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General fitting framework
| General fitting framework [message #65276] |
Wed, 25 February 2009 10:03 |
Giorgio
Messages: 31
Registered: March 2008
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Member |
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Hi,
For my research work, the data analysis is often reduced to fit data
with a model. For that I often use MPfit which is a basically
Levenberg-Marquardt algorithm. In general this performs well however I
found that it depends a lot on the initial guess of the parameters and
it often gets stuck in a local minima. There are other open source
optimization algorithms written in IDL like genetic algorithms (Rob
Dimeo's code) or simulated annealing (Kling's book). I am thinking in
a way to implement a general fitting program that allow you to choose
which algorithm to use. The best way I thought it will be by using
object oriented programming. The different class objects can be:
- A class to hold the data, this can be either 2D or 1D data.
- A class to perform the function evaluations. The way that mpfit
treats the function is quite general. This would have the function
string and the number of parameters supported by the function. One
method will be the evaluation of the function with the values
positions where to do it.
- A function to evaluate the difference between the data and the
model function. This is usually the chi-squared function but it can
also be another one like the sum of the absolute difference. I did not
know yet which if the best approach is a function or an object.
- A class for the parameters to handle the parinfo structure define
in the mpfit program.
- And finally, a class to define a general framework for the
optimization algorithms. Each precise algorithm will be a child of
this class and will contain the algorithms parameters in it.
This is the general framework I thought about. By looking at this I
realized that it will take a lot of time for me alone to do it since I
will do it in my spare time. So my questions will be: Are there any
suggestions or ideas of which will be a better implementation of this?
And is there someone who will like to contribute or help me in doing
this?
Thanks,
Giorgio
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