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View Code? Open in Web Editor NEWFinding ways to solve ill-conditioned systems efficiently
Finding ways to solve ill-conditioned systems efficiently
I see you are writing Python code using scipy.optimize.minimize(), and have the initial parameter array x_0 as random numbers. The authors of scipy have added a genetic algorithm for initial parameter estimation for use with their non-linear solvers, the module is named scipy.optimize.differential_evolution and uses the Latin Hypercube algorithm to ensure a thorough search of parameter space.
I have used scipy's Differential Evolution genetic algorithm to determine initial parameters for fitting a double Lorentzian peak equation to Raman spectroscopy of carbon nanotubes and found that the results were excellent. The GitHub project, with a test spectroscopy data file, is:
https://github.com/zunzun/RamanSpectroscopyFit
If you have any questions, please let me know. My background is in nuclear engineering and industrial radiation physics, and I love Python, so I will be glad to help.
James Phillips
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