[SciPy-user] Optimization Working only with a Specific Expression of the input Parameters

Brandon Nuttall bnuttall@uky....
Fri Mar 2 07:50:53 CST 2007


Hello,

I'm just an amateur, but it seems to me like the array data in myvar1 are 
likely integers. When you raise the data to a power of type float (i.e. 
2.0) all the members of the array are automatically converted to real 
(float) types. Easiest and fastest thing I know to do would be:

      myvar1 = myvar1*1.0

Or, and probably preferred (assuming you are using the numpy array type and 
have imported it):

      myvar1 = numpy.array(myvar1,dtype=float)

Brandon

At 08:25 AM 3/2/2007, you wrote:
>Dear All,
>I was trying to fit some data using the leastsq package in
>scipy.optimize. The function I would like to use to fit my data is:
>
>log(10.0)*A1/sqrt(2.0*pi)/log(myvar1)*exp(-((log(x/mu1))**2.0)/2.0/log(myvar1)/log(myvar1)))
>
>  where A1, mu1 and myvar1 are fitting parameters.
>For some reason, I used to get an error message from scipy.optimize
>telling me that I was not working with an array of floats.
>I suppose that this is due to the fact that the optimizer also tries
>solving for negative values of mu1 and myvar1, for which the log
>function (x is always positive) does not exist.
>In fact, if I use the fitting function:
>
>log(10.0)*A1/sqrt(2.0*pi)/log(myvar1**2.0)*exp(-((log(x/mu1**2.0))**2.0)/2.0/log(myvar1**2.0)/log(myvar1**2.0)))
>
>Where mu1 and myvar1 appear squared, then the problem does not exist
>any longer and the results are absolutely ok.
>Can anyone enlighten me here and confirm this is what is really going on?
>Kind Regards
>
>Lorenzo
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Brandon C. Nuttall

BNUTTALL@UKY.EDU                         Kentucky Geological Survey
(859) 257-5500                                     University of Kentucky
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