[proFit-list] Repetitive fit using pro Fit 6.2.2

[proFit Support]

Dear Christian

There seems to be a bug here. We are investigating this. However, I presently understand that the fit would run correctly, but the check for empty columns is executed with the wrong parameters. So try to make sure that column 1 is not empty, and then run the fit again.

Best regards

Kurt Sutter
QuantumSoft

On 7. Feb 2011, at 5:56, Scott Lasley wrote:

> It appears that the fit still uses columns 1 and 2 even after setting xColumn=2 and yColumn=3 in pf.FitSetExperiment. the line print fitObj in the code below shows xColumn = 2 and yColumn = 3, but if column 1 is empty the call to pf.FitExecute fails with the error   "Python exception: Empty columns cannot be used".  If column 1 contains the x data, column 2 contains the y data and column 3 is empty the fit works (after holding A constant in the Parameters window) even though xColumn=2 and yColumn=3 in pf.FitSetExperiment
> 
> 
> 
> fitObj = pf.FitCreate(function = 'Exp')
> pf.FitSetArguments(fitObject = fitObj, algorithm = pf.robust, printResults = True, \
>                   onlyActiveParameters = False, fullDescription = True)
> pf.FitSetExperiment(fitObject = fitObj, window =  pf.GetCurrentWindow(pf.dataType), \
>                    xColumn = 2, yColumn = 3 )
> print fitObj
> fitResultObj = pf.FitExecute(fitObject = fitObj)
> n = pf.FitResult(fitResultObject = fitResultObj, result = pf.nrFittedParameters)
> print 'Number of parameters fitted:', n 
> pf.FitResultDispose(fitResultObject = fitResultObj)
> pf.FitDispose(fitObject = fitObj)
> ----
> column 1 empty, column 2 x, column 3 y
> 
> function               : Exp
> algorithm              : robust
> guessInitialParameters : True
> stopIfError            : True
> doErrorAnalysis        : False
> iterations             : 500
> confidence             : 68.3
> printResults           : True
> onlyActiveParameters   : False
> fullDescription        : True
> autoSearch             : True
> stopCounter            : 0
> localParameters        : -1
> 
> experiment               : 1
> 1 - window               : test.data
> 1 - selectedRowsOnly     : False
> 1 - input                : 0
> 1 - xColumn              : 2
> 1 - xErrorKind           : zeroError
> 1 - xErrorColumn         : 0
> 1 - xError               : 1
> 1 - xErrorDistribution   : gaussianDistribution
> 1 - output               : 0
> 1 - yColumn              : 3
> 1 - yErrorKind           : zeroError
> 1 - yErrorColumn         : 0
> 1 - yError               : 1
> 1 - yErrorDistribution   : gaussianDistribution
> 1 - localParameterValue  : 
> 
> 
> Python exception: Empty columns cannot be used.
> Traceback (most recent call last):
>  File "Untitled Function 1", line 7, in <module>
> ----
> same function, column 1 x, column 2 y, column 3 empty
> 
> function               : Exp
> algorithm              : robust
> guessInitialParameters : True
> stopIfError            : True
> doErrorAnalysis        : False
> iterations             : 500
> confidence             : 68.3
> printResults           : True
> onlyActiveParameters   : False
> fullDescription        : True
> autoSearch             : True
> stopCounter            : 0
> localParameters        : -1
> 
> experiment               : 1
> 1 - window               : test.data
> 1 - selectedRowsOnly     : False
> 1 - input                : 0
> 1 - xColumn              : 2
> 1 - xErrorKind           : zeroError
> 1 - xErrorColumn         : 0
> 1 - xError               : 1
> 1 - xErrorDistribution   : gaussianDistribution
> 1 - output               : 0
> 1 - yColumn              : 3
> 1 - yErrorKind           : zeroError
> 1 - yErrorColumn         : 0
> 1 - yError               : 1
> 1 - yErrorDistribution   : gaussianDistribution
> 1 - localParameterValue  : 
> 
> 
> ===========================================
> Fit Algorithm:	Robust
> 
> Function  :	Exp
> Descr 1  :	y = A * exp(-(x-x0)/t0)  + const
> Descr 2  :	exponential function
> 
> Data      :	test.data
> 
> output    :	y
> y  column:	Column 2
> ∆y value :	0.0
> ∆y distr.:	Gaussian
> 
> input     :	x
> x  column:	Column 1
> ∆x value :	0.0
> ∆x distr.:	Gaussian
> 
> 
> Iterations:	390
> -------------------------------------------
> Chi squared       	=	1.68866816e-33
> 
> Parameters:
> A    	=	 1.00000000
> x0   	=	 2.00000000
> t0   	=	30.00000000
> const	=	 2.10254858e-17
> 
> Number of parameters fitted: 4.0
> 
> 
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