Fitting only one parameter of a function with many parameters in python

Question

In python I have a function which has many parameters. I want to fit this function to a data set, but using only one parameter, the rest of the parameters I want to supply o

Answer 1

A better approach would use lmfit, which provides a higher level interface to curve-fitting. Among other features, Lmfit makes fitting parameters be first-class objects that can have bounds or be explicitly fixed (among other features).

Using lmfit, this problem might be solved as:

from lmfit import Model
def func(x,a,b):
   return a*x*x + b

# create model
fmodel = Model(func)
# create parameters -- these are named from the function arguments --
# giving initial values
params = fmodel.make_params(a=1, b=0)

# fix b:
params['b'].vary = False

# fit parameters to data with various *static* values of b:
for b in range(10):
   params['b'].value = b
   result = fmodel.fit(ydata, params, x=x)
   print(": b=%f, a=%f+/-%f, chi-square=%f" % (b, result.params['a'].value, 
                                             result.params['a'].stderr,
                                             result.chisqr))