Fitting of data is a very common task when analyzing measured data. This involves finding a formula that best describes the relationship between one or more independent variables to a dependent variable. LabVIEW provides easy-to-use VIs for a few commonly used formulae but often your data won’t be a good fit to any of these models. If that’s the case then more often than not you’ll want to use one of the Nonlinear Curve Fit VIs. LabVIEW’s Nonlinear Curve Fit VIs include several fitting algorithms like the Levenberg-Marquardt algorithm (LM) and the trust-region dogleg algorithm (TRDL). Whichever fitting algorithm is chosen, you’ll need to provide an initial estimation for each of the independent variables.

The Wakefield Engineering fitting package for LabVIEW does the hard work of calculating the initial guesses for you (and choosing the best algorithm). The free, soon to be released version makes it very easy to fit to some of the most commonly used functions including Gaussian, Super Gaussian, Extreme, Boltzmann, Sine, Exponential Growth and Lorentzian.