[SciPy-user] optimize.fmin_l_bfgs_b and 'ABNORMAL_TERMINATION_IN_LNSRCH',

[Ryan Krauss]

I am using optimize.fmin_l_bfgs_b and getting the following output:

(array([ 8142982.47310469,        0.        ,   614438.11725001]),
 1.58474444864e+12,
 {'funcalls': 21,
  'grad': array([      0.    ,  952148.4375,   24414.0625]),
  'task': 'ABNORMAL_TERMINATION_IN_LNSRCH',
  'warnflag': 2})

What does this mean?  I am trying to do a least squares curve fit between
some noisy data and a nonlinear model.  I need to constrain one of my fit
parameters to be positive.  I do not have an fprime function, so the
gradient is being determined numerically.

Is there a better routine to use?

I get a fairly close answer using my own hacked solution of using
optimize.fmin where the cost function adds a gigantic penalty to the cost if
the middle coefficient is greater than 0:
[  8.16174249e+06   1.93528613e-10   6.14626152e+05]

So, I don't think the answer is bad, I just want to know why it terminated
abnormally and whether or not I can trust the result.

Thanks,

Ryan
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