4.50 sddsgenericfit

• description: sddsgenericfit does fits to an arbitrary functional form specified by the user.
• examples: Fit a gaussian to a beam profile to get the rms beam size. In this example, the file beamProfile.sdds is assumed to contain data to be fit in columns x and Intensity.

  sddsgenericfit beamProfile.sdds beamProfile.gfit -column=x,Intensity
   ‘‘-equation=height x center - sqr 2 / sigma sqr / exp / baseline + Intensity - sqr’’
   -variable=name=height,start=1,lower=0,upper=10,step=0.1
   -variable=name=center,start=0,lower=-10,upper=10,step=0.1
   -variable=name=sigma,start=1,lower=0.1,upper=10,step=0.1
   -variable=name=baseline,start=0,lower=-1,upper=1,step=0.1

• synopsis:

  sddsgenericfit [-pipe=[input][,output]] [inputfile] [outputfile] -columns=x-name,y-name[,ySigma=sy-name] -equation=string[,algebraic] [-target=value] [-tolerance=value] [-simplex=[restarts=integer][,cycles=integer,][evaluations=integer]] -variable=name=name,lowerLimit=value,upperLimit=value,stepsize=value,startingValue=value[,units=string][,heat=value] [-variable=...] [-verbosity=integer] [-startFromPrevious]

• files: inputFile contains the columns of data to be fit. If inputFile contains multiple pages, each page of data is fit separately. outputFile has columns containing the independent variable data and the corresponding values of the fit. The name of the column is constructed by appending the string Fit to the name of the dependent variable. The name of the residual column is constructed by appending the string Residual to the name of the dependent variable. outputFile also contains parameters giving the values of the fit parameters.
• switches:
  • -pipe=[input][,output] — The standard SDDS Toolkit pipe option.
  • -columns=x-name,y-name[,ySigma=name] — Specifies the names of the independent and dependent columns of data, and optionally the name of the column containing the errors in the dependent column.
  • -equation=string[,algebraic] — Specifies the functional form of the fit, y(x,{p₁,p₂,...}), where {p₁,p₂,...} represents the parameters of the function and x is the independent variable value. The fitting process attempts to minimize the penalty function ∑ _i=0^N-1(y(x_i,{p₁,p₂,...})-y_i)² (or ∑ _i=0^N-1(y(x_i,{p₁,p₂,...})-y_i)²∕σ_y,i² if y sigma values are given) by changing the values of the parameters {p₁,p₂,...}.
  • -tolerance=value — Specifies the minimum change in the (weighted) rms residual that is considered significant enough to justify continuing optimization.
  • -simplex=[restarts=nRestarts][,cycles=nCycles,][evaluations=nEvals] — Specifies parameters of the simplex optimization used to perform the fit. Each start or restart allows nCycles cycles with up to nEvals evaluations of the function. Defaults are 10 restarts, 10 cycles, and 5000 evaluations.
  • -variablename=name,lowerLimit=value,upperLimit=value,stepsize=value,startingValue=value[,units=string][,heat=value] — Specifies a parameter of the fitting function. If the heat qualifier is given, then prior to each restart the code “heats” the values by adding random numbers to the result of the last iteration. This can help avoid getting stuck in a local minimum. You must give one variable option for every parameter of the fit.
  • -startFromPrevious — Meaningful for multipage input files only. If given, then the optimization for each page starts from the parameter values from the fit to the previous page. By default, fitting for each page starts from the values specified on the commandline.
  • -verbosity=integer — Specifies that informational printouts are desired during fitting. A larger integer produces more output.
• see also:
  • sddsexpfit
  • sddsgfit
  • sddsoutlier
  • sddspfit
• author: M. Borland, ANL/APS.