[SciPy-User] fmin_bfgs failing on simple problem

John Salvatier jsalvati@u.washington....
Tue Apr 17 12:35:29 CDT 2012

Hi all!

I am having a problem with the fmin_bfgs solver that's surprising to me.
Here's the toy problem I've set up:

from scipy.optimize import fmin_bfgs, fmin_ncg
from numpy import *
import numpy as np

def f(x ):
    if x < 0:
        return 1.79769313e+308
    else :
        return x + 1./x

xs = fmin_bfgs(f, array( [10.]), retall = True)

The solver returns [nan] as the solution.

The problem is designed to be stiff: between 0 and 1, it slopes upward to
infinity but between 1 and infinity, it slopes up at a slope of 1. Left of
0 the function has a "nearly infinite" value. If bfgs encounters  a value
that's larger than the current value, it should try a different step size,
no? Why does fmin_bfgs fail in this way?

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