponding properties of the TotalFit object
 Utilization of parallel processors for Global Optimization functions and MonteCarlo (when run on a multicore workstation) is included (Parallel Processing Toolbox is required). Distributed MonteCarlo's using deamons still utilize deamons running on individual cores (due to MathWorks limitations).
 Modes were renamed for the fit(mode) function to be 'single_cluster' and 'multiple_cores'.
 Synthax of model functions calls (parameter lists) is changed: include now the name of a solver and its options. Models that are solved numerically will use these parameters. Others will ignore them.
To migrate your own existing models you created for previous version of IDAPsimply include to extra parameters in the model function call (and not use them if you don't want):

In code/+equilibrium_thermodynamic_equations/:
U_model(Rtotal, LRratio, K_A, model_numeric_solver, model_numeric_options);
 In code/+line_shape_equations_1D/:
U_model_1D(parameters, X, model_numeric_solver, model_numeric_options)
 Transient kinetics module RapidMixingKinetics is included.
 The code for creating kinetic matrices for NMR line shapes was moved into code/+line_shape_equations_1D. The folder +line_shape_kinetic_matrices was removed.
 The following methods now require explicit solver and solver options given along with the model:
 Dataset: set_active_model()
 TotalFit: dataset_set_active_model()
 TotalFit: change_model_in_series()
 TotalFit: create_simulation_series()
 output functions output_figure() and re_export_results() are moved to code/+results_output
 Output arguments of functions calculating equlibrium concentration of species changed in +equilibrium_thermodynamic_equations/. Now it returns a single vector of concentrations and a single cell array of names of species.
 The 1D line shape models no longer normalize concentrations by total concentration of the receptor. Instead, ScaleFactor will take care of normalization in the model. I did it because some models will include two different receptors (a model with mixture)then this normalization becomes ambiguous. As result, spectral intensity now takes values in a range of 1e4.