Returns the amplitude, center, and standard deviation of the Gaussian fit for a data set (X, Y).


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Inputs/Outputs

  • cnclst.png initial guess —

    initial guess specifies the initial guesses of amplitude, center, standard deviation, and offset for use in the iterative algorithm. If initial amplitude, initial center, initial standard deviation, or initial offset is NaN, this VI calculates the initial guess automatically.

  • cdbl.png initial amplitude —

    initial amplitude is the initial guess of amplitude.

  • cdbl.png initial center —

    initial center is the initial guess of center.

  • cdbl.png initial standard deviation —

    initial standard deviation is the initial guess of standard deviation.

  • c1ddbl.png Y —

    Y is the array of dependent values. Y must contain at least three points.

  • c1ddbl.png X —

    X is the array of independent values. X must be the same size as Y.

  • c1ddbl.png Weight —

    Weight is the array of weights for the observations (X, Y). Weight must be the same size as Y. Weight also must contain non-zero elements. If an element in Weight is less than 0, the VI uses the absolute value of the element.

    If you do not wire an input to Weight, the VI sets all elements of Weight to 1.

  • cdbl.png tolerance —

    tolerance determines when to stop the iterative adjustment of amplitude, center, and standard deviation. If the relative difference of the weighted mean error of the Gaussian fit in two successive iterations is less than tolerance, this VI returns the resulting amplitude, center, and standard deviation.

    If tolerance is less than or equal to 0, this VI sets tolerance to 0.0001.

  • cu16.png method —

    method specifies the fitting method.

    0Least Square (default)
    1Least Absolute Residual
    2Bisquare
  • idbl.png amplitude —

    amplitude returns the amplitude of the fitted model.

  • idbl.png center —

    center returns the center of the fitted model.

  • idbl.png standard deviation —

    standard deviation returns the standard deviation of the fitted model.

  • ii32.png error —

    error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster.

    • This VI is similar to the Gaussian Peak Fit VI but does not return the y-values or weighted mean error of the fitted model.