I'd like to be able to perform fits that allows me to fit an arbitrary curve function to data, and allows me to set arbitrary bounds on parameters, for example I want to fit function:
f(x) = a1(x-a2)^a3\cdot\exp(-\a4*x^a5)
and say:
a2
is in following range:(-1, 1)
a3
anda5
are positive
There is nice scipy curve_fit function, but it doesn't allow to specify parameter bounds. There also is nice http://code.google.com/p/pyminuit/ library that does generic minimalization, and it allows to set bounds on parameters, but in my case it did not coverge.
Note: New in version 0.17 of SciPy
Let's suppose you want to fit a model to the data which looks like this:
and with the constraint on alpha
while other parameters a and b remains free. Then we should use the bounds option of curve_fit in the following fashion:
Source is here.