Two Python implementations of fitting a sum of exponentials to numerical data. I haven't tested both carefully, but method 2 seems to work better:
- Based on Kaufmann (2003) "Fitting a Sum of Exponentials to Numerical Data".
- Based on scipy.optimize differential evolution
Note: The kaufmann implementation finds the best fit assuming the exponential
does not decay to zero, whereas the diffevol implementation does assume the
exponential decays to zero.
##TODO
- add error analysis (note: proper error analysis would probably include basin hopping, but that's probably too sophosticated)
- describe algorithm