[SciPy-User] Simple root solving issues

Gökhan Sever gokhansever@gmail....
Sun Oct 24 15:43:34 CDT 2010


I have a simple test case below:

#!/usr/bin/env python

import numpy as np
from scipy.optimize import leastsq, fsolve

def fitfunc(gsd):
    #return dH_dlogDP1 -
    return dH_dlogDP1 - (h1.sum()/((2*np.pi)**0.5*np.log(gsd)))

dH_dlogDP1 = np.array([ 869.11014589])
Dp1 = np.array([ 0.02994996])
h1 = np.array([ 1906.7283])

res = leastsq(fitfunc, x0=1.5)
res2 = fsolve(fitfunc, x0=1.0)

return terms in fitfunc are equivalent since np.exp(-0) = 1
I hand-solve this equation and find gsd as ~2.4. Both leastsq and
fsolve requires initial estimates to work properly. Now the problem is
they are very sensitive
to the selection of initial parameter. x0=1.5 works (gives ~2.39)
whereas x0=1.0 situation can't estimate a solution.

Is there a way to improve this sensitive init estimate issue with an
alternative approach?



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