Copyright 2014-2020 by Evgueni Kovriguine
IDAP is an environment and a set of libraries for analysis of different kinds of data. Main focus in development of IDAP was to enable simultaneous fitting of multiple datasets, particularly - of different kinds of experiments. The key benefit of such simultaneous fitting is that when we study some experimental system, all measurements that we record are governed by the same molecular parameters. Therefore, combining datasets of different kinds may enable determination of these molecular parameters with improved accuracy. One has to keep in mind, though, that combining multiple kinds of data in one fitting session it requires a decision on an individual weight of each technique in the total sum of squares. Different kinds of data cannot be all assigned the same, "equal" weight because sums of squares in different measurements may differ by an order of magnitude due to specifics of the measurements. These relative weights cannot have a solid theoretical ground and will always be set according to a conventional research practice.
For the theory and test examples see Model derivations, implementation and testing and Tutorials.
All non-trivial mathematical derivations that produced equations for various modules in IDAP are documented in the form of MuPad notebooks and their HTML representations. I also conducted testing of IDAP implementations of most of them here. The user is invited to examine and rerun notebooks to better understand inner workings of the mathematical models used in fitting and simulations. The folder Mathematical_models/ contains definitions, derivation of equations and test simulations for:
For more examples see Tutorials.
For the theory and test examples see Model derivations, implementation and testing and Tutorials.
Tutorials are summarized in a dedicated document: Tutorial_index.htm