[Numpy-discussion] hold parameters

Bevan Jenkins bevan07@gmail....
Mon Aug 1 19:43:28 CDT 2011


Hello,

I have a function that I fitting to a curve via scipy.optimize.leastsq.  The 
function has 4 parameters and this is all working fine.

For a site, I have a number of curves (n=10 in the example below).  I would 
like to some of the parameters to be the best fit across all curves (best fit 
for a site) while letting the other parameters vary for each curve.  I have 
this working as well.

The issue I have is like to be able to vary this for a run.  That is do a run 
where parameter1 is best fit for entire site, whith the remaining three 
varying per curve. Then on the next run, have two parameters being held or 
fitted for all curves at one.  Or be able to do a run where all 4 parameters 
are fit for each individual curve.

Using my e.g. below, if I change the 'fix' dict, so that 'a','b', and 'c' are 
True, with 'd' False, then I will have to change the zip to
for a,b,c in zip(a,b,c):
    solve(a,b,c,d)
 
I would prefer to find a way to do this via code.  I hope this example makes 
sense.  The code below is all within my objective function that is being 
called by scipy.optimize.leastsq.
import numpy as np

def solve(a,b,c,d):
    print a,b,c,d
    #return x*a*b*c*d


    
fix = {"a":True,"b":True,"c":False,"d":False}

n=10
params = np.array([0,1,2,3]*n)
params = params.reshape(-1,4)

if fix["a"] is True:
    a = params[0,0]
else:
    a = params[:,0]
if fix["b"] is True:
    b = params[0,1]
else:
    b = params[:,1]
if fix["c"] is True:
    c = params[0,2]
else:
    c = params[:,2]
if fix["d"] is True:
    d = params[0,3]
else:
    d = params[:,3]

res=[]
for c,d in zip(c,d):
    res = solve(a,b,c,d)
    #res = solve(a,b,c,d)-self.orig
#return np.hstack(res)**2 



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