[SciPy-dev] fmin_cg bug

[Robert Cimrman]

Hi,
the little script below revealed a little bug in scipy.optimize.fmin_cg:

before fix:
Warning: Desired error not necessarily achieved due to precision loss
          Current function value: 333283335000.000000
          Iterations: 0
          Function evaluations: 2
          Gradient evaluations: 1
after fix:
Optimization terminated successfully.
          Current function value: 0.000000
          Iterations: 5
          Function evaluations: 26
          Gradient evaluations: 26

I dared to commit the (little :) change to SVN.

r.

---
import numpy as nm
import scipy.optimize as opt

def f( x ):
     return nm.sum( x * x )

def fg( x ):
     return 2 * x

x0 = nm.arange( 100000, dtype = nm.float64 )
x = opt.fmin_cg( f, x0, fg )